# Best books on AI transformation for executives in 2026

Best-of list · By Nolli research, The Nolli team · Published 2026-10-18 · Updated 2026-10-18 · Prices and features checked 2026-10-16

Canonical page: https://withnolli.com/blog/best-books-on-ai-transformation-for-executives-2026

**Short answer.** Read Rewired, second edition (April 2026), if you own the program, and Co-Intelligence if you have not used the tools yourself. Read Human + Machine for how work and roles change. Skip AI-First Leader unless you want a primer. We have not read any of these cover to cover. This list comes from publisher pages and tables of contents, checked October 16, 2026.

## Quick picks

- **Read first: Rewired, 2nd edition.** McKinsey’s manual for running the program, rewritten in April 2026. It is 624 pages, so read the part that matches your weakest capability.
- **Read for the org design: Human + Machine, Updated and Expanded.** Starts from processes and roles, with six named hybrid human and machine jobs. The 2024 update adds one chapter on generative AI.
- **Read if you have not used the tools: Co-Intelligence.** At 256 pages, the shortest book here that is already in print. It teaches how a person works with AI, not how a company changes.
- **Skip unless: AI-First Leader.** Four of its eleven chapters are primers on AI, machine learning and generative AI. Skip it if you already use these tools every week.

## Key takeaways

1. Four of the nine books were published between 2020 and 2024, before agents, so read them for the argument and not for the tooling advice.
2. Only one title is both a step-by-step manual and rewritten in 2026: Rewired, second edition, at 624 pages.
3. Publisher pages say little about measuring results: three of the nine give measurement its own chapter, section or scorecard.

Most books on AI for executives were written before an executive could hand a task to an agent. Four of the nine below are dated 2020 to 2024. Five are dated 2026, and one of those is not in print until November 3.

We have not read any of them cover to cover. What we read on October 16, 2026: the publisher’s page for each book, the table of contents where one is public, the author’s own page where there is one, and one library record. Everything we say about what a book contains comes from those pages. Everything we say about whether you should read it is opinion, and we rest it on things you can check: the year, the length, who the authors are and what their employers sell, and whether the book is a framework or a set of cases.

We also have a yardstick, and you should know it. We think an AI-native company redesigns its work around AI and keeps what works as shared skills, SOPs and evals. Our guide lays it out. It is our view, so discount it.

> **How we chose.** We started from the titles our searches turned up and kept a book only if a publisher, a bookstore or a library page confirmed its author, title, publisher and year. A book we could not confirm is out. The order below is a reading order, not a quality score: first the book we would hand an executive who has to run a program, then shorter ones that change how you think, then the older frameworks, then the 2026 titles from newer authors, then the one still in pre-order. We did not check sales or reviews. Where a page shows no table of contents, we say so.

## When each one was written

**Publication dates, from the publisher and bookstore pages**

- **Jan 7, 2020, Competing in the Age of AI.** Iansiti and Lakhani, Harvard Business Review Press. The subtitle says “algorithms and networks”, not language models.
- **Nov 15, 2022, Power and Prediction.** Agrawal, Gans and Goldfarb, Harvard Business Review Press. Mollick’s publisher page dates the arrival of ChatGPT to the same month.
- **Jun 2023, Rewired, first edition.** Lamarre, Smaje and Zemmel, Wiley, 400 pages. The title already said “digital and AI”.
- **Apr 2, 2024, Co-Intelligence.** Mollick, Penguin Random House, 256 pages.
- **Sep 10, 2024, Human + Machine, updated and expanded.** Daugherty and Wilson, Harvard Business Review Press. The page names one new chapter, on generative AI.
- **Apr 2026, Rewired, 2nd edition, and The AI Transformation Playbook.** Wiley’s second edition runs to 624 pages. Jain’s playbook is listed on April 21, 2026 and is independently published.
- **2026, AI-First Leader and Return on Intelligence.** Both on Routledge, both with a 2026 copyright on the publisher page. The pages give no month.
- **Nov 3, 2026, AI Native.** Kai-Fu Lee. Penguin Random House lists the hardcover for this date and the ebook for September 15, 2026.

The year is only half of it; read what the pages say. Four of the nine descriptions name AI agents as a topic: Rewired’s second edition, AI-First Leader, Return on Intelligence and AI Native. Jain’s page names agents only to say his book is not about them. The four older descriptions never mention them.

