diff --git "a/example_source/vector/storage_nodes/docstore.json" "b/example_source/vector/storage_nodes/docstore.json" new file mode 100644--- /dev/null +++ "b/example_source/vector/storage_nodes/docstore.json" @@ -0,0 +1 @@ +{"docstore/data": {"c981a5ff-129f-48a9-bd42-69efa603ecbf": {"__data__": {"id_": "c981a5ff-129f-48a9-bd42-69efa603ecbf", "embedding": null, "metadata": {"page_label": "i", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "What is the title of the book authored by David R. Martinez and Bruke M. Kifle, and what is its primary focus?", "excerpt_keywords": "Keywords: Artificial Intelligence, Systems Approach, MIT Press"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "71a4b630-2c38-40aa-a026-c02c2765bd38", "node_type": "4", "metadata": {"page_label": "i", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "658f532b23a238011b905c0b883f5273bbda5383d43a578d74e9c3ad1f009149", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "The MIT Press\nCambridge, Mas\n \nsa\n \nchu\n \nsetts \nLondon, E\nngland\nArtificial Intelligence\nA Systems Approach from Architecture \nPrinci\n ples to Deployment\nDavid\u00a0R. Martinez and Bruke M. Kifle\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 272, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "7a940454-ad69-41cf-a0d7-58d4d956c6a7": {"__data__": {"id_": "7a940454-ad69-41cf-a0d7-58d4d956c6a7", "embedding": null, "metadata": {"page_label": "ii", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the names of the authors of the book \"Artificial Intelligence: A Systems Approach from Architecture Principles to Deployment\"?\n\nThis question is unlikely to be answered elsewhere without access to the specific publication details, as it directly references the authorship of a particular book along with its publication information.", "excerpt_keywords": "Keywords: Artificial Intelligence, Systems Approach, MIT Press"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "614a3eda-cd16-432b-978b-8d1a12f12804", "node_type": "4", "metadata": {"page_label": "ii", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "845a7f5cb8f7d9b467306af305b6bdc0c45c18fd1849efc2d76cd399dc9e98d9", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "\u00a9 2024 Mas sa chu setts Institute of T echnology\nAll rights r\neserved. No part of this book may be used to train artificial intelligence systems or \nreproduced in any form by any electronic or mechanical means (including photocopying, \nrecording, or information storage and retrieval) without permission in writing from the publisher.\nThe MIT Press would like to thank the anonymous peer reviewers who provided comments on \ndrafts of this book. The generous work of academic experts is essential for establishing the \nauthority and quality of our publications. We acknowledge with gratitude the contributions of \n these other wise uncr\nedited readers.\nThis book was set in Adobe Garamond Pro and HelveticaNeue by Westchester Publishing \nServices. Printed and bound in the United States of Amer\n i\n ca.\nLibrar\ny of Congress Cataloging-in-Publication Data\nNames: Martinez, David R., author. | Kifle, Bruke, author. \nTitle: Artificial intelligence : a systems approach from architecture principles to deployment / \nDavid R. Martinez, Bruke Kifle.\nDescription: Cambridge : The MIT Press, 2024. | Series: Lincoln laboratory series | \nIncludes bibliographical references and index.\u00a0\nIdentifiers: LCCN 2023030187 (print) | LCCN 2023030188 (ebook) | ISBN 9780262048989 \n(hardcover) | ISBN 9780262378710 (epub) | ISBN 9780262378703 (pdf) \u00a0\nSubjects: LCSH: Artificial intelligence\u2014Industrial applications. | Systems engineering.\u00a0\nClassification: LCC TA347.A78 M37 2024\u00a0 (print) | LCC TA347.A78\u00a0 (ebook) | \nDDC 006.3\u2014dc23/eng/20231121\u00a0\nLC record available at https://lccn.loc.gov/2023030187\nLC ebook record available at https://lccn.loc.gov/2023030188\n10\n \n9\n \n8\n \n7\n \n6\n \n5\n \n4\n \n3\n \n2\n \n1\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 1, "end_char_idx": 1760, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "0338c72e-f324-4cfd-8b5a-84609ae126c4": {"__data__": {"id_": "0338c72e-f324-4cfd-8b5a-84609ae126c4", "embedding": null, "metadata": {"page_label": "1", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "What is the significance of a strategic road map in the development and deployment of AI capabilities within an organization, as discussed in Part II of the book?", "excerpt_keywords": "Keywords: AI strategy, deployment roadmap, organizational framework"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "e7882645-e149-4be4-9a00-7e27484ed8fe", "node_type": "4", "metadata": {"page_label": "1", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "2a7b5ff2a17a76974546e1b7826f7416b0967644ea8b4ac4c6af2203c29cdb59", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "287 \nWithout strategy, execution is aimless. Without execution, strategy is useless.\n\u2014\n M\norris Chang, \n founder and former CEO of \nTaiwan Semiconductor Manufacturing \nCom\n \npany (TSMC)\nIn part I of the book, as illustrated in figure\u00a01.1\u00a0in chapter\u00a01, we presented an overview \nof the artificial intelligence (AI) system architecture, elaborated on the fundamentals of \nsystems engineering, and described in detail the key architecture subcomponents. These\n \nchapters helped the reader gain a deeper understanding of the building blocks used in \nthe development of AI products and \n ser\nvices.\n These building blocks, acr\noss the AI pipeline, are necessary to transform data input \ninto insights. The created insights are delivered as AI value in the form of predictions \nor classifications to the ultimate stakeholders. However, to successfully deliver busi-\nness value, it is imperative that AI prac\n ti\n tion\n ers institute \na systematic approach within \ntheir respective \n organizations that conforms to a w\nell-\n defined strategy and associated \nr\noad map.\nPart II begins with chapter\u00a09, which discusses the steps involved in the formulation \nof an AI strategy, culminating in a strategic road map. The strategic road map serves as \nthe blueprint for upper management, technical leaders, AI architects, designers, and \nimplementers to pro\n gr\ness from architecture princi\n ples to deplo\nyment. The strategic \nroad map, also referred to as the \u201cstrategic blueprint,\u201d must be an integral part of any \nAI-\n based \n organization to successfully dev\nelop and deploy AI capabilities.\nDuring his illustrious \n car\neer as an engineer, man\n ag\n er\n, and business leader, Morris \nChang, the \n founder and former chief ex\necutive officer (CEO) of the Taiwan Semicon-\nductor Manufacturing Com\n pany (\nTSMC), emphasized the importance of formulating \na strategy and executing that strategy\u2014\n meaning \nto \u201cplan the work and work the plan.\u201d \n9\nAI Strategy and Road Map\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2037, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "bc4be34e-f24b-4796-8f4d-52ff116be0cf": {"__data__": {"id_": "bc4be34e-f24b-4796-8f4d-52ff116be0cf", "embedding": null, "metadata": {"page_label": "2", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the five steps outlined by Andrew Ng for leading a company into the AI era, and how do they relate to the development of an AI strategy?\n\nThis question directly pertains to the specific content discussed in the chapter, particularly the five-step playbook presented by Andrew Ng, which is not likely to be found in other sources without referencing this specific context.", "excerpt_keywords": "Keywords: AI strategy, pilot projects, in-house AI team"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "5c62b578-be64-429c-b876-8c787380d92d", "node_type": "4", "metadata": {"page_label": "2", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "81a310bf228d98454517ea9d64db51ceca014387c8b77d64b38321ddd99f1a25", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "288 Chapter 9: AI Strategy and Road Map\nThe strategy is the cornerstone for leaders and team members to identify their collective \nefforts under \na unified AI strategic direction, to work to\nward a set of well-\n defined \ngoals \nand establish actionable milestones.\nOne of this book\u2019s authors, David Martinez, with his colleagues Stephen Rejto and \nMarc Zissman, instituted a \n pr\nocess for formulating a strategic direction and road map, \nin their roles as coleaders of the Cyber Security and Information Sciences Division at \nMIT Lincoln Laboratory. Some of the techniques described in this chapter are drawn \nfrom many years of practical experience successfully developing and deploying com-\nplex prototype systems. The formulated strategic road map served as a first step \n to\nward \nembarking on a prototype development and ultimately in its successful deployment.\nIn this chapter, we provide the reader a step-\n b\ny-\n step pr\nocedure to create an AI stra-\ntegic road map. The creation of a strategy is not a final destination, but a journey to \nget the \n whole AI team mar\nching in the same direction. A strategy is not a static deliv-\nerable; instead, it is a living blueprint that must be revisited and, if necessary, updated \nthroughout the year while the AI system is undergoing development leading to the \nfinal deployment.\nAndrew Ng, a faculty member at Stanford University and the CEO and \n founder of \nLanding.ai, outlined the fiv\ne-\n step playbook sho\nwn in \n table\u00a0\n9.1 during a fireside chat \nat the MIT T echnology Review conference on AI-\n focused E\nmT ech Digital [1].\nNg\u2019s five steps are very consistent with several of the topics discussed in part II of this \nbook. The need to execute \n pilot pr\noj\n ects to gain buy-in and momentum\u2014w\ne use \n pilot\n \nproj\n ects and pr\nototypes interchangeably\u2014is necessary to demonstrate initial AI capabili-\nties in the form of a minimum \n viable pr\noduct (MVP). Step 2, building an in-\n house AI\n \nteam, allows AI \n organizations to gr\now and preserve organic capabilities, since AI tech-\nnologies evolve very rapidly. Also, as discussed in \n earlier chapters, AI ex\ncellence requires \nteams to be multidisciplinary, so \n ther\ne is a need for continued training to broaden the AI \n Table\u00a09.1 AI transformation playbook\u2014 how to lead your com pany into the AI era\nP\nlaybook Steps\n1.\n E\nxecute \n pilot pr\noj\n ects to gain momentum.\n2.\n B\nuild an in-\n house AI team.\n3.\n P\nrovide broad AI training.\n4.\n D\nevelop an AI strategy.\n5.\n D\nevelop internal and external communications.\nSource: Ng (2021).\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2632, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "564ebacc-63b1-46fd-9ebd-6763df8bb770": {"__data__": {"id_": "564ebacc-63b1-46fd-9ebd-6763df8bb770", "embedding": null, "metadata": {"page_label": "3", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What is the AI Strategic Development Model (AISDM), and how has it been utilized in the context of developing strategic road maps for technical divisions?\n\nThis question focuses on the specific framework mentioned in the text and its application, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, strategic development model, technical divisions"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "79c4f86d-8d46-4e0e-89c2-00f8f8fc8f62", "node_type": "4", "metadata": {"page_label": "3", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "9343a49a431cd3586693bd8027a6e017070f17d1e1416c3a0998be616925b3a4", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.1: Introduction to Strategic Thinking 289 \nteam\u2019s levels of expertise. The fourth recommendation is to develop an AI strategy, which \nis the focus of this chapter. Fi\n nally\n, the last recommendation\u2014\n step 5\u2014is to dev\nelop \ninternal and external communications. We would augment that recommendation to \ninclude relationships as well. It is impor tant to communicate the AI v\nalue proposition \ninternally, to your team and other internal business units, and externally, to stakeholders. \nBut to be successful in the development and deployment of AI capabilities, an AI \n organization must also use its internal and external exper\ntise by cementing enduring \nrelationships.\nPart I of the book focused on the AI system architecture, representing the \u201cwhat\u201d that \nforms the end-\n to-\n end building blocks. P\nart II focuses primarily on the \u201chow\u201d of imple-\nmenting the AI system architecture. \n After the AI strategy discussion in this chapter\n, we \ndevote chapters\u00a010 and 11 to AI deployment, using techniques initially formulated \n under\n \nthe field of development, security, and operations (DevSecOps), and applied to the nascent \ndiscipline of machine learning operations (MLOps). Chapter\u00a012 delves more deeply into \nthe fostering of an innovative team environment, addressing the impor tant \ntopics of AI \nleadership and technical talent. Chapter\u00a013 provides tools and techniques to communi-\ncate technical topics clearly and focuses on communicating effectively, internally, and \nexternally to the AI \n organization\u2014\n a topic that is v\nery impor tant for technology-\n based\n \nbusinesses, their leadership, and their technical employees.\nIn section\u00a09.1, we begin by setting up the stage and defining the \n pr\nocess of strategic \nthinking. We then pre\n sent an AI strategic dev\nelopment model (AISDM) that, in addi-\ntion to being used in our class proj\n ects, has been used during the cr\neation of strategic \ndevelopment road maps for technical divisions. The remaining sections in this chapter \ndescribe in detail the key parts of the AISDM framework, employing a selective class \nproj\n ect example fr\nom one of our MIT classes. We conclude the chapter with the main \ntakeaways and a set of exercises.\n9.1 Intr oduction to Strategic Thinking\nIn this section, we explicate the importance of developing a strategic thinking compe-\ntency. Initially, this competency might appear relevant to only the C-\n suite and upper \nmanagement. H\nowever, strategic thinking, to work effectively, must include members \nof the AI team who are responsible for di\nff er ent aspects of AI pr\noducts and \n ser\nvices \nthroughout the AI system life cycle. A superior and well-\n defined strategic r\noad map is \nnot executable \n unless \n ther\ne is buy-in from the top management and the staff.\nLet us start by addressing a \n simple but po\nwer ful perspectiv\ne on strategic thinking. \nDavid Briggs, emeritus director of the MIT Lincoln Laboratory, stressed the importance \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 3028, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "345311f4-31a0-478e-9612-c867ab94ffae": {"__data__": {"id_": "345311f4-31a0-478e-9612-c867ab94ffae", "embedding": null, "metadata": {"page_label": "4", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key differences between strategic thinking and tactical competencies as described in the context of AI leadership and project management?\n\nThis question is tailored to the specific content of the excerpt, focusing on the distinctions made between strategic and tactical approaches in the context of AI leadership, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI leadership, strategic thinking, tactical competencies"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "614023f1-ba97-47eb-9c51-adfa84fcc05a", "node_type": "4", "metadata": {"page_label": "4", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "a4fd63c0949367b7c9d5f220c8146d064ca4b2345b10981d8e98b129f0183dd0", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "290 Chapter 9: AI Strategy and Road Map\nof technical personnel developing strategic thinking skills as they advance in their car eers. \nHis perspective, and what he referred to as the \u201cstrategic and tactical divide,\u201d is shown in \nfigure\u00a09.1. \n Ther\ne are two impor tant messages captur\ned in the graph \n her\ne:\n\u2022\n As the AI leadership and pr\noj\n ect man\n ag\n ers incr\nease in responsibilities, more and \nmore of their time must be spent on strategic thinking.\n\u2022\n I\nn contrast to tactical competencies, where the work is more defined and typi-\ncally coupled to the individual\u2019s education and training, strategic thinking is \nmore ambiguous and the tool set is \n limited.\nP\natrick McGovern, an American businessman who was the chairman and \n founder \nof the I\nnternational Data Group, built a multibillion-\n dollar corporation b\ny focusing \non a clear mission and vision while embracing emerging technologies. Glenn Rifkin, \nin his book \n F\nuture Forward: Leadership Lessons from Patrick McGovern [2], highlights \none of \n these lessons, ex\nemplified in the following quote from McGovern: \u201cIn a fast-\n \nchanging business, long-\n term vision plus shor\nt-\n term operational ex\ncellence \n will out\n-\nperform any other strategy.\u201d This lesson is also consistent with the impor tant message \nmentioned \n earlier: to plan the wor\nk and work the plan. Plan the work\u2014\n meaning \nformulating \na strategic plan\u2014\n should \nencompass multiple years, as shown in the hori-\nzons framework discussed in part I. The execution approach should be short-\n term and \nfocused on operational ex\ncellence.\nStrategic\n\u2022 More ambiguity\n\u2022 Tool set limited\nTactical\n\u2022 More defined\n\u2022 Coupled to education/training\nIncreasing responsibility level\n0%\n100%\nYour time\nFigure\u00a09.1 Strategic and tactical divide.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 1850, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "ccf58566-3723-4605-8f8b-374b32993198": {"__data__": {"id_": "ccf58566-3723-4605-8f8b-374b32993198", "embedding": null, "metadata": {"page_label": "5", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key considerations for an AI organization when engaging in strategic thinking to shape its future direction over different time horizons?\n\nThis question is tailored to the unique insights presented in the context regarding the strategic planning process for AI organizations, including the specific time horizons (near term, midterm, and far term) and the various management questions that need to be addressed.", "excerpt_keywords": "Keywords: strategic thinking, AI organization, management questions"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "04b82d29-1656-4bcb-9aa6-a65dec5ef342", "node_type": "4", "metadata": {"page_label": "5", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "295a8706995379c3d4a35dc79c96fdf210828d0e252c2deec7e627e7e3a2f54f", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.1: Introduction to Strategic Thinking 291 \nStrategic thinking puts a framework around determining the overall direction of an \nAI \n organization. M\nore specifically, strategic thinking helps answer critical manage-\nment questions, such as the following:\n\u2022\n What \nshould the AI organization \nlook like in the near term (horizon 1; 1\u20132\u00a0years), \nmidterm (horizon 2; 3\u20134\u00a0years), and far term (horizon 3;\n \u2265\n \n5\u00a0years)?\n\u2022\n Who benefits fr\nom strategic thinking and the formulation of a strategic plan?\n\u2022\n Who should w\ne be hiring (i.e., talent)?\n\u2022\n What should w\ne be learning?\n\u2022\n What technologies do w\ne need to enter or exit?\n\u2022\n What contracts and channels should w\ne grow or shrink?\n\u2022\n Who \n will be willing and able to pay for it?\n\u2022\n What pr\no\n cesses ar\ne or are not needed?\n\u2022\n H\now federated should the portfolio be with re\n spect to internal and external \npar\ntners?\n\u2022\n What should be the mix of dir\nect and contracted employees?\nIt is also impor tant to emphasiz\ne that the \n pr\nocess of strategic thinking and the stra-\ntegic plan that results from this \n pr\nocess help in the following ways:\nIndividual leaders:\n\u27a3 The planning pr ocess causes y ou to stop and think about what\u2019s impor tant.\n\u27a3 The plan itself helps guide decision making going for ward.\n\u25aa\n I\nt is a \u201ccompass\u201d of sorts that can help remind you what your desired desti-\nnation is when the seas get rough.\nAI staff:\n\u27a3 The planning pr ocess is an opportunity to promote and get buy-in.\n\u27a3 The plan can be used as a per formance goal guide in the evaluation of AI staff.\nUpper management:\n\u27a3 The plan explains where your AI team is going in the development and deploy-\nment of AI products and \n ser\nvices.\n\u27a3 The plan can be used to justify decisions and sho w pro gr ess.