That is a reason to read the 2020 to 2024 titles for their argument and skip them for advice on tools. Power and Prediction’s argument is that AI makes prediction cheap and moves the value to judgment and to the system around it. That would hold if the models were swapped tomorrow. Co-Intelligence’s advice on working with a chatbot is the part most likely to have aged. We cannot say how much without reading it, so take that as a guess.

## The nine, in the order we would read them

### 1. Rewired, 2nd edition

Best for the executive who owns the program. By Eric Lamarre, Kate Smaje and Robert Levin, with Alex Singla and Alexander Sukharevsky, all from McKinsey. Wiley, April 2026, 624 pages. It is a manual built on six capabilities: a roadmap, a talent bench, an operating model, a distributed technology environment, data, and adoption and scaling. The first edition came out in June 2023 at 400 pages.

Strengths: The only title here that is both a step-by-step manual and rewritten this year. Wiley says the new edition adds AI agents in software development, human-AI collaboration models and how to scale AI safely.; Named cases: Toyota, DBS Bank, Freeport-McMoRan and LATAM Airlines get deep dives, out of more than 30 examples and 100 exhibits..

Limits: 624 pages. Nobody needs all of it. Pick the chapters for your weakest capability.; The authors work for a consulting firm that sells this work, and the cases are large, established companies. A 200-person company will have to shrink the advice. Wiley’s page names no failed transformation..

Pricing: $45.00 hardcover on Wiley, listed out of stock when we read the page

Vendor page: https://www.wiley.com/en-us/rewired-mckinsey%27s-playbook-on-how-leading-companies-win-with-technology-and-ai-2nd-edition-p-9781394381906

### 2. Co-Intelligence: Living and Working with AI

Best for the executive who has not used the tools. By Ethan Mollick, a Wharton professor who writes the One Useful Thing newsletter. Penguin Random House, April 2, 2024, 256 pages. It argues for treating AI as a co-worker, a co-teacher and a coach, with dozens of examples of AI at work, and it covers business and education.

Strengths: Short. At 256 pages it is the lightest book on the list that is already in print.; Hands-on: the Financial Times review quoted on the publisher page says Mollick runs his own experiments on what the tools can do..

Limits: It is about how a person works with AI. The page says nothing on agents, operating models or measurement, so it will not tell you how to restructure a department.; April 2024, before the agent tools of 2026..

Pricing: $30.00 hardcover on the Penguin Random House page

Vendor page: https://www.penguinrandomhouse.com/books/741805/co-intelligence-by-ethan-mollick/

### 3. Human + Machine, Updated and Expanded: Reimagining Work in the Age of AI

Best for redesigning work and roles. By Paul Daugherty and H. James Wilson, described by the publisher as Accenture technology leaders. Harvard Business Review Press, September 10, 2024, 336 pages. Its claim is that AI changes every business process, and that people and machines working closely makes processes fluid enough to be reimagined. It rests on research with 1,500 organizations, names six new hybrid human and machine roles, and includes a leader’s guide of five principles.

Strengths: It starts from the process and the role, which is where we think the work is.; The biggest sample any page here states: 1,500 organizations. Competing in the Age of AI says “hundreds of firms”..

Limits: The page names one new chapter, on generative AI. It does not mention agents.; The authors are from Accenture, a consultancy..

Pricing: $32.00 at Harvard Book Store

Vendor page: https://store.hbr.org/product/human-machine-updated-and-expanded-reimagining-work-in-the-age-of-ai/10724

### 4. Competing in the Age of AI

Best for the CEO who wants the firm-level argument. By Marco Iansiti and Karim Lakhani, Harvard Business School faculty. Harvard Business Review Press, January 7, 2020, 288 pages. It argues that firms built on data, analytics and AI shed old limits on scale, scope and learning, and gives a framework for rethinking the operating model. Its examples run from Airbnb and Ant Financial to Microsoft and Amazon, drawn from research in hundreds of firms.

Strengths: Its subject is the operating model, which is the part that has to change whichever model you use.; A research base, not only anecdotes: the page says hundreds of firms across many sectors..

Limits: January 2020, nearly three years before the month ChatGPT arrived.; The examples are the largest digital firms. That is a long way from a company of 500 people..

Pricing: $35.00 at Harvard Book Store

Vendor page: https://www.hbs.edu/faculty/Pages/item.aspx?num=56633

### 5. Power and Prediction: The Disruptive Economics of Artificial Intelligence

Best for the finance or strategy lead who wants one idea. By Ajay Agrawal, Joshua Gans and Avi Goldfarb, who call themselves economists. Harvard Business Review Press, November 15, 2022. The unit of analysis is the decision, split into prediction and judgment, with AI moving prediction from people to machines. The authors say we are in “the Between Times”: after the technology has proved itself and before it has spread through whole systems. A library record lists 17 chapters in six parts.

Strengths: One idea you can use in a meeting: split a decision into prediction and judgment, then ask what changes when prediction is cheap.; Its last two chapters, “Designing Reliable Systems” and “The Blank Slate”, point at redesign, which is the part we care about..

Limits: Published the month ChatGPT arrived, so it covers the prediction machine, not the language model or the agent.; It is economics, not a manual. The 17 chapter titles include nothing on rollout, training or measurement..

Pricing: $32.00 at the Harvard Business Review store

Vendor page: https://store.hbr.org/product/power-and-prediction-the-disruptive-economics-of-artificial-intelligence/10580

### 6. The AI Transformation Playbook: From Pilots to Production

Best for the COO or CFO whose pilots keep stalling. By Mehul Jain, who describes himself as an AI practitioner and founder. Independently published, April 21, 2026, 236 pages. It argues that stalled programs fail on program design (funding, operating model, talent, how the work is redesigned, vendor deals) and not on pilot quality. Its page says plainly that it has no code and no vendor comparison. It is the second book in a series; Book One, Enterprise AI Agents, covers the agents.

Strengths: Honest about its edges: the author’s page lists what the book is not.; Written so a CEO and a CTO can read the same chapter and agree on what to do, per the author..

Limits: Independently published. We found no table of contents and no named case studies, so you cannot preview the method.; The pages we read cite no research sample. It is one practitioner’s view..

Pricing: $29.99 on Amazon

Vendor page: https://www.jainmehul.com/books/ai-transformation-playbook

### 7. AI-First Leader: A Practical Guide to Organizational AI Leadership

Best for a leader who needs the technology explained first. By Bhavesh Mehta and Mahesh Kumar, product and engineering executives whose past employers include Uber, Cisco, VMware and Veritas. Routledge (Chapman & Hall), 2026. Eleven chapters in three sections: four on what leaders must know about AI, three on deploying and scaling it (including AI agents, infrastructure and security), and four on ROI, leading the transformation and responsible AI. Its case study is NovaBridge Health, which the page itself calls fictional.

Strengths: The table of contents is public, so you can check it against your own gaps. It includes AI agents (chapter 6) and ROI frameworks (chapter 9).; Technically specific: data governance, model evaluation and prompt engineering are named on the page..

Limits: The case study is made up, so there is no real company to check it against.; Section 1 is four chapters of essentials, including machine learning and generative AI. An executive who already uses these tools can skip it..

Pricing: Not shown on the Routledge page we read

Vendor page: https://www.routledge.com/AI-First-Leader-A-Practical-Guide-to-Organizational-AI-Leadership/Mehta-Kumar/p/book/9781041098232

### 8. Return on Intelligence: A Strategic Enterprise Playbook for Scalable AI Agents

Best for the leader who has to sell the program to a board. By Kristin Milchanowski, chief AI and data officer at BMO Financial Group. Routledge, 2026, 196 pages. Nine chapters in three parts: strategy, design and economic justification; leadership, culture and organizational change; governance, trust and adoption. The page promises 43 governing principles and two metrics for how well an institution has built AI into its workflows and governance.

Strengths: Written by an operator who runs AI and data at a bank, and the contents are public.; Puts the economic case (chapter 3, on return on investment) ahead of culture, which matches how boards read..

Limits: We could not see the two metrics or any of the 43 principles from the pages we read.; The description leans on big claims, such as intelligence as infrastructure and moving from pilots to permanence. It shows no named case and no sample of the method. Read a sample chapter first..