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 1824, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "65cc5a45-3e4a-4de6-b3d0-ae731197beb5": {"__data__": {"id_": "65cc5a45-3e4a-4de6-b3d0-ae731197beb5", "embedding": null, "metadata": {"page_label": "6", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the four key components of strategic thinking as adapted from Nina Bowman's approach in the context of AI strategy development?\n\nThis question is tailored to extract specific information from the text regarding the components of strategic thinking, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, strategic thinking, organizational communication"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "2e473dc6-d5d4-45fc-8477-86d6803b27ee", "node_type": "4", "metadata": {"page_label": "6", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "06962d50f1b3efc86598dd30528308f081bc44dad2d4e3ffa3098a703c7c5dcb", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "292 Chapter 9: AI Strategy and Road Map\n There are also impor tant questions that must be asked at the star t of the pr ocess. \nThe Harvard Business Review (HBR) guide Thinking Strategically pre\n sents a set of ques\n-\ntions to inspire strategic thinking, with dozens of prompts to get started [3]. As \npointed out in appendix A of the HBR guide, answers to \n these questions driv\ne clarity, \nalignment, and strategic insight.\nNina Bowman, in her HBR article \u201c4 Ways to Improve Your Strategic Thinking \nSkills\u201d [4], pre\n sents a clear appr\noach to reduce the ambiguity that it is often in the \nstrategic thinking pr\nocess. We have adapted her four-\n way appr\noach with some modi-\nfications to maintain the same terminology that we have used in this chapter. Fig-\nure\u00a09.2 illustrates the four areas of focus during the \n pr\nocess of strategic thinking. First, \nKnow emphasizes the need to observe and seek trends to identify both internal and \nexternal \n factors likely to affect y\nour strategic direction.\nAs pointed out \n earlier\n, a strategic planning \n pr\nocess should begin by asking key ques-\ntions to Broaden the AI value proposition understanding and how it affects the business. \nAnswers to key and tough questions must be addressed from di\nff er ent \npoints of view. \nThird, strategic planners must Communicate the strategic plan at \n ev\nery level within the \nAI \n organization that is r\nesponsible for delivering value. Communicating effectively (see \nchapter\u00a0 13) shapes a common understanding. Fi\n nally\n, the fourth component of the \napproach is to Act by identifying goals and actions that should be debated. The strategic \nviews should be challenged to ascertain that the strategic direction is consistent with the \noriginally defined objectives while formulating answers to key questions.\nStrategic\nthinking\nFormulate alternatives\nLook at information from \ndifferent points of view.\nObserve both internal \nand external factors\nMake it a routine exercise \nto explore and synthesize \nthe internal/external \nfactors.\n1. Know: observe and \nseek trends\n2. Broaden: ask the \ntough questions\nChange your mindset\nStrategic thinking must \nhappen at every level in \nthe organization.\n3. Communicate: shape \ncommon understanding\nFocus on issues\nInvite others to challenge \nyour strategic views and \ndo not take them personal.\n4. Act: embrace con\ufb02ict \nto debate key challenges\nFigure\u00a09.2 Four ways to impr ove your strategic thinking skills. Adapted from [4].\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2544, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "4c576e21-6c89-4782-ba28-9111e3f18659": {"__data__": {"id_": "4c576e21-6c89-4782-ba28-9111e3f18659", "embedding": null, "metadata": {"page_label": "7", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the primary barriers to AI adoption identified in the 2018 McKinsey & Company survey, and how does the AISDM framework address these barriers?\n\nThis question is tailored to extract specific insights from the context regarding the barriers to AI adoption and the role of the AISDM framework in overcoming those challenges, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI adoption, AISDM framework, strategic planning"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "aab232ac-02da-44b7-96dc-e0040af40c18", "node_type": "4", "metadata": {"page_label": "7", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "5162c1dc3434fe64539df55975a4f85152acb2815cba2a39bd1ae63ae08bc767", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.1: Introduction to Strategic Thinking 293 \nA 2018 survey by McKinsey & Com pany , performed across over 2,000 participants \nrepresenting a range of regions, industries, and com\n pany siz\nes, identified a lack of clear \nAI strategy as the most frequently cited barrier to AI adoption [5]. This barrier was iden-\ntified by 43\u00a0 per\ncent of the respondents. The next-\n largest barrier\n, identified by 42\u00a0 per\ncent \nof the respondents, was the lack of personnel with appropriate skills to be effective at \ntheir assigned AI duties.\nIn the next section, we introduce the reader to the AISDM. We have used the AISDM \nframework for our own real-\n world applications. \nWe have also taught, as part of our MIT \nclasses, the AISDM framework as a step-\n b\ny-\n step guide for cr\neating a strategic plan used \nin the team class proj\n ects. The use cases discussed in chapters\u00a0\n14\u201318, illustrate the appli-\ncation of the AISDM framework to a broad range of AI applications.\nThe AISDM approach helps in addressing the barriers identified in the McKinsey & \nCom\n pany r\neport. The output of the AISDM framework is a strategic development road \nmap that formulates the direction for the successful development and deployment of AI \ncapabilities.\nBefore we describe in detail the AISDM framework, readers interested in additional \ntools to assess emerging trends that could have an impact on business opportunities are \nreferred to Christensen et\u00a0al. [6], who have devised a theory to understand why compa-\nnies have difficulty responding to disruptive innovations. Their resource, \n pr\nocess, value \n(RPV) theory is very useful and well aligned, as a tool, with the first strategic thinking \nstep, Know: observe and seek trends. The RPV theory incorporates resources (what an \n organization has in \nthe form of people, \ntechnology, and equipment); pro\n cesses \n(how an \n organization does its wor\nk); and values (what the \n organization wants to achiev\ne). Again, \nthe strategic road map is the blueprint that codifies the near-\n term, midterm, and long- \nterm strategic dir\nections of an AI \n organization informed b\ny its resources, pro\n cesses, and\n \nvalues.\nAnother useful resource, on how other companies approach their long-\n term assess\n-\nment of opportunities, is by Schwartz, who describes techniques for scenario planning in \nhis book The Art of the Long View [7]. Scenario planning is not about trying to predict the \n futur\ne. Instead, it is a technique to help in formulating alternatives\u2014\n B\nroaden the AI value \nproposition options\u2014as discussed in the four-\n way appr\noach illustrated in figure\u00a09.2.\nThe ability to communicate effectively is so impor tant, fr\nom technical staff to upper \nmanagement, that we dedicate chapter\u00a013 to this topic. As shown in figure\u00a09.2, the \nthird step in improving strategic thinking skills is to Communicate at \n ev\nery level in the \n organization to shape a common understanding.\nI\nn the subsequent sections, we describe each of the components that form the \nAISDM framework.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 3087, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "ccec2452-3185-4001-b771-45e1feaa7395": {"__data__": {"id_": "ccec2452-3185-4001-b771-45e1feaa7395", "embedding": null, "metadata": {"page_label": "8", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components of a strategic development road map as discussed in the context of AI strategy, and how do they relate to the mission and vision statements of an organization?\n\nThis question is tailored to the unique insights provided in the text regarding the importance of mission and vision statements in the context of AI strategic planning, as well as the multidisciplinary approach required for effective strategy development.", "excerpt_keywords": "Keywords: AI strategy, mission statement, strategic development"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "ccbb90b4-4902-4cc6-8e31-4a84cb9fb8b9", "node_type": "4", "metadata": {"page_label": "8", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "38dc4f4fcdeb1769652108988cde307610b829a283fbaea83cde47504e61b8ec", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "294 Chapter 9: AI Strategy and Road Map\n9.2 AI Strategic Development Model\nOne of the most successful visionaries of the modern information age was Steve Jobs, \nwho, \n under his leadership\n, transformed Apple multiple times. One of his famous quotes \nwell reflects his emphasis incorporated into Apple\u2019s strategic planning: \u201cI\u2019m as proud of \nwhat we \n don\n\u2019t do as I am of what we do.\u201d A strategic development road map helps in \ndefining the business direction, priorities, and areas to emphasize and deemphasize.\nThe earlier \ndiscussion, in part I of the book, centered on the AI system architecture \nshown in figure\u00a0 1.3. The development of a strategy that is executable requires the \ncontributions of diverse participants with AI expertise across the full end-\n to-\n end ar\nchi-\ntecture. AI demands a multidisciplinary approach with responsibility for each of the \nsubcomponents in the AI architecture. Stadler et\u00a0al. discuss the need to \u201copen up your \nstrategy\u201d [8]. As the authors pointed out, making a com\n pany strategy \n behind closed \ndoors is a pr\nescription for failure. Our experience at MIT Lincoln Laboratory is to \ninclude all levels, with lead responsibilities within a technical group, to help in defin-\ning a group\u2019s strategy. The group\u2019s strategy then feeds into the overall division-\n lev\nel \nstrategy, consistent with the long-\n term dir\nection of the \n organization.\nM\nichael T ushman led the Program for Leadership Development (PLD) within the \nHarvard Business School for many years [9]. The depiction shown in figure\u00a09.3 is adapted \nfrom Harvard\u2019s PLD discussion of strategic planning. This high-\n lev\nel description incor-\nporates \n simple but meaning\nful explanations of some of the components that form part of \na strategic road map. Many \n organizations str\nug\n gle with the mission and vision statements.\n \nAs shown in figure\u00a09.3, the mission should be a short statement on why the \n organization,\n \nthe business unit, a group, or other collective exists. Sinek, in his book titled Start with \nWhy, discusses the importance of clearly defining the why [10]\u2014it must be an inspira-\ntional statement to take action. The vision should also be a short statement, focusing on \nwhat the \n organization wants to be and complementing the mission statement.\nLet us pr\ne\n sent a r\neal-\n life example that in practice describes v\nery inspirational mis-\nsion and vision statements. Daniela Rus, director of the MIT CSAIL Laboratory, \ndescribes its mission and vision as follows [11]:\n\u2022\n M\nission: MIT CSAIL pioneers research in computing that improves how \n people \nwor\nk, play, and learn.\n\u2022\n V\nision: A world where computing empowers all \n people and enhances all \n human \nexperiences.\nThe mission statement has a clear focus on action within the laborator\ny. MIT CSAIL \u2019s \nmission is also very well aligned with the overall mission of the Mas\n sa\n chu\n setts I\nnstitute of \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2971, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "608ba398-f93f-4d0a-ac43-87d26d0630f3": {"__data__": {"id_": "608ba398-f93f-4d0a-ac43-87d26d0630f3", "embedding": null, "metadata": {"page_label": "9", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components of the AI Strategic Development Model as outlined in the document, and how do they relate to the internal and external environments of an organization?\n\nThis question is tailored to the specific details mentioned in the context regarding the strategic development model, including the internal and external factors that influence an AI strategy, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI Strategy, Strategic Development Model, SWOT Analysis"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "193ffe09-4eff-4836-abfa-f6060c9c59f4", "node_type": "4", "metadata": {"page_label": "9", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "0b72f185a0dead602a0aa2e6885596e5c0483812bc64e66183c13f70e1ea1b8c", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.2: AI Strategic Development Model 295 \nT echnology (MIT), which is to advance knowledge and educate students in science, tech-\nnology, and other areas of scholarship that \n will best ser\nve the nation and the world in the \ntwenty-\n first \n centur\ny. MIT CSAIL \u2019s vision statement complements its mission statement, \ndescribing a purpose for the laboratory\u2019s research: namely, to have a worldwide impact.\nOther \n factors influencing a strategic r\noad map are the internal and external environ-\nments. We discuss the organization\n\u2019s strengths and weaknesses (internal environment), \nand the opportunities and threats (external environment) \n later in this section, when w\ne \ndiscuss the strengths, weaknesses, opportunities, and threats (SWOT) analy\n sis. F\nor now, \nit is sufficient to point out that successful \n organizations must formulate an AI strategy\n \nthat is executable.\nMission\nWhy\nwe exist\nWhat\nwe want\nto be\nVision\nOur\ngame plan\n\u2013 goalsStrategy Internal\nenvironment\nWhat\nspecific\nthings we\nwill do \u2013\nactions\nImplementation\ninitiatives\nMarket needs,\nopportunities\nbudgets,\ntechnologies,\ncompetitors\nStrengts,\nweaknesses,\nteaming,\ninfrastructure,\nculture\nExternal\nenvironment\nBasis for our Strategic\nDevelopment Model\nPerformance\nmeasurement\nHow do we\nmeasure\nsuccess?\nFigure\u00a09.3 High- level description of a strategic plan [9].\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 1419, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "af579566-4b67-4447-b082-24467feebe39": {"__data__": {"id_": "af579566-4b67-4447-b082-24467feebe39", "embedding": null, "metadata": {"page_label": "10", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components of the AISDM framework that organizations should consider when formulating an AI strategic road map?\n\nThis question is tailored to the specific details discussed in the context regarding the AISDM framework and its application in developing an AI strategic road map, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, AISDM framework, strategic road map"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "33a245f8-e1a8-4187-a74a-68e7ea6240de", "node_type": "4", "metadata": {"page_label": "10", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "2b073b18a21954ca4dd4eca9d89abb15e6731957ee8c52edbc30a3052eaff5b6", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "296 Chapter 9: AI Strategy and Road Map\n Organizations must focus on the pre sent or near term (r elative to execution), midterm, \nand the \n futur\ne (long term), as we \n will addr\ness during the envisioned \n futur\ne discussion in \nsection\u00a09.3. Smith et\u00a0al. referred to this duality (i.e., focusing on the near term through \nthe long term) as not an either/or choice but instead as \u201cBoth/and Leadership\u201d [12]. \nSimilarly, O\u2019Reilly and T ushman called for an \u201cAmbidextrous \n O\nrganization\u201d [13], where \n ther\ne is a need for a balance of the paradox between the exploitation of existing capabili-\nties (near term) and looking forward (long term) by exploring opportunities (i.e., staying \ncompetitive through constant innovation) [14]. They emphasized the importance of a \nvision, the associated strategy, and formulating clear objectives as the bedrocks for manag-\ning innovation and change. These \nlessons are crucial to AI organizations \nsince the techno-\nlogical under\n pinnings ev\nolve very rapidly. We elaborate further on \n these topics as par\nt of \nour upcoming discussion of the AISDM framework, starting with the \n organization\n\u2019s mis-\nsion and vision, core values, and strategic direction.\nWe integrate the last two ele\n ments of the high-\n lev\nel strategic plan shown in figure 9.3\u2014 \n \nimplementation initiativ\nes (i.e., goals and actions) and \n per\nformance \n measur\nement (i.e., \n per\nformance metrics)\u2014as part of the strategic road map deliverables.\nThe AISDM, shown in figure\u00a09.4, building on the description of the high-\n lev\nel stra-\ntegic plan shown in figure\u00a09.3, provides more context and details relevant to formulating \nan AI strategic road map. The AISDM framework is applicable to formulating an AI \nstrategic road map at the \n organization lev\nel, at the business-\n unit lev\nel, at the group-\n unit\n \nlevel, and at the AI-\n pr\noject level. However, since we want to cement many of \n these con\n-\ncepts by highlighting representative examples, we use MIT team class proj\n ects; which\n \n w\nere focused on formulating a strategic road map for a proposed AI \n organization pr\nod-\nuct or \n ser\nvice. Additional use cases are discussed in chapters\u00a014\u201318, and the reader is \nencouraged to follow up with \n these use cases to gain fur\nther understanding on how to \nuse the framework.\nIt is useful to start by formulating the long-\n term mission and the vision for the AI \npr\noduct or \n ser\nvice\u2014\n after trav\nersing the AISDM framework, culminating with a stra-\ntegic blueprint, we can then return and refine the mission and vision statements. The \nmission and vision statements, plus the envisioned futur\ne, are discussed in more detail \nin section\u00a09.3.\nOnce the envisioned \n futur\ne is formulated, we can then revisit the \n organization cor\ne \nvalues feeding into the strategic direction for an AI product or \n ser\nvice, based on the \n organization\n\u2019s competencies, capabilities desired, and existing and \n futur\ne system appli-\ncations. We discuss \n these components of the AISDM frame\nwork in section\u00a09.4.\nThe next step in the building of the strategic road map is to identify the AI value \nproposition (shown at the center of figure\u00a09.4). The AI value proposition is formulated \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 3278, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "df6bf61e-c47c-44d3-a18d-4ee6691ece65": {"__data__": {"id_": "df6bf61e-c47c-44d3-a18d-4ee6691ece65", "embedding": null, "metadata": {"page_label": "11", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context regarding the AI Strategic Development Model (AISDM) and its components, here is a question that can be specifically answered by this information:\n\n**Question:** What are the key components and considerations outlined in the AI Strategic Development Model (AISDM) for effectively implementing AI within an organization?\n\nThis question is tailored to extract specific insights from the context, focusing on the elements that contribute to the strategic development of AI in an organization, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI Strategic Development Model, implementation, governance"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "6d09780c-0cb9-43e4-b299-a6a583777ea2", "node_type": "4", "metadata": {"page_label": "11", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "48980b09145802eb8b4ceadb7c5b2b494fef62cb3c76272193df5e78d5eca97c", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.2: AI Strategic Development Model 297 \nLong term\nmission and\nvision\nOrganization\ncore values\nStrategic\ndirection\nEnvisioned\nfuture\nAl global trends\nLay-of-the-land\nCustomer priorites\nand vision\nAl strategic\nroadmap\n(blueprint)\nCulture\nOrganization\nPeople\nAl\nimplementation\nopportunities\nValue\nproposition\n(Al system\narchitecture)\nGovernance\nand\nresponsible Al\nTechnologies\nInfrastructure\nOrganization purpose\nLong term vs short term gains\nCustomer\nwith influence\nCustomer\nwith funding\nLeadership\nTalent\n\u2022\n\u2022\n\u2022\n\u2022\n\u2022\n\u2022\n\u2022\n\u2022\n\u2022\nCritical gaps\nBusiness\nneeds SWOT Risk\nmanagement\nGoals and\nactions\nPrototypes:\nMLOps\ndemo\nPerformance\nmetrics\nCapabilities\nvs. business\nneeds\nFigure\u00a09.4 The AISDM.