Pricing: Not shown on the Routledge page we read

Vendor page: https://www.routledge.com/Return-on-Intelligence-A-Strategic-Enterprise-Playbook-for-Scalable-AI-Agents/Milchanowski/p/book/9781041262985

### 9. AI Native: The Mandate to Transform Your Company

Best to wait on until the contents are public. By Kai-Fu Lee, who the publisher says was an executive at Apple, Microsoft and Google and is now a CEO, and who wrote AI Superpowers and AI 2041. Penguin Random House lists the hardcover, 208 pages, for November 3, 2026, and the ebook for September 15, 2026. The blurb promises a roadmap for restructuring teams around agentic AI and for using AI on “the hidden trove of knowledge inside companies”. We have only the blurb and endorsements.

Strengths: Written by someone who runs a company rather than advises one.; The only title here with AI-native in its name, and the only blurb that talks about the knowledge inside a company as an input..

Limits: No table of contents on the pages we read. We cannot say what is in it.; The blurb says top agents now do a human expert’s workday in less time than a coffee break, and gives no source or test on the page. Wait for the chapter that backs it..

Pricing: $34.00 hardcover, pre-order, on the Penguin Random House page

Vendor page: https://www.penguinrandomhouse.com/books/854461/ai-native-by-kai-fu-lee/

> **If you only read two** Spend a week with the tools first. Then read the Rewired chapter for the capability your company is weakest at. The nine books run to more than 2,600 pages by the publishers’ own counts, and no executive needs that.

## What each publisher page says it covers

**Topics shown on each book’s publisher page or table of contents** (none, partly or fully)

| | Rewired 2e | Competing | Power & Prediction | Human + Machine | Co-Intelligence | AI-First Leader | Return on Intelligence | Jain Playbook | AI Native |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Strategy: where to compete and what to bet on | fully | fully | fully | partly | partly | fully | fully | fully | fully |
| Operating model and org design | fully | fully | partly | fully | none | partly | partly | fully | fully |
| Named case studies | fully | fully | partly | partly | partly | partly | none | partly | none |
| Technical depth | fully | partly | none | none | partly | fully | partly | none | none |
| People and change | fully | partly | none | fully | partly | partly | fully | fully | partly |
| Measurement and ROI | partly | none | none | none | none | fully | fully | fully | none |
| AI agents | partly | none | none | none | none | fully | fully | none | fully |

Our reading of each publisher’s description and table of contents, read on October 16, 2026. Full: the page says it plainly. Half: it says part of it, or mentions it in passing. Empty: the page does not say, which is not the same as the book not covering it. A book can do more than its page admits. Jain’s page names agents only to rule them out, so it scores empty there. Only Rewired and Competing name companies on the page. The half marks in the case row are examples without names, or one fictional case.

Read down the columns and no book is full on everything. Rewired comes closest, which is what 624 pages buys. Read across the measurement row and it thins out. Three pages give measurement a chapter, a section or a scorecard: AI-First Leader (chapter 9, ROI frameworks), Return on Intelligence (chapter 3, plus its two metrics) and Jain’s board-level scorecard. If you will be asked to prove the program worked, the books will help less than you hope. We wrote how to measure AI impact for that gap.

## Who wrote it, and what they sell

Author descriptions are the publishers’ own or the author’s own page. Page counts are the publisher’s or bookstore’s.

| Book | What the authors do, per the page | Kind of book | Pages |
| --- | --- | --- | --- |
| Rewired, 2nd edition | Five McKinsey leaders; Lamarre also lectures at MIT | Manual, 30+ cases | 624 |
| Competing in the Age of AI | Two Harvard Business School professors | Framework, research in hundreds of firms | 288 |
| Power and Prediction | Three economists | Framework, one idea | 288 (HBR store) or 268 (library record) |
| Human + Machine, updated | Two Accenture technology leaders | Framework from a study of 1,500 organizations | 336 |
| Co-Intelligence | A Wharton professor and newsletter writer | Guide to working with AI | 256 |
| AI-First Leader | Two product and engineering executives | Primer plus a fictional case | 232 or 266 (Routledge lists both) |
| Return on Intelligence | Chief AI and data officer at BMO Financial Group | Principles and two metrics | 196 |
| The AI Transformation Playbook | An AI practitioner and founder | Principles, no cases shown | 236 |
| AI Native | A CEO and former Apple, Microsoft and Google executive | Roadmap (blurb only) | 208 |

Two of the nine come from consulting firms that sell the work the book describes, McKinsey and Accenture. That does not make them wrong. It does mean the cases were chosen to show the method works, and we saw no failed one named on Wiley’s page for Rewired. Ask who pays the author’s salary before you copy the roadmap.