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 765, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "9f373b1f-ba22-4fa5-a408-db363019d2c2": {"__data__": {"id_": "9f373b1f-ba22-4fa5-a408-db363019d2c2", "embedding": null, "metadata": {"page_label": "12", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be answered specifically from the information given:\n\n**Question:** What are the seven components of the AI strategic road map as outlined in the AISDM framework? \n\nThis question is unlikely to be answered in other contexts without access to the specific details of the AISDM framework discussed in this document.", "excerpt_keywords": "Keywords: AI strategy, AISDM framework, strategic road map"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "5126a445-cbb5-4345-a0c4-2d0e0b5b275f", "node_type": "4", "metadata": {"page_label": "12", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "ab2bca4c09c806adfc08d119b5d7e9a323184c2ec3ec65e86e46041e753e1ab2", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "298 Chapter 9: AI Strategy and Road Map\nbased on the AI system architecture discussed in part I. The value proposition is informed \nby four key components, which are discussed in detail in section\u00a09.5:\n\u2022\n AI implementation oppor\ntunities\n\u2022\n P\neople (i.e., leadership and talent)\n\u2022 \n O\nrganization AI governance, responsible AI (RAI), technologies, and infrastructure\n\u2022\n \nCulture\nThe ultimate deliverable, from the AISDM framework, is the AI strategic road map \n(i.e., a strategic blueprint). The AI value proposition must be aligned with the value \ncapture seen through the lens of the stakeholders. The AI strategic road map consists of \nseven components:\n\u2022\n The stakeholder\n\u2019s business needs\n\u2022\n SW\nOT analy\n \nsis\n\u2022\n Risk management (including cost)\n\u2022\n G\noals and actions\n\u2022\n Capabilities pr\novided versus business needs\n\u2022\n P\nerformance metrics (i.e., quantitative and qualitative assessment of pro\n gr\ness)\n\u2022\n P\nrototypes (i.e., demonstrating an initial MVP or \n ser\nvice through the implemen-\ntation of an MLOps demo)\nSince many trade-\n offs must be made in the formulation of a strategy that is ex\necutable, \nan impor tant b\ny-\n pr\noduct of executing \n these sev\nen components is enumerating the critical \ngaps found. Such gaps can result from any or several of the components. For example, the \nSWOT analy\n sis can inform on limitations on what can or cannot be implemented due to\n \ninternal weaknesses or external threats. Another example, informing identified critical \ngaps, can result from prototyping an initial MVP through a prototyping demo. The criti-\ncal gaps can then feed back to the envisioned \n futur\ne (i.e., the three horizons discussed in \n earlier chapters). A\nt this point, \n ther\ne is also an opportunity to refine the mission and \nvision statements.\nIt is impor tant to str\ness that the development of a strategic road map is not an end \npoint. It is a journey with a need to revisit, engage in dialogue, and debate the planned \nwork and its execution (i.e., work the plan) on a regular basis (e.g., \n ev\nery three months, \ndepending on the complexity of the AI system).\nIn the next sections, we address each of the components of the AISDM framework \nin greater detail.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2273, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "f8d25ac1-9c04-4352-9258-8fcb9cddcd8f": {"__data__": {"id_": "f8d25ac1-9c04-4352-9258-8fcb9cddcd8f", "embedding": null, "metadata": {"page_label": "13", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "What specific mission and vision statements did the MIT team formulate for their AI early detection and intervention product using the Misty robot?", "excerpt_keywords": "Keywords: AI, robotics, healthcare"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "1cc3a3cb-87b4-41d5-81a6-8ffa0f670e5a", "node_type": "4", "metadata": {"page_label": "13", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "a83886339ef9c35d3c1a85e6b9fed365ea404f9ae6e06e2351da3e0f9c071f82", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.3: Mission/Vision and Envisioned Futur e 299 \n9.3 Mission/Vision and Envisioned Futur e\nIn the previous section, we introduced the AISDM framework. In this section, we \npre\n sent \nmore details on the mission and vision statements and the envisioned \n futur\ne. \nThe mission and vision statements should be short, capturing the broad purpose of an \nAI product or \n ser\nvice. Again, \n these statements should be inspirational and able to \ndraw in pr\nospective stakeholders.\nLet us look at an example. During our MIT gradu\n ate engineering class, w\ne invited \nthe head of the Misty Robotics com\n pany\n, Tim Enwall, to pre\n sent a challenge pr\nob\n lem to\n \nthe students [15]. The posed challenge required that the students, working as a team, \ndevelop a strategic plan following the AISDM framework. The students \n w\nere given \naccess to a Misty robot demo unit (https://\n www .\n mistyr\nobotics\n .\n com\n /\n ). The team concep\n-\ntualized an AI product using the Misty robot, where the robot would serve as an el\n derly\n \nperson\u2019s companion, with the task of detecting the onset of a stroke and proceeding with \nan intervention. The MIT team consisted of gradu\n ate students H\nannah Varner, Jeg \nSithamparathas, Nicolas Zhang, and Zubin Wadia. In chapter\u00a014, we describe another \napplication, formulated by a di\nff er ent MIT student team, for the M\nisty companion \nrobot to help el\n derly \n people suffering fr\nom Alzheimer\u2019s disease.\nStroke is a cardiovascular disease responsible for about 6.7 million deaths worldwide, \nsecond only to coronary heart disease in terms of the number of deaths annually [16]. \n B\necause of its severity, stroke is the leading cause of disability in the US, with a very low \npercentage of stroke patients ever recovering completely (about 10\u00a0 per\ncent). Early stroke \ndetection can have a significant reduction on the afflicted damage caused by a stroke. \n Ther\ne are early signs of a likely onset of a stroke, classed \n under the acr\nonym BEFAST \n(which stands for \u201cBalance, Eyes, Face, Arms, Speech, and Time\u201d) [17]. This set of early \nindicators and warnings are very well matched to the capabilities of a personal robot like \nMisty, when supplied with a range of sensors such as cameras, microphone, and natural- \nlanguage pr\no\n cessing (NLP), and equipped with an AI capability\n.\nThe MIT team formulated a mission and vision for its AI early detection and inter-\nvention product, as follows:\nMission (Misty robot; the \u201cwhy\u201d): T o build a programmable robotics platform and \nmarketplace that accelerates societal pro\n gr\ness.\n\u2022\n P\nrogrammable: Application programming interfaces (APIs) and software \ndevelopment kits \n will use the M\nisty sensor suite fully, delivering high acces-\nsibility and productivity to science, technology, engineering, the arts, and \nmath (STEAM) prac\n \nti\n \ntion\n \ners.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2910, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "bbdf2197-edd8-4296-bda8-d37bcbe38303": {"__data__": {"id_": "bbdf2197-edd8-4296-bda8-d37bcbe38303", "embedding": null, "metadata": {"page_label": "14", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**What are the three horizons formulated by the MIT Misty robot team for their AI strategy, and what are the key focuses of each horizon?** \n\nThis question targets the specific strategic planning outlined in the text, which details the near-term, midterm, and far-term goals for the Misty robot, and is unlikely to be answered in other contexts without similar detailed insights into the AI strategy framework.", "excerpt_keywords": "Keywords: AI strategy, Misty robot, horizons framework"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "fd1c5d02-4fb8-42c9-b248-4548cd785bec", "node_type": "4", "metadata": {"page_label": "14", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "ec0f0ad69e36f676291d2e80ce5590237b9df8b425d4191a347f5640d5fa81c4", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "300 Chapter 9: AI Strategy and Road Map\n\u2022 M arketplace: Misty skills and labeled data sets for a variety of use cases. \nBoth of \n these assets can be monetiz\ned with network effects: More skills\n +\n \ndata \nlead to faster learning, faster iteration, and better solutions, plus more value \ndelivered to society.\nVision (Misty robot; the \u201cwant to be\u201d): T o be the world\u2019s most accessible and useful \nrobotics platform for hobbyists, educators, and professionals.\nThe Misty robotics mission statement is short but inspirational, and it captures its \npurpose. The additional supporting text (i.e., programmable and marketplace) only \nserves to clarify the context. The vision is a clear description of what the Misty robot\u2019s \nvalue-\n add and usefulness ar\ne for developers and educators.\nAs illustrated in figure\u00a09.4, the envisioned \n futur\ne is another impor tant par\nt of the \nAISDM framework. It helps crystalize the near-\n term, \nmidterm, and far-\n term \npros-\npects via the horizon structure discussed in part I. In the context of AI \n futur\ne direc-\ntions, it is formulated and informed by the following:\n\u2022\n AI global tr\nends: \n These tr\nends can be synthesized based on latest study reports, \nsurveys, and global projections [18\u201322].\n\u2022 Lay of the land: This input informs content for the horiz\nons but focused on the \nspecific AI product or ser\nvice. H\nere, we must analyze the competition, the market \nsegmentation, channels, pricing, and other ele\n ments. M\nichael Porter, a renowned \nscholar on the proper way to formulate a strategy, emphasizes that a com\n pany can\n \noutperform rivals if it can identify a com\n pany differ\nentiator that can be preserved \n[23]. Another useful reference, on how to identify a unique com\n pany differ\nentiator \nin a competitive market, is by Kim and Mauborgne [24].\n\u2022 C\nustomer priorities and vision: It is not uncommon to have \n either existing or poten\n-\ntial customers ask for help in formulating their own strategic road map. This pre\n-\nsents an oppor\ntunity for you to align your envisioned \n futur\ne with the needs of your \ncustomers. As we have done in other parts of the book, we use the term \u201cstakehold-\ners\u201d to mean customers or users (i.e., \n those \n people or \n organizations with the ability\n \nto influence or fund the development of AI capabilities) interchangeably.\n These inputs giv\ne the AI team tangible knowledge that it can use to proceed with \ndefining the com\n pany\n\u2019s envisioned \n futur\ne for an AI product or \n ser\nvice.\nReturning to our MIT Misty robot team, it formulated the three horizons illus-\ntrated in figure\u00a09.5.\nHorizon 1 (1\u20132\u00a0years) focuses on building the infrastructure and Misty skills employ-\ning existing ML tools. Horizon 2 (years 3\u20134) would incorporate multiple Misty robots \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2835, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "e751436a-c8bf-44d5-8fc5-cbcd7b143066": {"__data__": {"id_": "e751436a-c8bf-44d5-8fc5-cbcd7b143066", "embedding": null, "metadata": {"page_label": "15", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**Question:** How can the integration of machine learning and the Internet of Things (IoT) in robotic systems contribute to the early detection and intervention of strokes in elderly individuals?\n\nThis question is tailored to the specific example and insights shared in the text, particularly regarding the use of robots and machine learning algorithms to monitor and respond to potential health crises in real-time.", "excerpt_keywords": "Keywords: machine learning, Internet of Things, stroke detection"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "ab9de120-8a00-4ad8-84d2-eea0de5e7a5f", "node_type": "4", "metadata": {"page_label": "15", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "1eb3b55cc0ccef5bc8bbf1f48f4103e9b0cfad0c38e8a5f1641c307543a814b1", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.3: Mission/Vision and Envisioned Futur e 301 \ncollaborating in homes or businesses. For example, machine learning (ML) algorithms \nlearn from patterns seen in other stroke patients as robots share information and use an \nInternet of Things (I\noT) ecosystem. Horizon 3 (5+ years) integrates context in the robot \ndecision support system. An example of context might be observing that an el\n derly per\n-\nson with the propensity to have a stroke is not \n going to bed at a normal time and appears\n \nto unable to speak (one of the BEFAST indicators). The robot can then respond by call-\ning a nearby \n family member or neighbor\n. This example is drawn from a \n family member\n \nof one of the authors (David Martinez). A close relative was nonresponsive, sitting on a \ncouch \n until a r\nelative found her the next day. The person had suffered a massive stroke \nthat could have been prevented if ther\ne was an immediate action taken; like calling a \nnearby relative and responding in a more timely manner to minimize the stroke \nseverity.\nThe envisioned \n futur\ne helps in clarifying milestones and showing pro\n gr\ness in the \ndevelopment of AI capabilities. It is also very well aligned with executing \n pilot pr\noj\n ects \nto gain momentum, as outlined in \n table\u00a09.1.\nI\nn the next section, we formulate a strategic direction by incorporating the mission, \nvision, and envisioned \n futur\ne, all while staying consistent with an \n organization\n\u2019s core \nvalues.\nContent\n1\u20132 years\n3\u20134 years\nCollaboration\nContext\nMore sophisticated\nMisty bots available\nfor integration\nSituational awareness\nfrom a team of Misty\n\u201cdata sources\u201d\nPlatform proactively\nresponds to educational /\nsafety needs of users\nMulti-Misty systems in\nhomes and businesses\nPartner with wider loT\necosystem\n5+ years\n\u2022\n\u2022\n\u2022\nBuild \u201cskill\u201dand data\nlibrary\nBecome the developer\u2019s\nbest friend\nLeverage pre-existing\nML algorithms\n\u2022\n\u2022\n\u2022\n\u2022\n\u2022\nFigure\u00a09.5 Envisioned futur e (across three horizons) for the Misty robot applied to early \ndetection and intervention of stroke.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2105, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "3d1a78f8-943a-4255-947f-d0298234b069": {"__data__": {"id_": "3d1a78f8-943a-4255-947f-d0298234b069", "embedding": null, "metadata": {"page_label": "16", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the core values that should guide an organization in the development of AI products or services, according to the authors of the document?\n\nThis question is unlikely to be answered elsewhere as it specifically references the authors' perspective on core values in the context of AI strategy and development, which is detailed in the provided text.", "excerpt_keywords": "Keywords: AI strategy, core values, innovation"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "2370b6af-798e-41a4-872b-f0ee9c77e626", "node_type": "4", "metadata": {"page_label": "16", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "9b851da41fabf817509443bb30f27ed24f1af28c28d035b87cb0e0e494c2d727", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "302 Chapter 9: AI Strategy and Road Map\n9.4 Organization Cor e Values and Strategic Direction\nThe organization mission and vision statements, plus the envisioned futur e, are the start-\ning steps to help us formulate an \n organization\n\u2019s strategic direction for an AI product or \n ser\nvice. However, the strategic direction must align with the \n organization cor\ne values.\nIt is impor tant for us to hav\ne a common understanding of what \n organization cor\ne \nvalues are and are not. Lancioni articulates very clearly that \u201ccore values are the deeply \ningrained princi\n ples that guide all of the com\n pany\n\u2019s actions\u201d [25]. The core values are \nsacrosanct to the foundational bedrock of a well-\n functioning \n organization. The cultur\ne \nin the \n organization must br\neathe and live the com\n pany\n\u2019s core values. You can think of \ncore values as the guideposts and the culture (discussed further in section\u00a09.5) as the \ninstantiation of the core values in the organization\n\u2019s day-\n to-\n day \noperations (i.e., walk the \ntalk); and they must also be aligned with the mission and vision statements [26].\nEffective core values should resonate with all business units within an \n organization. \nA \nset of core values that have served the book authors well in the development and \nsuccessful demonstration of complex systems can be summarized as follows:\n\u2022\n I\nnnovation: Build advanced systems that exemplify innovative differentiators.\n\u2022\n T\nechnical excellence: In technology-\n based \n organizations, leaders and staff must \nmaintain the highest technical standar\nds.\n\u2022\n Learning-\n \nby-\n \ndoing: Mens et ma\n nus\n (mind and hand) is the MIT motto, and it \nmeans that it is not sufficient to conceptualize an AI capability. It must be dem-\nonstrated in real-\n world applications.\n\u2022 M\neritocracy: Reward successes based on well-\n defined expectations (see chapter\u00a0\n12 \nfor further details).\n\u2022\n M\nentoring: Strengthen staff effectiveness by establishing di\nff er ent mentorship \nappr\noaches across the \n organization. This cor\ne value implies reverse mentoring as \nwell, meaning a mentee providing feedback to a mentor.\n\u2022\n D\niversity, equity, and inclusion (DEI): Diversity of thought results from a well-\n \nestablished multidisciplinar\ny team with diverse backgrounds and experiences.\n\u2022\n I\nntegrity and openness: In the day-\n to-\n day wor\nk environment, we must celebrate \nand accept input from all ranks within the \n organization to do the right \n thing.\nI\nn addition to \n these br\noad core values, in the rapidly evolving field of AI, we must \noperate with purpose while adhering to a set of RAI princi\n ples. I\nn chapter\u00a08, we intro-\nduced and discussed the fairness, accountability, safety, transparency, ethics, privacy, and \nsecurity (FASTEPS) princi\n ples. \n These princi\n ples must form par\nt of the core values of an \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2902, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "b374dba3-4226-441c-9525-acbfbcb00c71": {"__data__": {"id_": "b374dba3-4226-441c-9525-acbfbcb00c71", "embedding": null, "metadata": {"page_label": "17", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the three parts of the strategic direction element in the AISDM framework as applied to AI products and services, and how do they relate to the competencies of an organization?\n\nThis question is tailored to the specific details mentioned in the context regarding the strategic direction of AI products and services, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, competencies, core capabilities"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "d1b39cf5-e57f-47c5-9754-0408ecfb2c38", "node_type": "4", "metadata": {"page_label": "17", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "b2b85d7aa495cc3d5dc5801c84769e6edaa260fb22133c93f1c358c72756155d", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.4: Organization Core Values and Strategic Direction 303 \nAI organization to behav e responsibly and be governed by moral values. Nonaka and \nTakeuchi highlighted this point by stressing that \u201cbusinesses must root strategy in moral \npurpose to thrive in a complex, rapidly changing world\u201d [27]. The strategic direction, for \nan AI product or \n ser\nvice, must incorporate, \n either implicitly or explic\n itly\n, the \n organization\n \ncore values.\nThe strategic direction ele\n ment of the AISDM frame\nwork shown in figure\u00a09.4 con-\nsists of three parts:\n\u2022\n Competencies:\n The \n organization\n\u2019s areas of existing or required expertise.\n\u2022\n Cor\ne capabilities: AI products or \n ser\nvices that are built from the \n organization\n\u2019s \ncompetencies.\n\u2022\n S\nystem applications: Areas to which the AI products or \n ser\nvices are applied. \n These \napplication ar\neas can be identified from a stakeholder\u2019s pull (i.e., business needs) \nor from an AI developer\u2019s innovation push.