## Practical against recent

**How practical each book looks, and how recent it is** (x: How recent, 0 to 100; y: How practical, 0 to 100; corners: top-left Practical, older, top-right Practical, recent, bottom-left Conceptual, older, bottom-right Conceptual, recent)

- Rewired 2e: x 88, y 92
- Human + Machine: x 58, y 58
- Co-Intelligence: x 52, y 68
- Competing: x 6, y 42
- Power & Prediction: x 22, y 26
- AI-First Leader: x 78, y 78
- Jain Playbook: x 90, y 62
- Return on Intelligence: x 84, y 46
- AI Native: x 98, y 52

Our reading from publisher pages, not a review. Recent runs from January 2020 to the pre-order date of November 2026. Practical means the page shows checklists, diagnostics, a public table of contents or named steps. AI Native sits at the midpoint on practicality because we have only a blurb.

The top right holds one book, Rewired. That is the case for starting there, and also a reason to be careful: it is the longest, and it is written by the people who sell the work. The bottom right is where we would be wary. Those books are new and abstract on the evidence of their pages. That is not a verdict. It is what we can see without opening them.

## Pick one

- **Read Rewired if** you own the program and have a team and a budget. Start with the capability you are weakest at.
- **Read Co-Intelligence if** you have not spent a week with the tools. You cannot judge a transformation you have not used.
- **Read Human + Machine if** you are redesigning jobs and processes and want names for the new roles.
- **Read Competing in the Age of AI if** you want the operating-model argument and can translate examples from giants down to your size.
- **Read Power and Prediction if** you must decide what to automate and want a test: is this a prediction, and who holds the judgment?
- **Read the Jain playbook if** pilots work and nothing reaches production, and you can accept a book you cannot preview.
- **Skip AI-First Leader unless** you want one book that explains machine learning, generative AI and agents to a leader, and you do not mind a fictional case.
- **Skip Return on Intelligence unless** the principles survive a sample chapter. Check before you buy.
- **Wait on AI Native until** a table of contents is public and someone who has read it says what the roadmap is.

## What we could not find in any of them

Here is the gap we notice, and it comes with our bias. The nine pages describe strategy, operating models and ROI. We found none that describes how to learn, from the work itself, which of your company’s tasks belong to AI. Rewired’s roadmap that “targets real value” comes closest. The rest assume you already know where to point the effort.

That may only be because we read blurbs, and a chapter might do it. If you want to see how we think about it, how to find where AI belongs is our free guide. And someone has to own the job once the books are read. We wrote up what a Head of AI Enablement does from ten job postings.

## Free reading from us, and what we sell

Nolli sells a product, and these books are not about it. If you want free reading with the sources shown, our /learn library has guides on what AI-native means and how to find where AI belongs. We wrote them, so give them the doubt you would give any vendor’s reading list.

## Questions people ask

**Which book should an executive read first on AI transformation?**

If you own the program, Rewired, second edition (Wiley, April 2026). If you have not yet used the tools yourself, Co-Intelligence by Ethan Mollick first, at 256 pages. We chose from publisher pages and have not read either cover to cover.

**Are the older AI books still worth reading?**

For the argument, yes. Competing in the Age of AI (2020) and Power and Prediction (2022) came out before ChatGPT, and their descriptions never mention agents. Their frameworks on operating models and decisions do not depend on a specific model. Skip them for advice on tools.

**Is there a book on AI agents for executives?**

Four of the nine publisher pages name agents as a topic: Rewired, second edition, AI-First Leader (chapter 6), Return on Intelligence (in its subtitle) and AI Native, which is still in pre-order. We have not read any of them, so we cannot say which handles agents best.

**Have you read all of these books?**

No. We read each publisher’s page and, where public, the table of contents, plus the author’s own page for two of them and a library record for one. We say what a page says and mark our opinions as opinions.

**What is the newest book on the list?**

AI Native by Kai-Fu Lee. Penguin Random House lists the ebook for September 15, 2026 and the 208-page hardcover for November 3, 2026.

## Sources

- Eric Lamarre, Kate Smaje, Robert Levin, Alex Singla and Alexander Sukharevsky. "Rewired: McKinsey’s Playbook on How Leading Companies Win with Technology and AI, 2nd Edition." Wiley, April 2026; accessed October 16, 2026. https://www.wiley.com/en-us/rewired-mckinsey%27s-playbook-on-how-leading-companies-win-with-technology-and-ai-2nd-edition-p-9781394381906
- Eric Lamarre, Kate Smaje and Rodney Zemmel. "Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI." Wiley, June 2023; accessed October 16, 2026. https://www.wiley.com/en-us/Rewired%3A+The+McKinsey+Guide+to+Outcompeting+in+the+Age+of+Digital+and+AI-p-9781394207121
- Ethan Mollick. "Co-Intelligence: Living and Working with AI." Penguin Random House, April 2, 2024; accessed October 16, 2026. https://www.penguinrandomhouse.com/books/741805/co-intelligence-by-ethan-mollick/
- Ajay Agrawal, Joshua Gans and Avi Goldfarb. "Power and Prediction: The Disruptive Economics of Artificial Intelligence." Harvard Business Review store, November 15, 2022; accessed October 16, 2026. https://store.hbr.org/product/power-and-prediction-the-disruptive-economics-of-artificial-intelligence/10580
- Avi Goldfarb. "Power and Prediction." Author’s website, accessed October 16, 2026. https://www.avigoldfarb.com/powerandprediction
- "Power and Prediction: the disruptive economics of artificial intelligence (catalog record with table of contents)." Wyoming Libraries, accessed October 16, 2026. https://wyld.wyldcatalog.org/Record/a2508971
- "Power and Prediction: The Disruptive Economics of Artificial Intelligence." Harvard Book Store, accessed October 16, 2026. https://www.harvard.com/book/9781647824198
- Marco Iansiti and Karim R. Lakhani. "Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World." Harvard Business School Faculty & Research, 2020; accessed October 16, 2026. https://www.hbs.edu/faculty/Pages/item.aspx?num=56633
- Marco Iansiti and Karim R. Lakhani. "Competing in the Age of AI." Harvard Book Store, January 7, 2020; accessed October 16, 2026. https://www.harvard.com/book/9781633697621
- Paul R. Daugherty and H. James Wilson. "Human + Machine, Updated and Expanded: Reimagining Work in the Age of AI." Harvard Business Review store, September 10, 2024; accessed October 16, 2026. https://store.hbr.org/product/human-machine-updated-and-expanded-reimagining-work-in-the-age-of-ai/10724
- Paul R. Daugherty and H. James Wilson. "Human + Machine, Updated and Expanded: Reimagining Work in the Age of AI." Harvard Book Store, September 10, 2024; accessed October 16, 2026. https://www.harvard.com/book/9781647827205
- Bhavesh Mehta and Mahesh Kumar. "AI-First Leader: A Practical Guide to Organizational AI Leadership." Routledge, 2026; accessed October 16, 2026. https://www.routledge.com/AI-First-Leader-A-Practical-Guide-to-Organizational-AI-Leadership/Mehta-Kumar/p/book/9781041098232
- Kristin L. Milchanowski. "Return on Intelligence: A Strategic Enterprise Playbook for Scalable AI Agents." Routledge, 2026; accessed October 16, 2026. https://www.routledge.com/Return-on-Intelligence-A-Strategic-Enterprise-Playbook-for-Scalable-AI-Agents/Milchanowski/p/book/9781041262985
- Mehul Jain. "The AI Transformation Playbook: From Pilots to Production." Author’s website, 2026; accessed October 16, 2026. https://www.jainmehul.com/books/ai-transformation-playbook
- Mehul Jain. "AI Transformation Playbook: From Pilots to Production (The AI Black Book)." Amazon (independently published), April 21, 2026; accessed October 16, 2026. https://www.amazon.com/AI-Transformation-Playbook-Pilots-Production/dp/B0GY3RD65J
- Kai-Fu Lee. "AI Native: The Mandate to Transform Your Company." Penguin Random House, hardcover November 3, 2026; accessed October 16, 2026. https://www.penguinrandomhouse.com/books/854461/ai-native-by-kai-fu-lee/