\nWe adopted these \nthree parts of the strategic direction from the seminal research of \nPrahalad and Hamel [28], which pointed out: \u201cThe corporation, like a tree, grows \nfrom its roots. Core products are nourished by competencies and engender business \nunits, whose fruit are end products.\u201d We \n adopted the same thr\nee-\n par\nt structure since \nit applies well to AI products and \n ser\nvices (meaning AI core capabilities).\nLet us now crystalize this structure, applied to the AI product formulated by the MIT \nMisty robot team in enabling the robot to detect and intervene at the onset of a stroke. \nFigure\u00a09.6 shows the three parts of the MIT team\u2019s strategic direction. The competencies \nrepresent the required technical skills needed to nourish the desired core capabilities. \n These capabilities in turn engender a set of system applications. I\nn par tic\n u\n lar\n, the AI \nsystem application of early stroke detection and intervention falls \n under the r\nesponsibili-\nties of the caretaker. The MIT team also formulated other AI system applications that are \nwell matched to the set of core competencies, enabled by a set of competencies.\nThe \n organization cor\ne values are implicit in this AI application example, since the AI \ndesigners, developers, and implementers must attend to such issues as patient privacy. \nThe ML algorithms must also comply with fairness across a broad range and diverse \npopulation, and the AI techniques must be safe and secure. Broadly speaking, this type \nof healthcare application must be deployed in a responsible way for the betterment of \nthe aging population (accelerating societal pro\n gr\ness and employing an accessible and \nuseful robot, as described in the mission and vision statements).\nNow that we have formulated what goes into a strategic direction, we expand on \nthe ele\n ments of the AI v\nalue proposition in the next section. The AI value proposition \nis a key component of the overall AISDM framework.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2998, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "c1c9c303-59fa-44c5-afa7-376c85fd6ac4": {"__data__": {"id_": "c1c9c303-59fa-44c5-afa7-376c85fd6ac4", "embedding": null, "metadata": {"page_label": "18", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**What are the four key subelements that substantiate the AI value proposition within the AISDM framework?** \n\nThis question is tailored to the specific details mentioned in the context regarding the AI value proposition and its components, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI value proposition, AISDM framework, strategic road map"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "7c9f18c2-b95b-477d-8542-326e7bd34e35", "node_type": "4", "metadata": {"page_label": "18", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "1162aeb2963621a5dca5bcefc0e7a04f8acf61631c97a48427bf484f57794830", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "304 Chapter 9: AI Strategy and Road Map\n9.5 AI V alue Proposition\nThe AI value proposition forms the cornerstone of the AISDM framework, gluing \ntogether preceding ele\n ments of the model (i.e., mission and vision statements, envisioned\n \n futur\ne, \n organization cor\ne values, and strategic direction) with the AI strategic road map. \nAs shown in figure\u00a09.4, the AI value proposition is substantiated and reinforced by four \nkey subelements:\n\u2022\n AI implementation oppor\ntunities\n\u2022\n \nPeople\n\u2022\n \nOrganization\n\u2022\n \nCulture\nThe reader \n will notice the explicit emphasis on the people-\n pr\nocess-\n technology triad \nthat \nwe have discussed throughout the earlier \nchapters of this book in the context of \nemphasizing the AI systems engineering approach across all aspects of an AI-\n driv\nen \nCore \ncapabilities\nSensor input \nresolution \noptimization\nCoordination/\nassistace \nanalysis\nAnomoly \nevent analysis\nIdentity\ndetection\nSystem \napplications Pet sitterHazard \ndetectionLearning aidChild sitter\nTeacher\u2019s \nassistant\nElderly \ncaretaker\nReceptionist/\ngreeter\nHome security \nsystem\nCompetencies\nHMM, \n3D-CNN\nOnboard \nprocessing\nMulti-modal\nanalyticsAutonomy\nCommunication\n(microphone/\nspeaker)\nSignal \nprocessing\nAnomoly\nunderstanding\nFacial \nrecognition\nFigure\u00a09.6 Strategic dir ection for the AI product using the Misty robot to enable the \ntimely detection and intervention of a stroke.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 1468, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "c232356d-a5ee-4a78-88a3-db2c8ece4e31": {"__data__": {"id_": "c232356d-a5ee-4a78-88a3-db2c8ece4e31", "embedding": null, "metadata": {"page_label": "19", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components that an organization must establish to effectively support the development and implementation of AI products or services, according to the AI value proposition framework?\n\nThis question is tailored to the specific details mentioned in the text regarding the necessary elements for an AI organization, such as governance structure, access to AI technologies, and the importance of culture, which may not be easily found in other sources.", "excerpt_keywords": "Keywords: AI governance, implementation opportunities, organizational culture"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "92658d95-aabb-46ae-b88e-1fa3a6ec610e", "node_type": "4", "metadata": {"page_label": "19", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "b65e4ca084140590b532895e16587936617dad47b51f8a37c663e7f22c7f7d75", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.5: AI Value Proposition 305 \n organization. The first subelement\u2014 AI implementation oppor tunities\u2014 r eflects the \nneed for financial support. An AI value proposition is not realistic if \n ther\ne is no source \nof financial backing from \n either internal (e.g., internal r\nesearch and development) or \nexternal support (e.g., investors, customers, or business clients). Typically, \n ther\ne are \nimplementation opportunities from customers with influence and/or customers with \nfunding resources. This distinction is made \n because, for example, a CEO of a corpora\n-\ntion (with influence) can direct the development of a proposed AI capability, but an \nexecutor like a chief technology officer must allocate the financial resources.\nNext in the subelements outlined \n her\ne is \n people; w\ne devote chapter\u00a012 to the topic \nof leadership and talent. Both are needed to successfully execute an AI strategic road \nmap. Furthermore, since AI requires a multidisciplinary team with broad expertise, \nleaders must be AI-\n awar\ne, with sufficient competence (with emphasis on systems-\n lev\nel \nknowledge) to lead teams. Conversely, an AI team with \n limited skills\u2014\n meaning lack \nof talent\u2014\n will str\nug\n gle in ex\necuting the AI value proposition.\nNext, an AI \n organization must suppor\nt the development and implementation of AI \nproducts or \n ser\nvices by establishing a governance structure, facilitating access to AI tech-\nnologies, and building the requisite infrastructure. The governance structure must ascer-\ntain compliance with the FASTEPS ele\n ments discussed in chapter\u00a0\n8. The AI governance, \nwithin the organization, \nshould be light enough to avoid atrophying innovation, but \nrobust enough to assert correction if the AI \n organization deviates fr\nom its moral compass, \nand to ensure operating within the guardrails complying with the FASTEPS princi\n ples.\nA\nccess to AI technologies is needed to enable the AI value proposition. The AI \ntechnologies are the innovative differentiators for an \n organization acr\noss the end-\n to-\n \nend AI system ar\nchitecture shown in figure\u00a01.3\u00a0in chapter\u00a01. We include this compo-\nnent within the organization \nsubelement because \nan AI \n organization must appr\noach \nthe design, development, and integration of their products and \n ser\nvices, emphasizing \n ev\nery ele\n ment of the system ar\nchitecture. However, we do not elaborate further in this \nchapter since this topic has been covered in detail in part I of the book.\nAn AI-\n based \n organization must also wor\nk with internal and external partners by \ncementing relationships and using an AI ecosystem, which strengthens the prowess of \nan AI team to successfully develop and deploy AI capabilities. We elaborate on this \ntopic in much greater detail in chapter\u00a010.\nAs we traverse the inputs that influence the AI value proposition, culture is a subele-\nment that makes or breaks the ability to effectively and efficiently execute the design, \ndevelopment, and implementation of AI capabilities. It is very well documented that \nwithout a supporting culture, a strategy \n will fail. E\ndgar Schein, an MIT professor emeri-\ntus and renowned scholar of \n organizational cultur\ne, clearly expressed what culture means \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 3303, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "e1e93e00-8bb5-433a-bdbc-01b9a964aabc": {"__data__": {"id_": "e1e93e00-8bb5-433a-bdbc-01b9a964aabc", "embedding": null, "metadata": {"page_label": "20", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** How does organizational culture influence the successful integration of AI capabilities within an organization, according to the insights from Ransbotham et al. and Westerman et al.?\n\nThis question is tailored to the unique insights presented in the text regarding the interplay between organizational culture and AI deployment, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: organizational culture, AI integration, digital transformation"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "e934aa81-45df-4247-90b8-cc99ad45a96d", "node_type": "4", "metadata": {"page_label": "20", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "47fbd08813323d1e97b0aa564120989363ce5e4a61a615cc4692379961b8b689", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "306 Chapter 9: AI Strategy and Road Map\nfor an organization in his seminal paper \u201cComing to a N ew Awareness of O rganizational \nCulture\u201d [29]. He defined \n organizational cultur\ne as \u201ca pattern of basic assumptions that \na given group has in\n v\nen\n ted, disco\nvered, or developed in learning to cope with its prob\n-\nlems of exter\nnal adaptation and internal integration, that has worked well enough to be \nconsidered valid and, therefore, to be taught to new members as the correct way to \nperceive, think, and feel in relation to \n those pr\nob\n lems.\n\u201d\nWe emphasized the phrase \u201cprob\n lems of external adaptation and internal integra\n-\ntion\u201d since developing AI capabilities depends on the successful internal integration, \nverification, and validation of the systems engineering Vee-\n model sho\nwn in figure\u00a02.1. \nThe Vee-\n model star\nts with understanding the stakeholders\u2019 specifications through sys-\ntem realization, while at the same time meeting the needs of external customers.\nVan Maanen explains succinctly what culture is: \u201cThe \n organizational cultur\ne is not as \nvis\n i\n ble as, for example, the \n organization\n\u2019s management structure, but it is the glue that \ndrives the operating environment of an \n organization\n\u201d [30]. As we pointed out \n earlier\n, \n organization \ncore values can be thought as the guideposts. The organizational \nculture is \nhow leaders and staff effect or espouse \n those cor\ne values in practice (i.e., walk the talk \n[31]). \n O\nrganizational culture encapsulates its purpose while always balancing long-\n term\n \nversus short-\n term gains.\nW\nesterman et\u00a0 al., in their article \u201cBuilding Digital-\n R\neady Culture in T raditional \n O\nrganizations\u201d [32], discussed areas to advance the state of traditional organizations \nas \nthey go through a digital transformation by adhering to the following steps:\n\u2022\n B\nuild an environment for rapidly experimenting, self-\n organizing, and driving \ndecisions with data.\n\u2022\n P\nreserve practices of acting with integrity and seeking stability by attracting and \nretaining talent, fostering customer loyalty, and ensuing stakeholder confidence.\n\u2022\n \nReorient the business direction, anticipating customers\u2019 needs, driving account-\nability for results, and setting rules that prevent abuses.\n These steps ar\ne excellent recommendations for building a digital-\n r\neady culture. \nThey provide guidelines very consistent with our emphasis in this chapter.\nIt is also very refreshing to see and to recognize that AI can also help in unifying the \nculture within an \n organization. Ransbotham et\u00a0\nal. performed a comprehensive global \nsurvey across over 2,000 man\n ag\n ers and inter\nviews with \n eighteen ex\necutives. A com-\nmon message that they heard was: \u201cBusiness culture affects AI deployments, and AI \ndeployments affect business culture.\u201d [33].\nAnother relevant survey was performed by Deloitte Global Boardroom to identify \nhow well aligned the technology was with the organization\n\u2019s strategy. T ouche et\u00a0 al. \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 3065, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "547b14d1-0832-4900-929c-c7b4bc9de986": {"__data__": {"id_": "547b14d1-0832-4900-929c-c7b4bc9de986", "embedding": null, "metadata": {"page_label": "21", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**Question:** What are the seven elements of an AI strategic road map as outlined in the AI Strategy and Road Map document?\n\nThis question is unlikely to be answered elsewhere as it specifically pertains to the detailed framework presented in the document, which includes unique elements related to AI strategy formulation.", "excerpt_keywords": "Keywords: AI strategy, road map, implementation blueprint"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "06ed9264-dbf3-4a25-afba-7f28871bce76", "node_type": "4", "metadata": {"page_label": "21", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "b8d092f0e0a4c4c23078e4572976cf74a8f38b72098aa7a99e2ecb60b934def7", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.6: AI Strategic Road Map: A Blueprint 307 \nsummarized the global survey performed across fifty- fiv e countries, consisting of more \nthan 500 board directors, C-\n suite ex\necutives, and subject \n matter exper\nts (SMEs) [34]. \nOne of their findings motivates the clear need for formulating an AI strategic plan as \ndescribed in this chapter. They found that about 50\u00a0 per\ncent of the respondents said that \nthey: \u201c didn\n\u2019t think\u2014or \n didn\n\u2019t know if\u2014\n technology aligned with the \n organization\n\u2019s strat-\negy.\u201d This finding was common among a large range of industries, including financial \n ser\nvices, manufacturing, healthcare, and retail.\nReturning to the Misty robot application from one of the MIT teams working on \nearly detection and intervention of the onset of stroke, they formulated their AI value \nproposition as shown in figure\u00a09.7. The AI system architecture illustrates the labeled data \nfeeding into the desired Misty apps and skills. The apps and skills, designed from the \nincoming labeled data, form the core ML techniques to enable BEFAST stroke detec-\ntion and intervention. The architecture uses a multicloud computing environment, such \nas with Microsoft Azure, Amazon Web \n S\nervices (AWS), or Google Cloud Platform. The \nteam also included the use of multiple Misty robots and available open-\n sour\nce tools.\nThe prior descriptions, on the ele\n ments of the AISDM frame\nwork shown in fig-\nure\u00a09.4, lead to coupling the near-\n term and \nlong-\n term strategic \ndirections with the AI \ntechnology underpinning the AI value proposition. We are now equipped to formulate \nthe AI strategic road map (i.e., the strategic blueprint), aligning the value proposition \nwith the customer\u2019s value capture.\n9.6 AI Strategic Road Map: A Blueprint\nThe AI strategic road map bridges the five early subcomponents of the AISDM \nframework\u2014\n long-\n term mission and vision and envisioned \n futur\ne (section\u00a0 9.3), the \n organization cor\ne values and strategic direction (section\u00a09.4), and the AI value proposi-\ntion (section\u00a09.5)\u2014\n with the implementation blueprint. As w\ne have emphasized through-\nout this chapter, a strategy without an implementation blueprint is not \n going to bring\n \nbusiness value to an AI-\n driv\nen \n organization. The sev\nen ele\n ments of an AI strategic r\noad \nmap are:\n\u2022\n B\nusiness needs: A clear delineation of the stakeholder\u2019s requirements to ascertain \nthat the AI value proposition is aligned with the value capture from the view-\npoint of the customers.\n\u2022\n SW\nOT: An analy\n sis of organization\n\u2019s strengths and weaknesses (internal \n factors), \nand oppor\ntunities and threats (external \n factors).\n\u2022\n Risk management: Risk categories and risk lev\nels.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2769, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "ace7ed36-0a06-4fc5-bdd4-721a5292c5ac": {"__data__": {"id_": "ace7ed36-0a06-4fc5-bdd4-721a5292c5ac", "embedding": null, "metadata": {"page_label": "22", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**Question:** What are the key components of the AI value proposition related to stroke detection and intervention as presented by the Misty robot team?\n\nThis question is tailored to extract specific details about the AI value proposition mentioned in the context, particularly focusing on the application of the Misty robot in healthcare settings, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, stroke detection, Misty robot"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "154d86ae-8f60-479d-b7b3-cef1ee9a4fac", "node_type": "4", "metadata": {"page_label": "22", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "b110ae749924946a16004d3b6523002f047eed35698e338f8696954f1bc022af", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "308 Chapter 9: AI Strategy and Road Map\nLegend Cloud ML/AI pipeline\nData conditioning\nMachine learning\nModern computing\nRobust and responsible AI\nModel updates Training data\nMisty command center\nHobbyists Educators\nProfessionals\nMisty apps\nApp data + sensor data\nMisty skills\nMisty learn\nScene\nText\nSLAM\nSpeech\nFace\nEmotion\nLabeled data\nRest API\nTouch\nExpansion\necosystem\nMisty Skill\nRunner\nTooling:\nEvents + data\nHTTPS +\nwebsocket\nHuman-machine\nteaming\nMisty senior\nliving app\nMisty stroke\ndetection skill\nMisty anomaly\ndetection skill\nExpansionsSpeakers\nMicrophones\nFlashlight + LED\nCamerasMotors\nMisty hardware boundary\nRest API\nCommands\nMisty cloud\nMisty Misty\nswarm\nLCD panel\nRaspberry Pi\nFigure\u00a09.7 AI value pr oposition from the Misty robot team on stroke detection and \nintervention.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 869, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "86d66382-2e34-4389-b2a0-d274dc041a93": {"__data__": {"id_": "86d66382-2e34-4389-b2a0-d274dc041a93", "embedding": null, "metadata": {"page_label": "23", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a specific question that can be answered:\n\n**Question:** What are the key elements and considerations involved in formulating an AI strategic road map, particularly in relation to understanding business needs and stakeholder pain points?\n\nThis question is tailored to the unique insights presented in the context, particularly regarding the mapping of AI capabilities to business needs, the importance of customer focus, and the strategic implementation framework discussed in the document.", "excerpt_keywords": "Keywords: AI strategy, business needs, stakeholder analysis"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "48ea77df-6459-4f8f-8c1e-6ef0469dbf63", "node_type": "4", "metadata": {"page_label": "23", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "5d2caed1d32f804e2e8dd13f31f72004a6d95ac86ddca357f4bf98b9bb3d11e7", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.6: AI Strategic Road Map: A Blueprint 309 \n\u2022 G oals and actions: Roles and responsibilities within the leadership and manage-\nment team to achieve a defined set of objectives.\n\u2022\n Capabilities \nversus business needs: Mapping of AI capabilities to the business \nneeds of the stakeholders and determining if \n ther\ne are critical gaps.\n\u2022\n P\nerformance metrics: T ools and techniques for evaluating execution pro\n gr\ness \nwhen implementing the AI strategic road map.\n\u2022\n P\nrototypes (MLOps demo): Demonstration of the MVP to gain momentum \n(see table\u00a09.1).\nLet us no\nw describe in more detail each of the seven ele\n ments of the AI strategic \nr\noad map, starting with business needs. \n Ther\ne have been a number of academic and \nhow-to articles on the effective mapping of a business digital transformation [35\u201337]. \nAn emphasis in \n these r\necommended approaches is to understand the pain points of \nthe stakeholder (e.g., the customer), and how the value proposition addresses them. \nThey point out the importance of focusing not just on technology, but instead on the \nbusiness value (i.e., the customer\u2019s value captured from the AI value proposition).\nAs discussed in chapter\u00a02, the strategic road map implementation\u2014\n specifically\n, the AI \nvalue proposition\u2014\n hinges on the effectiv\ne execution of the AI system architecture imple-\nmentation framework shown in figure\u00a02.2. We \n will discuss the AI strategic implementa\n-\ntion in more detail in chapter\u00a010. In chapter\u00a03, the questions to answer \n w\nere focused on \nthe data, ML algorithms, and computing requirements (as shown in \n table\u00a0\n3.1). Business \nunderstanding for creating value out of AI capabilities is intrinsic to the key phases of the \ncross-\n industr\ny standard \n pr\nocess for data mining (CRISP-\n DM) [38].\nI\nn formulating the AI strategic road map, we need to ask higher-\n lev\nel questions focus-\ning on the expected value delivered to the customer. T\nable\u00a09.2 addresses the key ques-\ntions. Again, the AI team must be customer focused. Answers to \n these questions, during\n \nthe formulation of the AI strategic development road map and prior to the implementa-\ntion phase, are critical to the successful design, development, and deployment of AI \ncapabilities.\nThe questions in the \n table ar\ne an adaptation of the well-\n kno\nwn questions known as the \n\u201cHeilmeier Catechism,\u201d or sometimes called the \u201cHeilmeier Criteria,\u201d originally posed by \nGeorge\u00a0H. Heilmeier, in deciding \n whether to appr\nove funding research proj\n ects.\nThe M\nisty robot with the MIT team formulated a set of answers to the questions \nposed \n her\ne, which are given in \n table\u00a09.3.\nN\next, we turn our attention to a SWOT analy\n sis of the \n organization with r\ne\n spect \nto the offer\ned AI product or \n ser\nvice. The proper method to develop a SWOT analy\n sis \nis to identify the internal and external \n factors that most critically affect the ability of \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2980, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "cf334660-a1fe-41b6-909d-f1c599236c43": {"__data__": {"id_": "cf334660-a1fe-41b6-909d-f1c599236c43", "embedding": null, "metadata": {"page_label": "24", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context from Chapter 9 of the document on AI Strategy and Road Map, here is a question that can be specifically answered by the content:\n\n**Question:** What key questions should an organization consider when assessing the business needs for an AI product or service, according to the Heilmeier Criteria?\n\nThis question is tailored to extract specific insights from the text regarding the evaluation process for AI capabilities, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, Heilmeier Criteria, business assessment"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "31a4eea4-647b-45af-b42d-bcb95895308a", "node_type": "4", "metadata": {"page_label": "24", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "46cc831efef1cefd672bc03f7e5db519abbb872b805dfebdde4ac45c8a619b79", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "310 Chapter 9: AI Strategy and Road Map\nthe organization to design, dev elop, integrate, and deploy the AI capability in produc-\ntion. One can formulate an effective SWOT analy\n sis as follo\nws [39]:\n\u2022\n S\ntart with \n either of the follo\nwing:\n\u2022\n S\ntrengths and weaknesses (internal)\n\u2022\n Then, oppor\ntunities and threats (external)\n\u2022\n O\nr strengths and opportunities, and then weaknesses and threats\n\u2022\n Look at alternativ\nes:\n\u2022\n D\nebate alternatives viewed through the lens of making your product or \n ser\nvice \nexecutable, and in line with the 1-\n to-5-\n y\near envisioned \n futur\ne (i.e., the three \nhorizons: near term, midterm, and far term).\n Table\u00a09.2 Key questions to ask addr essing business needs, adapted from the Heilmeier \nCriteria\nKey Questions Comments\nWhat AI capability is the customer looking for \nfrom this AI product or \n ser\nvice?\nWork from the result expected back to the product \nor \n ser\nvices needed.\nHow is it done \n today? And what ar\ne the limits of \nthe current practice?\nUnderstand the competition landscape.\nWhat is new in your approach? And why do you \nthink it \n will be successful?\nH\nighlight the unique differentiator.\nWho cares? Identify the customers with influence and/or \nfunding resources.\nIf \n y\nou\u2019re successful, what difference \n will it make? E\nmphasize the customer value aligned to the AI \nvalue proposition (using the AI system architecture).\nWhat are the risks and the payoffs? Assess the capabilities versus the needs through the \nlens of a risk management approach (i.e., risk \ncategories and levels).\nHow much \n will it cost? H\now long \n will it take? T\nime is money. Balance requirements against time \nand cost.\nWhat are the \n per\nformance metrics? Define clear metrics to assess pro\n gr\ness.\nWhat are the milestones to check for success? Formulate the success criteria as defined in the \nenvisioned futur\ne.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 1936, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "25d3fb7b-1564-4156-acd8-f90dd3c80ef2": {"__data__": {"id_": "25d3fb7b-1564-4156-acd8-f90dd3c80ef2", "embedding": null, "metadata": {"page_label": "25", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**What are the key performance metrics and milestones for the development of the Misty robot as an early stroke detection solution?**\n\nThis question is tailored to extract specific details about the performance metrics and milestones outlined in the context, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: Misty robot, stroke detection, performance metrics"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "e693d724-742a-41d2-9f3e-9d19f1dfff7e", "node_type": "4", "metadata": {"page_label": "25", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "70a1256998cfa8b4295ee6c7ba909c74dfe35db7401d7c60c9842c485e5f1c52", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.6: AI Strategic Road Map: A Blueprint 311 \n Table\u00a09.3 Misty r obot answers to questions addressing business needs\nKey Questions Answers\nWhat AI capability is the customer looking for \nfrom this AI product or \n ser\nvice?\nHelping caretakers and the el\n derly as an early \nstr\noke detection and intervention solution for \nresidential environments.\nHow is it done \n today? And what ar\ne the limits of the \ncurrent practice?\nStroke victims go too long before treatment \n because r\necognition of symptoms by the patient \nor caretaker is slow. Average time to reach the \nemergency room is 5.5 hours.\nWhat is new in your approach? And why do you \nthink it \n will be successful?\nM\nisty with ML capabilities \n will be a companion \nand vigilant attendant to notice the first physical \nsigns or be\n hav\n ior changes caused b\ny a stroke. \nSensors and ML algorithms are available now\nWho cares? El\n derly patients and their car\netakers deserve \npeace of mind and a reliable backup (i.e., \nnonthreatening appearance)\nIf \n y\nou\u2019re successful, what difference \n will it make? M\nillions of \n people hav\ne heightened risk \n factors \nfor str\noke, and billions of dollars in treatment \ncost are on the line. Only 10\u00a0\n per\ncent of \n today\n\u2019s \nstroke patients make a full recovery\nWhat are the risks and the payoffs? Risk is in the rejection of Misty in the target use \ncase. The payoffs \n will be commensurate with the \nenvisioned \n futur\ne time line.\nHow much \n will it cost? H\now long \n will it take? Cost is in primarily softwar\ne development. Time \nto completion is <6 months for proof of concept \nand <9 months to a prototype deployment.\nWhat are the \n per\nformance metrics? High accuracy in early stroke detection; very low \nfalse negatives.\nWhat are the milestones to check for success? Checkpoints are as follows:\n1. \n P\nroof of concept: Ability to recognize time \nseries invariance in normal be\n hav\n ior patterns\n2. \nT ransition to Misty platform\n3. T\nraining for physical symptoms with \ncompiled data\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2070, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "f133a29a-f522-476e-9187-92cfd596d603": {"__data__": {"id_": "f133a29a-f522-476e-9187-92cfd596d603", "embedding": null, "metadata": {"page_label": "26", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "What are the specific risk categories identified in the AI strategic road map, and how do they relate to the successful implementation of AI system architecture?", "excerpt_keywords": "Keywords: AI strategy, risk management, system architecture"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "9f6436d8-2949-473a-a017-e076e259b68c", "node_type": "4", "metadata": {"page_label": "26", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "58741dbbe44a4afbfd1208bfc3cefa8852f5f14252190d27263e0455264bc75f", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "312 Chapter 9: AI Strategy and Road Map\n\u2022 S ummarize these alternativ es.\n\u2022\n V\note on top choices.\n\u2022\n D\no a quick revisit again \n after completing all four categories.\n\u2022\n SW\nOT analy\n sis output:\n\u2022\n H\nighlight the most impor tant \n driv\ners per quadrant (typically \n limited to about \nfiv\ne)\nThe MIT team also performed a SWOT analy\n sis for their \nMisty robot offering, as \nshown in \n table\u00a09.4.\nThe thir\nd component of the AI strategic road map, risk management, deserves a \ndetailed explanation since \n ther\ne are well-\n established tools within the systems engineering\n \ndiscipline [40], but that have not yet been adapted to the development of AI strategic \nplans. In this section, we bridge that gap by introducing the reader to \n these risk manage\n-\nment tools. It is impor tant to identify the risk categories and lev\nels within the AI strate-\ngic road map since \n these ar\ne crucially impor tant to the successful implementation of the\n \nAI system architecture framework illustrated in figure\u00a02.2.\nThe INCOSE: Systems Engineering Handbook [40] addresses several types of risk cat-\negories and levels, as shown in figure\u00a09.8. T o be consistent with the International Coun-\ncil on Systems Engineering (INCOSE) standards and guidelines, we highlight the \nmeaning of each of the following risk categories:\n\u2022\n T\nechnical risk: The possibility that a technical requirement of the system may \nnot be achieved.\n\u2022\n Cost risk: The possibility that the av\nailable \n budget \n will be ex\nceeded.\n\u2022\n Schedule risk: The possibility that the pr\noj\n ect \n will fail to meet the scheduled \nmilestones.\n\u2022\n P\nrogrammatic risk: Risk produced by events that are beyond the control of the \nproj\n ect man\n ag\n er and can affect the risk in any of the other thr\nee risk categories\nNote that \n these risk categories ar\ne exacerbated by a number of \n factors, such as r\nequire-\nment drift (i.e., scope creep), technical prob\n lems, compr\nessed schedules, and \n limited\n \nfunds. Therefore, \n ther\ne needs to be alignment among the envisioned \n futur\ne, the strategic \ndirection\u2014\n discussed early in the AISDM frame\nwork\u2014\n and the AI v\nalue proposition \nwith the execution approach defined in the AI strategic plan.\n These risk categories hav\ne another impor tant and complementar\ny dimension when \nassessing the impact on the overall proj\n ect. As illustrated in figur\ne\u00a09.8, the risk levels \ndetermine the severity of the risk categories on AI development. It is an assessment of the \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2545, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "dc958819-3b5a-48b5-8cd7-b959c45838ec": {"__data__": {"id_": "dc958819-3b5a-48b5-8cd7-b959c45838ec", "embedding": null, "metadata": {"page_label": "27", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**Question:** What are the identified strengths and weaknesses of the Misty robot as outlined in the SWOT analysis, and how do these factors relate to its potential use in AI detection of strokes?\n\nThis question is tailored to extract specific insights from the SWOT analysis presented in the context, focusing on the internal factors (strengths and weaknesses) that could impact the robot's effectiveness and acceptance in a critical application like stroke detection.", "excerpt_keywords": "Keywords: AI strategy, Misty robot, SWOT analysis"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "290fed83-3e4b-4890-ac95-a1ed4cf30a54", "node_type": "4", "metadata": {"page_label": "27", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "a12b420ffe8e37a39d03b04054d44ba3cf66e107d90fb69f4393d267d3f2dd6d", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.6: AI Strategic Road Map: A Blueprint 313 \nlikelihood that an event will occur and the undesirable consequence of that ev ent on the \nAI proj\n ect [40, 41]. The likelihood is often pr\nesented as a probability of the event occur-\nring (from low to high). The consequence, or impact of an event, depends on the type \nof event at any of the subcomponents in our AI system architecture causing a risk (e.g., \nlack of data, low-\n per\nforming ML algorithms, \n limited computing r\nesources, adversarial \nattacks, and many other technical risks). The same is true for programmatic, cost, and \nschedule risks. The risk assessments have a direct implication on the Vee-\n model subcom\n-\nponents [42] in figure\u00a02.1 and the AI system architecture implementation framework \nillustrated in figure\u00a02.2.\nThe fourth ele\n ment of the AI strategic r\noad map is goals and actions. Goals enumer-\nate objectives that must be met to successfully develop, integrate, and deploy an AI \nproduct or \n ser\nvice. The actions are formulated with re\n spect to the set of goals. I\nt is also \nimpor tant to allocate a member of the AI team with the authority and r\nesponsibility to \n Table\u00a09.4 Misty r obot SWOT analy sis\nI\nnternal \nFactors Strengths Weaknesses\n\u2022 V\nersatile platform, navigation of a home \nis built into the design \n\u2022 \n The shor\nt height of Misty robot \nmeans that some events may be \nout of view.\n\u2022 \n H\nigh-\n r\nesolution cameras integrated on \nboard\n\u2022 The mar\nketing platform as a tool for \nhobbyists might reduce trust in the \nlife-\n \nor-\n \ndeath BEFAST application.\n\u2022 Proximity with the developer community \u2022 P\nrivacy violations have the potential \nto damage com\n pany image and\n \nreduce customer trust.\nExternal \nfactors Opportunities Threats\n\u2022 \n N\no existing commercial platform for AI \ndetection of stroke on the market\n\u2022 \n A\nbility to make 911 calls / proper \nemergency alerts\n\u2022 \n M\nisty robot is likely to be accepted given \nits form \n factor\n\u2022\n P\nos\n \nsi\n \nble regulatory prohibitions for \nuse in nursing homes. (however, \n ther\ne is a large market potential).\n\u2022 \n Car\netakers are increasingly trusting of and \nsavvy with technology\n\u2022 \n P\nersonal robotics is a very active \ngrowth sector.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2268, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "ecec0543-5fc7-46d3-bb37-8aa2361e51f1": {"__data__": {"id_": "ecec0543-5fc7-46d3-bb37-8aa2361e51f1", "embedding": null, "metadata": {"page_label": "28", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the different risk categories and their associated levels as outlined in the AI Strategy and Road Map document?\n\nThis question is tailored to extract specific information from the context regarding the risk management framework presented in the document, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: risk management, AI strategy, programmatic risk"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "5878a25f-584f-4051-a575-549bf0b86b57", "node_type": "4", "metadata": {"page_label": "28", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "f186c509d6b3caaa49594d3e9f768efb3137bcc02b30230a3b0c7bc19bfb9859", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "314 Chapter 9: AI Strategy and Road Map\nRisk categories\nTechnical\nrisk\nMission\n Technical\nproblems\nLimited\nfunds\nchanges\nTechnical\n problems\nCompressed\n schedules\nSchedule\nrisk\nProgrammatic\nrisk\nImposed\nbudgets\nDemand\nschedules\nSchedule\nslips\nRisk levels\nHigh\nCost risk\nHigh risk\nMedium risk\nConsequence\nLow\nLow\nLow risk\nLikelihood\nHigh\nFigure\u00a09.8 INCOSE risk management categories and levels [40]. \u00a9 2015 John Wiley & \nSons, Inc.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 510, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "b7bd94dc-a0f5-427f-8d93-8611a50d2885": {"__data__": {"id_": "b7bd94dc-a0f5-427f-8d93-8611a50d2885", "embedding": null, "metadata": {"page_label": "29", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components of an AI strategic road map, and how can they be utilized to align AI capabilities with business needs?\n\nThis question is tailored to extract insights from the detailed discussion on the elements of an AI strategic road map, including the importance of defining goals, actions, timelines, and performance metrics, as well as the relationship between existing capabilities and stakeholder business needs.", "excerpt_keywords": "Keywords: AI strategic road map, business needs, performance metrics"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "c4035c6b-b395-4a5d-a257-28169e5c2dba", "node_type": "4", "metadata": {"page_label": "29", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "f3125050dc5e36c1dbfdcb9870859fa2c30c3cdedb94b93565d9f3d0e3de567a", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.6: AI Strategic Road Map: A Blueprint 315 \nmeet a subset of the defined actions. Other wise, the AI pr oj ect can fail because of lack of \nowner\n ship b\ny the team members. It is useful to define the goals and actions relative to \naddressing the business needs, SWOT analy\n sis, and risk management. \n These goals and\n \nactions must also have a deliverable time line to make them tangible. An example of a \ngoal for the Misty robot application might be to receive approval from the US Food and \nDrug Administration (FDA) to operate in nursing homes. The action can be to fill out \na formal request with the FDA office in question.\n Ther\ne are also practical tools to address capabilities versus business needs as part of a \ncomprehensive AI strategic road map. A tool used by one of the authors, in the \n actual\n \ndevelopment of a strategic road map, is shown in figure\u00a09.9. The chart depicts capabili-\nties (existing or new) and stakeholder business needs (existing or new). This topology is \nvery useful \n because an existing customer can be v\nery receptive to advancing capabilities \nby evolving from existing to new. Or an existing capability, in development or delivered \nto an existing customer, might be very appealing to a new customer if it underwent some \nadaptations.\nThe \u201ccapabilities versus business needs\u201d context is most useful when revenues are iden-\ntified for each of the respective AI programs or proj\n ects. The arr\nows represent the use of \nan \n earlier pr\nogram in a new program or programs. A well-\n functioning AI \n organization is\n \nlikely to have most of its revenues (and backlog) in the Existing-\n E\nxisting quadrant. \n Ther\ne \nare likely less AI programs in the New-\n N\new quadrant since new capabilities for a new \nstakeholder require significant marketing and business development efforts. In the \n pr\nocess \nof identifying di\nff er ent AI pr\nograms, the AI strategic road map must be directly coupled \nwith the system applications of the AI strategic direction shown in figure\u00a09.6. For exam-\nple, for the Misty robot that we have discussed throughout this chapter, the focus has \nbeen primarily on the el\n derly car\netaker AI application. However, the same AI capability \n(existing), with some modifications, can be well matched to a home security system, \n hazar\nd detection, or teacher\u2019s assistant (representing \n either ne\nw capabilities for existing \nstakeholders or similar capabilities for new stakeholders).\nThe sixth ele\n ment \nof the AI strategic road map must incorporate both quantitative \nand qualitative \n per\nformance metrics to determine how well the execution of the AI \nstrategic blueprint is progressing. An example of a quantitative metric is an evaluation \nof the accuracy and level of false negatives (i.e., meaning the robot indicated no stroke \nwhen the el\n derly person did hav\ne a stroke) in the early stroke detection.\nA more macro-\n lev\nel metric, as a qualitative metric, is the level of maturity of the pro-\nposed AI product or \n ser\nvice. All products or \n ser\nvices go through a life cycle, depending \non how mission critical the offering is to the AI \n organization v\nersus the level of com\n pany\n \ndifferentiator, as illustrated in figure\u00a09.10.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 3293, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "ef3693ea-3100-4bc6-b82f-0f86ce9de21a": {"__data__": {"id_": "ef3693ea-3100-4bc6-b82f-0f86ce9de21a", "embedding": null, "metadata": {"page_label": "30", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context from Chapter 9 of the document \"AI Strategy and Road Map,\" here is a specific question that can be answered using the information:\n\n**Question:** What are the key quadrants in the AI strategic road map that organizations should focus on to innovate and maximize revenue from AI capabilities?\n\nThis question is tailored to extract insights specifically from the discussion of the quadrants mentioned in the text, which outlines the stages of AI product maturity and strategic focus areas for organizations.", "excerpt_keywords": "Keywords: AI strategy, innovation, revenue generation"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "06064cf5-c1b3-4c8f-9417-a59e4944783c", "node_type": "4", "metadata": {"page_label": "30", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "5729147c735c5b924e10253caec597e9018c1e0e4b60b10f45da41d775f63500", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "316 Chapter 9: AI Strategy and Road Map\nA thriving technology- based organization must be constantly inno vating. This repre-\nsents the lower-\n right quadrant in figur\ne\u00a09.10. Once products or \n ser\nvices demonstrate \nuseful AI capabilities, the \n organization can then exploit this adv\nancement to gain broader \nmarket share with existing customers or penetrate new sources of revenue as high com\n-\npany differ\nentiators\u2014\n this is r\nepresented by the top-\n right quadrant. O\nnce the AI product \nor \n ser\nvice reaches maturity, it is best to commoditize the AI capability to reap the bene-\nfits of the revenue stream, and some percentage of the revenue can also be used to infuse \nsources of funding into new, innovative AI products or \n ser\nvices. Fi\n nally\n, the last quadrant \nof figure\u00a09.10 represents the outsourcing of routine jobs (e.g., product support).\nThe last ele\n ment of the AI strategic r\noad map requires a description of the type of \nprototype \n under the categor\ny of MLOps. This component of the road map is so impor\n-\ntant to the ultimate success of an AI capability that w\ne devote chapters\u00a010 and 11 to AI \ndeployment and operations. As emphasized \n earlier in \n table\u00a0\n9.1, executing \n pilot pr\noj\n ects\n \n will help with gaining momentum. \n These \n pilot demonstrations ser\nve to assess the \nStakeholder\nProgram 1\nProgram 3\nProgram 15\nCapabilities\nExisting New\nAdvanced research\nExisting\nNew\nCloud and software systems securityAI systems security\nCore capabilities:\nProgram N\nProgram 14\nProgram 9\nProgram 10\nProgram 12\nProgram 2\nProgram 13\nProgram 7\nProgram 11 Program 16\nProgram 4\nProgram 8\nProgram 5\nProgram 6\nFigure\u00a09.9 Capabilities versus stakeholder business needs.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 1773, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "f7e3d34f-b990-447d-b3d3-60cf67485f46": {"__data__": {"id_": "f7e3d34f-b990-447d-b3d3-60cf67485f46", "embedding": null, "metadata": {"page_label": "31", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What role does the AISDM framework play in the strategic planning and execution of AI products or services within an organization?\n\nThis question is tailored to the specific details mentioned in the context regarding the AISDM framework and its importance in encapsulating the focus, justification, and plans for AI development, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AISDM framework, AI strategy, execution"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "9b3972ca-09f4-4d4f-86b4-0ec647712b26", "node_type": "4", "metadata": {"page_label": "31", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "3c227e1abbf6393a20d16d8f190a74993c2dbab9115714d9a346446087c13ae0", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.7: Strategy and Execution: A Complementary Duo 317 \npro gr ess in formulating new innovative AI concepts, as shown in the lower- right quad -\nrant in figure\u00a09.10.\nThe MIT team did an in-\n class demonstration to a panel of academia and AI prac\n-\nti\n tion\n ers, of an initial \n pilot pr\nototype using the Raspberry Pi (representing the single-\n \nboar\nd computer that could \n house the M\nisty robot\u2019s \u201cAI brains\u201d). The team was able to \nsuccessfully demonstrate the ability to learn normal patterns, spot movement pattern \nchanges, and notify responsible caretakers if an abnormal be\n hav\n ior was detected.\nAs \nshown in figure\u00a09.4, the AISDM framework must be used as an ongoing and for-\nmal document that encapsulates the overall focus, justification, and plans for the design, \ndevelopment, integration, and deployment of the \n organization\n\u2019s AI products or \n ser\nvices. \nAn impor tant par\nt of revisiting the strategic plan is to incorporate critical gaps. The criti-\ncal gaps result from an in-\n depth analy\n sis of the subelements of the AI strategic r\noad map \n(i.e., its seven ele\n ments), \nwith re\n spect \nto what desired business needs have not yet been \nmet.\n9.7 Strategy and Execution: A Complementary Duo\nWe began this chapter with a quote from Morris Chang: \u201cWithout strategy, execution is \naimless. Without execution, strategy is useless.\u201d Strategy depends on successful execu-\ntion to provide meaning and benefits to an \n organization. S\nimilarly, successful execution \nrequires a directional vector\u2014\n codified in the strategic dev\nelopment road map\u2014\n for the\n \nCommodities\n(ef\ufb01ciency; e.g., \nhigh-revenue \nproduct but low \ndifferentiator)\nHigh\nHigh\nLow\nLow Differentiator\nMission \ncritical \nto your \ncompany\nOutsource routine jobs \n(cost management; \ne.g., product support)\nInnovate \n(reward risk taking; \ne.g., data conditioning, \nML algorithms, human-\nmachine teaming, ...)\nExploit new advances \nin products or services \n(competitiveness; use \nhigh differentiator)\nFigure\u00a09.10 Macr o- level assessment of an AI pr oduct or service.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2131, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "37745ce7-9c77-49d0-8f92-098ebdbaa7cd": {"__data__": {"id_": "37745ce7-9c77-49d0-8f92-098ebdbaa7cd", "embedding": null, "metadata": {"page_label": "32", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**What is the AISDM framework and how does it contribute to the development and deployment of AI capabilities within an organization?**\n\nThis question is tailored to extract specific insights from the text regarding the AISDM framework, its purpose, and its role in the strategic planning and execution of AI initiatives, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AISDM framework, AI strategy, deployment"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "3b317ca6-400d-4591-9d0e-822c35f69c5a", "node_type": "4", "metadata": {"page_label": "32", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "83c257a0b38ea56c40b58a6e5bd9355d7f4133937d78bbed9089e05742555a12", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "318 Chapter 9: AI Strategy and Road Map\n organization and the AI team to have a clear understanding of the AI value proposition, \nand its intended business value to stakeholders, as a function of time (i.e., the envisioned \n futur\ne).\n Ther\ne have been many articles and studies showing lack of success in transitioning \nAI concepts into operation. Some of \n these barriers ar\ne particularly problematic for \n organizations that \n w\nere not originally digital. T\noday, AI \n organizations must make timely\n \ndecisions based on data-\n driv\nen approaches while attending to a rapidly evolving AI mar-\nket. As discussed by Fountaine et\u00a0al., in order to scale up, AI \n organizations must hav\ne a \nclear understanding of what is feasible, the business value, and time horizons [43].\nIt is also critical to incorporate the RAI guidelines discussed in chapter\u00a08. AI capa-\nbilities might show the right levels of per\nformance according to the metrics described \nin the strategic road map but can result in complete failure and not be accepted by the \nstakeholders, if \n these capabilities do not adher\ne to the FASTEPS princi\n ples.\nT\no increase the likelihood of success, in this chapter, we have described the AISDM \nframework for leaders, man\n ag\n ers, and technical staff who ar\ne responsible for develop-\ning and deploying AI capabilities. The tools described offer more clarity and specifics \nof the strategic focus (near term, midterm, and far term) and road map. In the next \nseveral chapters, we turn our attention to AI execution and deployment.\n9.8 Main T akeaways\nIn this chapter, we set the stage for part II of the book by discussing the steps involved \nin the formulation of an AI strategy that culminates with a strategic road map. It serves \nas a blueprint for upper management, technical leaders, AI architects, designers, and \nimplementers to pro\n gr\ness from architecture princi\n ples to deplo\nyment. A strategy is not \na static deliverable, but rather a living blueprint that must be revisited and, if necessary, \nupdated over time while the AI system is undergoing development and, \n until the final\n \ndeployment, careful attention must be paid to its use and monitoring. A key part of a \nsuccessful strategy is to include all ranks, from AI management to AI staff, in the \n pr\nocess \nof strategic thinking and in the formulation of the AI strategic road map.\nStrategic thinking puts a framework around determining the overall direction of an \nAI \n organization. M\nore specifically, strategic thinking helps answer critical manage-\nment questions, such as the following:\n\u2022\n What \nshould the AI organization \nlook like in the near term (horizon 1; 1\u20132\u00a0years), \nmidterm (horizon 2; 3\u20134\u00a0years), and far term (horizon 3;\n \u2265\n \n5\u00a0years)?\n\u2022\n Who benefits fr\nom strategic thinking and the formulation of a strategic plan?\n\u2022\n Who should w\ne be hiring?\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2936, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "2accee55-8255-482d-b0e7-8ac2f84c3ef1": {"__data__": {"id_": "2accee55-8255-482d-b0e7-8ac2f84c3ef1", "embedding": null, "metadata": {"page_label": "33", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**What are the key components that inform the AI value proposition within the AISDM framework?**\n\nThis question is tailored to extract specific information from the context regarding the formulation of the AI value proposition, which includes AI implementation opportunities, leadership and talent, AI governance, and organizational culture. This level of detail is unlikely to be found in other sources without similar context.", "excerpt_keywords": "Keywords: AI strategy, AISDM framework, value proposition"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "0f8c237e-bf8f-4ab6-86e2-19db5ceecb06", "node_type": "4", "metadata": {"page_label": "33", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "6b0291bcac8ba720e7433652c82bbc85fc8ca3fdeb6e6b1d3dd74137e00fcfdb", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.8: Main Takeaways 319 \n\u2022 What should w e be learning?\n\u2022\n What technologies do w\ne need to enter and exit?\n\u2022\n What contracts and channels should w\ne grow or shrink?\n\u2022\n Who \n will be willing and able to pay for it?\n\u2022\n What pr\no\n cesses ar\ne or are not needed?\n\u2022\n H\now federated should the portfolio be with re\n spect to internal and external \npar\ntners?\n\u2022\n What should be the mix of dir\nect and contracted employees?\nThe mastery of strategic thinking helps staff and entry-\n lev\nel man\n ag\n ers adv\nance in a \ncompetency that has long-\n lasting v\nalue, especially in highly competitive, technology- \nbased \n organizations. F\nour of the ways to improve your strategic thinking are: Know \n(observe and seek trends), Broaden (ask the tough questions), Communicate (shape com-\nmon understanding), and Act (embrace conflict to debate key challenges).\nThe AISDM, shown in figure\u00a09.4, provided context and details relevant to formulat-\ning an AI strategic road map. The AISDM framework is applicable to formulating an AI \nstrategic road map at the \n organization lev\nel, the business-\n unit lev\nel, the group-\n unit lev\nel, \nor the AI proj\n ect lev\nel.\nThe AISDM framework calls for first formulating a draft of the mission and vision \nstatements. \n These statements can be r\nefined \n after completing a full pass thr\nough the \nAISDM framework and after \ncompleting a draft of the AI strategic road map. The other \nkey ele\n ments of the AISDM frame\nwork are the envisioned \n futur\ne and \n organization cor\ne \nvalues. \n These two ele\n ments ser\nve to formulate the com\n pany\n\u2019s strategic direction for an \nAI product or \n ser\nvice. The mission and vision statements, the envisioned \n futur\ne, the \n organization cor\ne values, and the AI strategic direction lead to the central part of the \nAISDM framework: the AI value proposition.\nThe AI value proposition is formulated based on the subsystems of the AI sys-\ntem\u00a0architecture discussed in part I. The value proposition is informed by four key \ncomponents:\n\u2022\n AI implementation oppor\ntunities\n\u2022\n P\neople (i.e., leadership and talent)\n\u2022\n O\nrganization AI governance, RAI princi\n ples, technologies, and infrastr\nucture\n\u2022\n \nCulture\nThe prior key ele\n ments of the AISDM frame\nwork are necessary to understand how to \nproperly create an AI strategic road map, as the blueprint for the near term, midterm, \nand far term. The AI strategic road map also serves to build clarity in transitioning from \nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2519, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "bf73af7e-5d71-4dae-877b-5bbce6545208": {"__data__": {"id_": "bf73af7e-5d71-4dae-877b-5bbce6545208", "embedding": null, "metadata": {"page_label": "34", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context regarding the AI strategic road map, here is a question that can be specifically answered by the information given:\n\n**Question:** What are the seven key elements that should be included in an AI strategic road map to ensure alignment with business needs and successful implementation?\n\nThis question is tailored to extract specific details from the text regarding the components of an AI strategic road map, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, road map, business alignment"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "a30dd57f-6ce5-40de-b5bf-b4fece780db6", "node_type": "4", "metadata": {"page_label": "34", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "a9d1968cbf75cccc7ea268c79f6287d91399138548823bef09343296fe771ec2", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "320 Chapter 9: AI Strategy and Road Map\nthe com pany \u2019s strategy to an executable blueprint. The seven ele ments of an AI strategic \nroad map are:\n\u2022\n B\nusiness needs: A clear delineation of the stakeholder\u2019s requirements to ascertain \nthat the AI value proposition is aligned with the value capture from the perspec-\ntive of the customers\n\u2022\n SW\nOT: An analy\n sis of organization\n\u2019s strengths and weaknesses (internal \n factors), \nand oppor\ntunities and threats (external \n factors)\n\u2022\n Risk management: Risk categories and risk lev\nels\n\u2022\n G\noals and actions: Roles and responsibilities within the leadership and manage-\nment team to achieve a defined set of objectives\n\u2022\n Capabilities \nversus business needs: Mapping of AI capabilities to the business \nneeds of the stakeholders and determining if \n ther\ne are critical gaps\n\u2022\n P\nerformance metrics: T ools and techniques for evaluating execution pro\n gr\ness \nwhen implementing the AI strategic road map\n\u2022\n P\nrototypes (MLOps demo): Demonstration of the MVP to gain momentum.\nNo one should start formulating an AI strategic road map without well-\n defined \nansw\ners to the stakeholders\u2019 business needs outlined in \n table\u00a0\n9.2. Often AI strategies \nfail \n because they focus primarily on the technologies; \n organizations must driv\ne their \nAI products or \n ser\nvices based on the business needs.\nOnce an AI-\n based com\n pany understands the driving business needs, the next task is\n \nformulating the \n organization\n\u2019s SWOT with re\n spect to the offer\ned AI product or \n ser\nvice. \nThe proper method to develop SWOT analy\n sis \nis to identify the internal and external \n factors that most critically affect the ability of the \n organization to design, dev\nelop, inte-\ngrate, and deploy AI capabilities in production.\nAn AI strategic road map must also balance the \n organization\n\u2019s desires against the \nachievable capabilities, as a function of time. Therefore, a crucial step in the formula-\ntion of the AI strategic road map is to assess the risk categories and levels.\nThe INCOSE: Systems Engineering Handbook [40] addresses several types of risk \ncategories and levels, as shown in figure\u00a09.8. We highlighted the meaning of each of \nthe risk categories as follows:\n\u2022\n T\nechnical risk: The possibility that a technical requirement of the system may \nnot be achieved\n\u2022\n Cost risk: The possibility that the \n budget \n will be ex\nceeded\n\u2022\n Schedule risk: The possibility that the pr\noj\n ect \n will fail to meet the scheduled \nmilestones\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2567, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "f442eb02-3d61-4e10-b1bc-f33a09510a7d": {"__data__": {"id_": "f442eb02-3d61-4e10-b1bc-f33a09510a7d", "embedding": null, "metadata": {"page_label": "35", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What is the significance of performance metrics in the development of an AI strategic road map, and how do they contribute to identifying critical gaps?\n\nThis question is tailored to extract specific insights from the text regarding the role of performance metrics in the AI strategic planning process, which may not be easily found in other sources.", "excerpt_keywords": "Keywords: AI strategy, performance metrics, critical gaps"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "93479d00-f312-4664-9447-8c3edaa04eb1", "node_type": "4", "metadata": {"page_label": "35", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "3fc95602a3f0a1808afa48f74f3b976787d3c8e8e12b143e5d6c87d68557b306", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.9: Exercises 321 \n\u2022 P rogrammatic risk: Risk produced by events that are beyond the control of the \nproj\n ect man\n ag\n er; and can affect the risk in any of the other thr\nee risk categories\nOnce we have determined the business needs, performed a SWOT analy\n sis, and\n \nassessed the categories and levels of risk, we then can proceed to identify a set of goals \nand actions. Members of the AI team must be assigned this responsibility and given the \nauthority to attend to a subset of the goals and actions; this helps the team have owner\n-\nship of the AI strategic r\noad map.\nAgain, an impor tant r\neason for developing the AI strategic road map is to clearly \ndetermine the achievable AI capabilities (existing and new) relative to the stakehold-\ners\u2019 business needs (existing and new). From this analy\n sis, one can begin to generate a \nset \nof critical gaps that can be delayed until futur\ne iterations of AI products or ser\nvices.\nOne of the most impor tant \ncomponents of a comprehensive strategic plan is the \n per\nformance metrics. We discussed quantitative and qualitative metrics. P\nerformance \nmetrics help in tracking and measuring \npro\n gr\ness. These \nmetrics also help in enumerat-\ning critical gaps.\nUltimately, the AI team must develop the MVP , an early prototype to gain credibil-\nity and provide initial value to the stakeholders. An early prototype also leads to find-\ning additional critical gaps. This effort falls \n under the r\nubric of ML operations, which \n will be discussed in the next two chapters.\n9.9 Exercises\n 1. I s it correct to say that without strategy, execution is useless, and with a strat-\negy, execution is guaranteed?\na.\n \nT rue\nb.\n \nFalse\n 2.\n A strategic r\noad map is addressed once and should never be revisited through-\nout the year in order to avoid misunderstandings.\na.\n \nT rue\nb.\n \nFalse\n 3.\n S\ntrategic thinking, as well as the strategic plan that results from the \n pr\nocess, \nhelp for example AI staff, proj\n ect leaders, and upper management.\na.\n \nT rue\nb.\n \nFalse\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2105, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "22cbce8f-86f4-4600-9d75-7f56f4e43937": {"__data__": {"id_": "22cbce8f-86f4-4600-9d75-7f56f4e43937", "embedding": null, "metadata": {"page_label": "36", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context from the document \"AI Strategy and Road Map,\" here is a question that can be specifically answered using the information given:\n\n**Question:** What are the seven elements of an AI strategic road map as outlined in the document, and why are they essential for guiding an organization's AI initiatives?\n\nThis question is tailored to extract specific information that is likely detailed in the document but may not be readily available in other sources, focusing on the unique framework for AI strategy development presented in the text.", "excerpt_keywords": "Keywords: AI strategy, strategic road map, organizational initiatives"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "a5fef0e9-45fc-4348-af99-35dff9c2215b", "node_type": "4", "metadata": {"page_label": "36", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "74ace150c9872323203adadc1880c4a46925c80d72b9a0195331e7a1228df646", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "322 Chapter 9: AI Strategy and Road Map\n 4. Choose two of the strategic thinking questions that help answ er critical man-\nagement questions, outlined in section\u00a09.1, and elaborate on what they are \naddressing and why they are impor tant.\n 5.\n P\nick one out of the four ways to improve your strategic thinking and discuss \nits meaning and benefit.\n 6.\n A 2018 M\ncKinsey & Com\n pany r\neport identified a lack of a clear strategy for \nAI as the most frequently cited barrier to AI adoption [5].\na.\n \nT rue\nb.\n \nFalse\n 7.\n The \n organization\n\u2019s mission is about \u201cwhat\u201d the \n organization wants to be. The \nvision is about \u201c\nwhy\u201d the \n organization exists.\na.\n \nT rue\nb.\n \nFalse\n 8.\n I\nn a short set of paragraphs, give succinct definitions for the envisioned \n futur\ne, \nthe \n organization cor\ne values, and the AI strategic direction.\n 9.\n The strategic r\noad map is the blueprint that codifies the near-\n term, midterm, \nand long-\n term strategic dir\nections for an AI \n organization, informed b\ny its \nresources, pro\n cesses, and v\nalues.\na.\n \nT rue\nb.\n \nFalse\n10.\n What ar\ne the seven ele\n ments of an AI strategic r\noad map?\n11.\n P\nick one of the key questions to ask addressing business needs, and describe \nwhy that question is impor tant in formulating an AI strategic r\noad map.\n12.\n D\nescribe the four risk management categories.\n13.\n E\nlaborate on the risk levels and their significance.\n14.\n H\nighlight the four quadrants of the macro-\n lev\nel assessment of an AI product \nor \n ser\nvice, in terms of mission critical to your com\n pany v\nersus com\n pany dif\n-\nferentiator, and provide a short description of each.\n15.\n An early \n pilot pr\noj\n ect is useful \n because of which of the follo\nwing:\na.\n I\nt helps in gaining momentum with demonstrating AI capabilities\nb.\n The AI team can identify additional critical gaps\nc.\n The har\ndware designers can perform a preliminary design review before \nstarting the software coding or hardware fabrication\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2033, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "6fb3fdc5-d3d8-413c-b716-a9e2d4bed1e8": {"__data__": {"id_": "6fb3fdc5-d3d8-413c-b716-a9e2d4bed1e8", "embedding": null, "metadata": {"page_label": "37", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be answered specifically from the information given:\n\n**Question:** What are some recommended performance metrics for assessing compliance with the RAI principles (FASTEPS) as discussed in Chapter 8 of the document?\n\nThis question is tailored to the specific content of the document, particularly focusing on the strategic development road map and the RAI principles mentioned, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, RAI principles, performance metrics"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "7491d6a1-b12e-42fb-a7a9-fbebde3328e6", "node_type": "4", "metadata": {"page_label": "37", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "65f170dac98251358d08d932c43829bd378abfc4d569cfe955e804b33fbb1ec8", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.10: References 323 \nd. a. and b\ne.\n N\none of the above\n16. What \n per\nformance metrics would you recommend, as part of the strategic devel-\nopment road map, to ascertain compliance with the RAI princi\n ples (F\nASTEPS) \ndiscussed in chapter\u00a08?\n9.10 References\n 1. Ng, A., MIT technology review: AI- focused E mT ech digital. 2021.\n 2.\n Rifkin, \nG., F\nuture forward: Leadership lessons from Patrick McGovern, the vision-\nary who circled the globe and built a technology media empire. 2018, McGraw-\n \nH\nill. https://\n \nwww .\n \nfutureforwardbook\n \n.\n \ncom\n \n/\n \n.\n \n3.\n H\narvard Business Review, HBR guide to thinking strategically. 2019, Harvard \nBusiness School Publishing Corporation.\n 4.\n Bo\nwman, N. 4 ways to improve your strategic thinking skills. Harvard Business \nReview, December\u00a027, 2016. https://\n \nhbr .\n \norg\n \n/\n \n2016\n \n/\n \n12\n \n/\n \n4\n \n-\n \nways\n \n-\n \nto\n \n-\n \nimprove\n \n-\n \nyour\n \n-\n \nstrategic\n \n-\n \nthinking\n \n-\n \nskills.\n 5.\n W\nebb, N., Notes from the AI frontier: AI adoption advances, but foundational bar-\nriers remain. 2018, McKinsey & Com\n pany R\neport.\n 6.\n Christensen, C.\u00a0\nM., S.\u00a0D. Anthony, and E.\u00a0A. Roth, Seeing what\u2019s next: Using the \ntheories of innovation to predict industry change. 2004, Harvard Business Press.\n 7.\n Schwar\ntz, P ., The art of the long view: Planning for the \n futur\ne in an uncertain \nworld. 2012, Currency.\n 8.\n S\ntadler, C., J. Hautz, K. Matzler, and S.\u00a0F . von den Eichen, Open up your strat-\negy. MIT Sloan Management Review, 2022. 63(2): 1\u20136.\n 9.\n H\narvard Business School, Program for leadership development: Accelerating the \n car\neers of high-\n \npotential leaders. https://\n \nwww .\n \nexed\n \n.\n \nhbs\n \n.\n \nedu\n \n/\n \ncomprehensive\n \n-\n \nleadership\n \n-\n \nprograms.\n 10.\n S\ninek, S., Start with why: How \n gr\neat leaders inspire every one to take action\n. 2009, \nPenguin.\n 11.\n MIT computer science and ar\ntificial intelligence laboratory. https://\n \nwww .\n \ncsail\n \n.\n \nmit\n \n.\n \nedu\n \n/\n \nabout\n \n/\n \nmission\n \n-\n \nhistory.\n 12.\n S\nmith, W .\u00a0K., M.\u00a0W . Lewis, and M.\u00a0L. T ushman, Both/and leadership. Harvard \nBusiness Review, 2016. 94(5): 62\u201370.\n 13.\n O R\neilly, C.\u00a0A. and M.\u00a0L. T ushman, The ambidextrous \n organization. \nHarvard \nBusiness Review, 2004. 82(4): 74\u201383.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2308, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "e19c7135-6eec-482e-868c-08ba0bbb9765": {"__data__": {"id_": "e19c7135-6eec-482e-868c-08ba0bbb9765", "embedding": null, "metadata": {"page_label": "38", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be answered specifically by the information given:\n\n**Question:** What are some key references and resources cited in the AI Strategy and Road Map document that discuss national AI strategies and competitive forces shaping strategy?\n\nThis question is tailored to extract specific information from the citations listed in the context, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, national strategies, competitive forces"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "b31f1f51-7b97-44e6-989b-9380c0909687", "node_type": "4", "metadata": {"page_label": "38", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "dbee6e6f1651f04690a528f8ffe780aa35129c2aa4db33bdacdcc2a8082009a1", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "324 Chapter 9: AI Strategy and Road Map\n 14. T ushman, M., M.\u00a0L. T ushman, and C.\u00a0A. O\u2019Reilly, Winning through innovation: \nA practical guide to leading \n organizational change and r\nenewal. 2002, Harvard \nBusiness Press.\n 1\n5. E\nnwall, T . Challenge: Formulate a strategic development roadmap helping the el\n der\nly \nusing the misty robot, 2019. https://\n \nwww .\n \nyoutube\n \n.\n \ncom\n \n/\n \nwatch\n \n?\n \nv\u200b=\u200b\nFDukxWJk6iU.\n 16.\n Chandra, A., C.\u00a0\nR. Stone, X. Du, et\u00a0al., The \n cer\nebral circulation and cerebrovas-\ncular disease III: Stroke. Brain Circulation, 2017. 3(2): 66. https://\n www .\n ncbi\n \n.\n \nnlm\n \n.\n \nnih\n \n.\n \ngov\n \n/\n \npmc\n \n/\n \narticles\n \n/\n \nPMC6126259\n \n/\n \n.\n 17.\n S\ntull, M. When it comes to recognizing a stroke, B.E.FA.S.T. 2018. https://\n www\n \n.\n \nmymarinhealth\n .\n \norg\n /\n \nblog\n /\n \n2018\n /\n \nmay\n /\n \nwhen\n -\n \nit\n -\n \ncomes\n -\n \nto\n -\n \nrecognizing\n -\n \na\n -\n \nstroke\n -\n \nb \n-\n \ne\n \n-\n \nf\n \n-\n \na\n \n-\n \ns\n \n-\n \n/\n \n.\n 18.\n D\nutton, T ., Overview of national AI strategies. Medium, June\u00a028, 2018.\n 19.\n G\nil, Y. and B. Selman, A 20-\n y\near community roadmap for artificial intelligence \nresearch in the US, 2019. arXiv preprint arXiv:1908.02624.\n 20.\n P\narker, L.\u00a0 E., Creation of the National Artificial Intelligence Research and \nDevelopment Strategic Plan. AI Magazine, 2018. 39(2): 25\u201332.\n 21.\n Schmidt, E., et\u00a0\nal., NSCAI final report. 2021, National Security Commission on \nArtificial Intelligence. https://\n \nwww .\n \nnscai\n \n.\n \ngov\n \n/\n \n2021\n \n-\n \nfinal\n \n-\n \nreport/\n 22.\n Zhang, D., N. M\naslej, E. Brynjolfsson, et\u00a0al., The AI Index 2022 Annual Report. \n2022, Stanford Institute for Human-\n Center\ned AI.\n 23.\n P\norter, M.\u00a0E., The five competitive forces that shape strategy. Harvard Business \nReview, 2008. 86(1): 25\u201340.\n 24.\n Kim, \nW .\u00a0C. and R. Mauborgne, Blue ocean strategy, expanded edition: How to \ncreate uncontested market space and make the competition irrelevant. 2014, Har-\nvard Business Review Press.\n 25.\n Lencioni, P\n.\u00a0M., Make your values mean something. Harvard Business Review, \n2002. 80(7): 113\u2013117.\n 26.\n Collins, \nJ.\u00a0C. and J.\u00a0I. Porras, Building your com\n pany\n\u2019s vision. Harvard Business \nReview, 1996. 74(5): 65.\n 27.\n N\nonaka, I. and H. Takeuchi, Strategy as a way of life. 2021, MIT Sloan Manage-\nment Review.\n 28.\n P\nrahalad, C. and G. Hamel, The core competence of the corporation. Interna-\ntional Library of Critical Writings in Economics, 2003. 163: 210\u2013222.\n 29.\n Schein, \nE.\u00a0H., Coming to a new awareness of organizational \nculture. Sloan Man-\nagement Review, 1984. 25(2): 3\u201316.\nPROPERTY OF THE MIT PRESS \nDIGITAL REVIEW COPY \nFOR PROMOTIONAL PURPOSES ONLY", "mimetype": "text/plain", "start_char_idx": 0, "end_char_idx": 2628, "metadata_seperator": "\n", "text_template": "[Excerpt from document]\n{metadata_str}\nExcerpt:\n-----\n{content}\n-----\n", "class_name": "TextNode"}, "__type__": "1"}, "88d9554b-1e7f-4667-bc5f-89afccf20dac": {"__data__": {"id_": "88d9554b-1e7f-4667-bc5f-89afccf20dac", "embedding": null, "metadata": {"page_label": "39", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are some key references that discuss the cultural implications of artificial intelligence in organizations, as mentioned in the AI Strategy and Road Map document?\n\nThis question is tailored to extract specific information from the references listed in the context, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: artificial intelligence, organizational culture, digital transformation"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "593c8e21-1e53-4a32-be0a-116939dbae2b", "node_type": "4", "metadata": {"page_label": "39", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16"}, "hash": "3c060ba2781dcece1432673f4d13e1c0ddcecd153b60e08819e52356145de96e", "class_name": "RelatedNodeInfo"}}, "metadata_template": "{key}: {value}", "metadata_separator": "\n", "text": "9.10: References 325 \n 30. V an Maanen, J., Early car eer leaders\u2014 C ircle mentoring program. 2015, MIT Lin-\ncoln Laboratory.\n 31.\n S\null, D., S. T urconi, and C. Sull, When it comes to culture, does your com\n pany \nwalk the talk? 2020, \nMIT Sloan Management Review.\n 32.\n W\nesterman, G., D.\u00a0L. Soule, and A. Eswaran, Building digital-\n r\neady culture in \ntraditional organizations. MIT S\nloan Management Review, 2019. 60(4): 59\u201368.\n 33.\n Ransbotham, S., F\n. Candelon, D. Kiron, et\u00a0al., The cultural benefits of artificial \nintelligence in the enterprise. 2021, MIT Sloan Management Review and Boston \nConsulting Group.\n 34.\n T\nouche, W ., D. Konigsburg, and J. Iwasaki, Digital frontier: A technology deficit \nin the boardroom, D.\u00a0 G.\u00a0 B. Program, Editor. 2022. Deloitte. https://\n www2\n \n.\n \ndeloitte\n .\n \ncom\n /\n \nca\n /\n \nen\n /\n \npages\n /\n \naudit\n /\n \narticles\n /\n \ndigital\n -\n \nfrontier\n -\n \na\n -\n \ntechnology\n -\n \ndeficit\n -\n \nin \n-\n \nthe\n \n-\n \nboardroom\n \n.\n \nhtml.\n 35.\n F\nritscher, B. and Y. Pigneur, Visualizing business model evolution with the busi-\nness model canvas: Concept and tool, in 2014 IEEE 16th\u00a0Conference on Business \nInformatics. 2014. IEEE.\n 36.\n O\nsterwalder, A., Y. Pigneur, G. Berrardo, and A. Smith, Value proposition design: \nHow to create products and \n ser\nvices customers want. 2015, John Wiley & Sons.\n 3\n7. M\nueller, B. How to map out your digital transformation. Harvard Business Review, \n2022. https://\n \nhbr .\n \norg\n \n/\n \n2022\n \n/\n \n04\n \n/\n \nhow\n \n-\n \nto\n \n-\n \nmap\n \n-\n \nout\n \n-\n \nyour\n \n-\n \ndigital\n \n-\n \ntransformation.\n 38.\n K\nelleher, J.\u00a0D., B. Mac Namee, and A. D\u2019arcy, Fundamentals of machine learning \nfor predictive data analytics: Algorithms, worked examples, and case studies. 2020, \nMIT Press.\n 3\n9. Leigh, D., SW\nOT analy\n sis. \nHandbook of improving \n per\nformance in the work-\nplace,\u00a0 Volumes 1\u20133, 2009. 115\u2013140. International Society for \n P\nerformance \nImprovement.\n 40.\n INC\nOSE: Systems engineering handbook: A guide for system life cycle pro\n cesses and \nactivities\n. 4th\u00a0ed., edited by D.\u00a0D. Walden, G.\u00a0J. Roedler, K.\u00a0J. Forsberg, et\u00a0al. \n2015, John Wiley & Sons.\n 41.\n E\nisner, H., Systems engineering: Building successful systems. Synthesis lectures on \nengineering, science, and technology. Vol. 14. 2011, Morgan & Claypool Publish-\ners. 1\u2013139.\n 42.\n F\norsberg, K. and H. Mooz, The relationship of system engineering to the proj\n ect \ncy\ncle, in INCOSE International Symposium. 1991, Wiley Online Library.\n 43.\n F\nountaine, T ., B. McCarthy, and T . 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Martinez and Bruke M. Kifle, and what is its primary focus?", "excerpt_keywords": "Keywords: Artificial Intelligence, Systems Approach, MIT Press"}}, "614a3eda-cd16-432b-978b-8d1a12f12804": {"node_ids": ["7a940454-ad69-41cf-a0d7-58d4d956c6a7"], "metadata": {"page_label": "ii", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the names of the authors of the book \"Artificial Intelligence: A Systems Approach from Architecture Principles to Deployment\"?\n\nThis question is unlikely to be answered elsewhere without access to the specific publication details, as it directly references the authorship of a particular book along with its publication information.", "excerpt_keywords": "Keywords: Artificial Intelligence, Systems Approach, MIT Press"}}, "e7882645-e149-4be4-9a00-7e27484ed8fe": {"node_ids": ["0338c72e-f324-4cfd-8b5a-84609ae126c4"], "metadata": {"page_label": "1", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "What is the significance of a strategic road map in the development and deployment of AI capabilities within an organization, as discussed in Part II of the book?", "excerpt_keywords": "Keywords: AI strategy, deployment roadmap, organizational framework"}}, "5c62b578-be64-429c-b876-8c787380d92d": {"node_ids": ["bc4be34e-f24b-4796-8f4d-52ff116be0cf"], "metadata": {"page_label": "2", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the five steps outlined by Andrew Ng for leading a company into the AI era, and how do they relate to the development of an AI strategy?\n\nThis question directly pertains to the specific content discussed in the chapter, particularly the five-step playbook presented by Andrew Ng, which is not likely to be found in other sources without referencing this specific context.", "excerpt_keywords": "Keywords: AI strategy, pilot projects, in-house AI team"}}, "79c4f86d-8d46-4e0e-89c2-00f8f8fc8f62": {"node_ids": ["564ebacc-63b1-46fd-9ebd-6763df8bb770"], "metadata": {"page_label": "3", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What is the AI Strategic Development Model (AISDM), and how has it been utilized in the context of developing strategic road maps for technical divisions?\n\nThis question focuses on the specific framework mentioned in the text and its application, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, strategic development model, technical divisions"}}, "614023f1-ba97-47eb-9c51-adfa84fcc05a": {"node_ids": ["345311f4-31a0-478e-9612-c867ab94ffae"], "metadata": {"page_label": "4", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key differences between strategic thinking and tactical competencies as described in the context of AI leadership and project management?\n\nThis question is tailored to the specific content of the excerpt, focusing on the distinctions made between strategic and tactical approaches in the context of AI leadership, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI leadership, strategic thinking, tactical competencies"}}, "04b82d29-1656-4bcb-9aa6-a65dec5ef342": {"node_ids": ["ccf58566-3723-4605-8f8b-374b32993198"], "metadata": {"page_label": "5", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key considerations for an AI organization when engaging in strategic thinking to shape its future direction over different time horizons?\n\nThis question is tailored to the unique insights presented in the context regarding the strategic planning process for AI organizations, including the specific time horizons (near term, midterm, and far term) and the various management questions that need to be addressed.", "excerpt_keywords": "Keywords: strategic thinking, AI organization, management questions"}}, "2e473dc6-d5d4-45fc-8477-86d6803b27ee": {"node_ids": ["65cc5a45-3e4a-4de6-b3d0-ae731197beb5"], "metadata": {"page_label": "6", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the four key components of strategic thinking as adapted from Nina Bowman's approach in the context of AI strategy development?\n\nThis question is tailored to extract specific information from the text regarding the components of strategic thinking, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, strategic thinking, organizational communication"}}, "aab232ac-02da-44b7-96dc-e0040af40c18": {"node_ids": ["4c576e21-6c89-4782-ba28-9111e3f18659"], "metadata": {"page_label": "7", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the primary barriers to AI adoption identified in the 2018 McKinsey & Company survey, and how does the AISDM framework address these barriers?\n\nThis question is tailored to extract specific insights from the context regarding the barriers to AI adoption and the role of the AISDM framework in overcoming those challenges, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI adoption, AISDM framework, strategic planning"}}, "ccbb90b4-4902-4cc6-8e31-4a84cb9fb8b9": {"node_ids": ["ccec2452-3185-4001-b771-45e1feaa7395"], "metadata": {"page_label": "8", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components of a strategic development road map as discussed in the context of AI strategy, and how do they relate to the mission and vision statements of an organization?\n\nThis question is tailored to the unique insights provided in the text regarding the importance of mission and vision statements in the context of AI strategic planning, as well as the multidisciplinary approach required for effective strategy development.", "excerpt_keywords": "Keywords: AI strategy, mission statement, strategic development"}}, "193ffe09-4eff-4836-abfa-f6060c9c59f4": {"node_ids": ["608ba398-f93f-4d0a-ac43-87d26d0630f3"], "metadata": {"page_label": "9", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components of the AI Strategic Development Model as outlined in the document, and how do they relate to the internal and external environments of an organization?\n\nThis question is tailored to the specific details mentioned in the context regarding the strategic development model, including the internal and external factors that influence an AI strategy, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI Strategy, Strategic Development Model, SWOT Analysis"}}, "33a245f8-e1a8-4187-a74a-68e7ea6240de": {"node_ids": ["af579566-4b67-4447-b082-24467feebe39"], "metadata": {"page_label": "10", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components of the AISDM framework that organizations should consider when formulating an AI strategic road map?\n\nThis question is tailored to the specific details discussed in the context regarding the AISDM framework and its application in developing an AI strategic road map, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, AISDM framework, strategic road map"}}, "6d09780c-0cb9-43e4-b299-a6a583777ea2": {"node_ids": ["df6bf61e-c47c-44d3-a18d-4ee6691ece65"], "metadata": {"page_label": "11", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context regarding the AI Strategic Development Model (AISDM) and its components, here is a question that can be specifically answered by this information:\n\n**Question:** What are the key components and considerations outlined in the AI Strategic Development Model (AISDM) for effectively implementing AI within an organization?\n\nThis question is tailored to extract specific insights from the context, focusing on the elements that contribute to the strategic development of AI in an organization, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI Strategic Development Model, implementation, governance"}}, "5126a445-cbb5-4345-a0c4-2d0e0b5b275f": {"node_ids": ["9f373b1f-ba22-4fa5-a408-db363019d2c2"], "metadata": {"page_label": "12", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be answered specifically from the information given:\n\n**Question:** What are the seven components of the AI strategic road map as outlined in the AISDM framework? \n\nThis question is unlikely to be answered in other contexts without access to the specific details of the AISDM framework discussed in this document.", "excerpt_keywords": "Keywords: AI strategy, AISDM framework, strategic road map"}}, "1cc3a3cb-87b4-41d5-81a6-8ffa0f670e5a": {"node_ids": ["f8d25ac1-9c04-4352-9258-8fcb9cddcd8f"], "metadata": {"page_label": "13", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "What specific mission and vision statements did the MIT team formulate for their AI early detection and intervention product using the Misty robot?", "excerpt_keywords": "Keywords: AI, robotics, healthcare"}}, "fd1c5d02-4fb8-42c9-b248-4548cd785bec": {"node_ids": ["bbdf2197-edd8-4296-bda8-d37bcbe38303"], "metadata": {"page_label": "14", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**What are the three horizons formulated by the MIT Misty robot team for their AI strategy, and what are the key focuses of each horizon?** \n\nThis question targets the specific strategic planning outlined in the text, which details the near-term, midterm, and far-term goals for the Misty robot, and is unlikely to be answered in other contexts without similar detailed insights into the AI strategy framework.", "excerpt_keywords": "Keywords: AI strategy, Misty robot, horizons framework"}}, "ab9de120-8a00-4ad8-84d2-eea0de5e7a5f": {"node_ids": ["e751436a-c8bf-44d5-8fc5-cbcd7b143066"], "metadata": {"page_label": "15", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**Question:** How can the integration of machine learning and the Internet of Things (IoT) in robotic systems contribute to the early detection and intervention of strokes in elderly individuals?\n\nThis question is tailored to the specific example and insights shared in the text, particularly regarding the use of robots and machine learning algorithms to monitor and respond to potential health crises in real-time.", "excerpt_keywords": "Keywords: machine learning, Internet of Things, stroke detection"}}, "2370b6af-798e-41a4-872b-f0ee9c77e626": {"node_ids": ["3d1a78f8-943a-4255-947f-d0298234b069"], "metadata": {"page_label": "16", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the core values that should guide an organization in the development of AI products or services, according to the authors of the document?\n\nThis question is unlikely to be answered elsewhere as it specifically references the authors' perspective on core values in the context of AI strategy and development, which is detailed in the provided text.", "excerpt_keywords": "Keywords: AI strategy, core values, innovation"}}, "d1b39cf5-e57f-47c5-9754-0408ecfb2c38": {"node_ids": ["b374dba3-4226-441c-9525-acbfbcb00c71"], "metadata": {"page_label": "17", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the three parts of the strategic direction element in the AISDM framework as applied to AI products and services, and how do they relate to the competencies of an organization?\n\nThis question is tailored to the specific details mentioned in the context regarding the strategic direction of AI products and services, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, competencies, core capabilities"}}, "7c9f18c2-b95b-477d-8542-326e7bd34e35": {"node_ids": ["c1c9c303-59fa-44c5-afa7-376c85fd6ac4"], "metadata": {"page_label": "18", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**What are the four key subelements that substantiate the AI value proposition within the AISDM framework?** \n\nThis question is tailored to the specific details mentioned in the context regarding the AI value proposition and its components, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI value proposition, AISDM framework, strategic road map"}}, "92658d95-aabb-46ae-b88e-1fa3a6ec610e": {"node_ids": ["c232356d-a5ee-4a78-88a3-db2c8ece4e31"], "metadata": {"page_label": "19", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components that an organization must establish to effectively support the development and implementation of AI products or services, according to the AI value proposition framework?\n\nThis question is tailored to the specific details mentioned in the text regarding the necessary elements for an AI organization, such as governance structure, access to AI technologies, and the importance of culture, which may not be easily found in other sources.", "excerpt_keywords": "Keywords: AI governance, implementation opportunities, organizational culture"}}, "e934aa81-45df-4247-90b8-cc99ad45a96d": {"node_ids": ["e1e93e00-8bb5-433a-bdbc-01b9a964aabc"], "metadata": {"page_label": "20", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** How does organizational culture influence the successful integration of AI capabilities within an organization, according to the insights from Ransbotham et al. and Westerman et al.?\n\nThis question is tailored to the unique insights presented in the text regarding the interplay between organizational culture and AI deployment, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: organizational culture, AI integration, digital transformation"}}, "06ed9264-dbf3-4a25-afba-7f28871bce76": {"node_ids": ["547b14d1-0832-4900-929c-c7b4bc9de986"], "metadata": {"page_label": "21", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**Question:** What are the seven elements of an AI strategic road map as outlined in the AI Strategy and Road Map document?\n\nThis question is unlikely to be answered elsewhere as it specifically pertains to the detailed framework presented in the document, which includes unique elements related to AI strategy formulation.", "excerpt_keywords": "Keywords: AI strategy, road map, implementation blueprint"}}, "154d86ae-8f60-479d-b7b3-cef1ee9a4fac": {"node_ids": ["ace7ed36-0a06-4fc5-bdd4-721a5292c5ac"], "metadata": {"page_label": "22", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**Question:** What are the key components of the AI value proposition related to stroke detection and intervention as presented by the Misty robot team?\n\nThis question is tailored to extract specific details about the AI value proposition mentioned in the context, particularly focusing on the application of the Misty robot in healthcare settings, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, stroke detection, Misty robot"}}, "48ea77df-6459-4f8f-8c1e-6ef0469dbf63": {"node_ids": ["86d66382-2e34-4389-b2a0-d274dc041a93"], "metadata": {"page_label": "23", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a specific question that can be answered:\n\n**Question:** What are the key elements and considerations involved in formulating an AI strategic road map, particularly in relation to understanding business needs and stakeholder pain points?\n\nThis question is tailored to the unique insights presented in the context, particularly regarding the mapping of AI capabilities to business needs, the importance of customer focus, and the strategic implementation framework discussed in the document.", "excerpt_keywords": "Keywords: AI strategy, business needs, stakeholder analysis"}}, "31a4eea4-647b-45af-b42d-bcb95895308a": {"node_ids": ["cf334660-a1fe-41b6-909d-f1c599236c43"], "metadata": {"page_label": "24", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context from Chapter 9 of the document on AI Strategy and Road Map, here is a question that can be specifically answered by the content:\n\n**Question:** What key questions should an organization consider when assessing the business needs for an AI product or service, according to the Heilmeier Criteria?\n\nThis question is tailored to extract specific insights from the text regarding the evaluation process for AI capabilities, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, Heilmeier Criteria, business assessment"}}, "e693d724-742a-41d2-9f3e-9d19f1dfff7e": {"node_ids": ["25d3fb7b-1564-4156-acd8-f90dd3c80ef2"], "metadata": {"page_label": "25", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**What are the key performance metrics and milestones for the development of the Misty robot as an early stroke detection solution?**\n\nThis question is tailored to extract specific details about the performance metrics and milestones outlined in the context, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: Misty robot, stroke detection, performance metrics"}}, "9f6436d8-2949-473a-a017-e076e259b68c": {"node_ids": ["f133a29a-f522-476e-9187-92cfd596d603"], "metadata": {"page_label": "26", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "What are the specific risk categories identified in the AI strategic road map, and how do they relate to the successful implementation of AI system architecture?", "excerpt_keywords": "Keywords: AI strategy, risk management, system architecture"}}, "290fed83-3e4b-4890-ac95-a1ed4cf30a54": {"node_ids": ["dc958819-3b5a-48b5-8cd7-b959c45838ec"], "metadata": {"page_label": "27", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered by the information given:\n\n**Question:** What are the identified strengths and weaknesses of the Misty robot as outlined in the SWOT analysis, and how do these factors relate to its potential use in AI detection of strokes?\n\nThis question is tailored to extract specific insights from the SWOT analysis presented in the context, focusing on the internal factors (strengths and weaknesses) that could impact the robot's effectiveness and acceptance in a critical application like stroke detection.", "excerpt_keywords": "Keywords: AI strategy, Misty robot, SWOT analysis"}}, "5878a25f-584f-4051-a575-549bf0b86b57": {"node_ids": ["ecec0543-5fc7-46d3-bb37-8aa2361e51f1"], "metadata": {"page_label": "28", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the different risk categories and their associated levels as outlined in the AI Strategy and Road Map document?\n\nThis question is tailored to extract specific information from the context regarding the risk management framework presented in the document, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: risk management, AI strategy, programmatic risk"}}, "c4035c6b-b395-4a5d-a257-28169e5c2dba": {"node_ids": ["b7bd94dc-a0f5-427f-8d93-8611a50d2885"], "metadata": {"page_label": "29", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are the key components of an AI strategic road map, and how can they be utilized to align AI capabilities with business needs?\n\nThis question is tailored to extract insights from the detailed discussion on the elements of an AI strategic road map, including the importance of defining goals, actions, timelines, and performance metrics, as well as the relationship between existing capabilities and stakeholder business needs.", "excerpt_keywords": "Keywords: AI strategic road map, business needs, performance metrics"}}, "06064cf5-c1b3-4c8f-9417-a59e4944783c": {"node_ids": ["ef3693ea-3100-4bc6-b82f-0f86ce9de21a"], "metadata": {"page_label": "30", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context from Chapter 9 of the document \"AI Strategy and Road Map,\" here is a specific question that can be answered using the information:\n\n**Question:** What are the key quadrants in the AI strategic road map that organizations should focus on to innovate and maximize revenue from AI capabilities?\n\nThis question is tailored to extract insights specifically from the discussion of the quadrants mentioned in the text, which outlines the stages of AI product maturity and strategic focus areas for organizations.", "excerpt_keywords": "Keywords: AI strategy, innovation, revenue generation"}}, "9b3972ca-09f4-4d4f-86b4-0ec647712b26": {"node_ids": ["f7e3d34f-b990-447d-b3d3-60cf67485f46"], "metadata": {"page_label": "31", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What role does the AISDM framework play in the strategic planning and execution of AI products or services within an organization?\n\nThis question is tailored to the specific details mentioned in the context regarding the AISDM framework and its importance in encapsulating the focus, justification, and plans for AI development, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AISDM framework, AI strategy, execution"}}, "3b317ca6-400d-4591-9d0e-822c35f69c5a": {"node_ids": ["37745ce7-9c77-49d0-8f92-098ebdbaa7cd"], "metadata": {"page_label": "32", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**What is the AISDM framework and how does it contribute to the development and deployment of AI capabilities within an organization?**\n\nThis question is tailored to extract specific insights from the text regarding the AISDM framework, its purpose, and its role in the strategic planning and execution of AI initiatives, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AISDM framework, AI strategy, deployment"}}, "0f8c237e-bf8f-4ab6-86e2-19db5ceecb06": {"node_ids": ["2accee55-8255-482d-b0e7-8ac2f84c3ef1"], "metadata": {"page_label": "33", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**What are the key components that inform the AI value proposition within the AISDM framework?**\n\nThis question is tailored to extract specific information from the context regarding the formulation of the AI value proposition, which includes AI implementation opportunities, leadership and talent, AI governance, and organizational culture. This level of detail is unlikely to be found in other sources without similar context.", "excerpt_keywords": "Keywords: AI strategy, AISDM framework, value proposition"}}, "a30dd57f-6ce5-40de-b5bf-b4fece780db6": {"node_ids": ["bf73af7e-5d71-4dae-877b-5bbce6545208"], "metadata": {"page_label": "34", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context regarding the AI strategic road map, here is a question that can be specifically answered by the information given:\n\n**Question:** What are the seven key elements that should be included in an AI strategic road map to ensure alignment with business needs and successful implementation?\n\nThis question is tailored to extract specific details from the text regarding the components of an AI strategic road map, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, road map, business alignment"}}, "93479d00-f312-4664-9447-8c3edaa04eb1": {"node_ids": ["f442eb02-3d61-4e10-b1bc-f33a09510a7d"], "metadata": {"page_label": "35", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What is the significance of performance metrics in the development of an AI strategic road map, and how do they contribute to identifying critical gaps?\n\nThis question is tailored to extract specific insights from the text regarding the role of performance metrics in the AI strategic planning process, which may not be easily found in other sources.", "excerpt_keywords": "Keywords: AI strategy, performance metrics, critical gaps"}}, "a5fef0e9-45fc-4348-af99-35dff9c2215b": {"node_ids": ["22cbce8f-86f4-4600-9d75-7f56f4e43937"], "metadata": {"page_label": "36", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context from the document \"AI Strategy and Road Map,\" here is a question that can be specifically answered using the information given:\n\n**Question:** What are the seven elements of an AI strategic road map as outlined in the document, and why are they essential for guiding an organization's AI initiatives?\n\nThis question is tailored to extract specific information that is likely detailed in the document but may not be readily available in other sources, focusing on the unique framework for AI strategy development presented in the text.", "excerpt_keywords": "Keywords: AI strategy, strategic road map, organizational initiatives"}}, "7491d6a1-b12e-42fb-a7a9-fbebde3328e6": {"node_ids": ["6fb3fdc5-d3d8-413c-b716-a9e2d4bed1e8"], "metadata": {"page_label": "37", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be answered specifically from the information given:\n\n**Question:** What are some recommended performance metrics for assessing compliance with the RAI principles (FASTEPS) as discussed in Chapter 8 of the document?\n\nThis question is tailored to the specific content of the document, particularly focusing on the strategic development road map and the RAI principles mentioned, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, RAI principles, performance metrics"}}, "b31f1f51-7b97-44e6-989b-9380c0909687": {"node_ids": ["e19c7135-6eec-482e-868c-08ba0bbb9765"], "metadata": {"page_label": "38", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be answered specifically by the information given:\n\n**Question:** What are some key references and resources cited in the AI Strategy and Road Map document that discuss national AI strategies and competitive forces shaping strategy?\n\nThis question is tailored to extract specific information from the citations listed in the context, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: AI strategy, national strategies, competitive forces"}}, "593c8e21-1e53-4a32-be0a-116939dbae2b": {"node_ids": ["88d9554b-1e7f-4667-bc5f-89afccf20dac"], "metadata": {"page_label": "39", "file_name": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_path": "AI_Strategy_and_Road_Map_Artificial_Intelligence.pdf", "file_type": "application/pdf", "file_size": 1954829, "creation_date": "2025-04-30", "last_modified_date": "2025-03-16", "questions_this_excerpt_can_answer": "Based on the provided context, here is a question that can be specifically answered:\n\n**Question:** What are some key references that discuss the cultural implications of artificial intelligence in organizations, as mentioned in the AI Strategy and Road Map document?\n\nThis question is tailored to extract specific information from the references listed in the context, which may not be readily available in other sources.", "excerpt_keywords": "Keywords: artificial intelligence, organizational culture, digital transformation"}}}} \ No newline at end of file