In the summer of 2023, we created a Very Best Books on AI List.
It was right after ChatGPT launched and interest in AI was growing fast. There was a lot to learn and understand. Three years later, there’s still a lot to learn with new AI tools, agents and many challenges around the technology.
So, we wanted to take another look at what books are out there to help. Are books about AI still worth the read with AI changing so quickly? We think so.
With this list, we've tried to balance timely releases with books that teach frameworks and principles that remain relevant and important, especially from a historical or theoretical perspective. Plus we’ve added some novel choices: A book created by an AI agent and another created by our own Marketing AI Institute community.
Calling them the very best books is certainly subjective, but we have some clout behind it. We took recommendations from our AI community, an engaged group of marketers, AI practitioners, and business leaders, as well as our own Marketing AI Institute team that works with AI every day.
And yes, we asked ChatGPT and Claude for their recommendations, requesting they prioritize picks based on best-seller lists and favorites of AI influencers and experts. Also, a couple of these books (and their authors) were selected for our Live AI Academy Book Club.
The list is organized by topic to make it easier to find books relevant to your interests and job.
So, let’s dive in and get reading!
Authors: Rajkumar Venkatesan & Jim Lecinski
Why you should read it: This fully updated post-ChatGPT edition from two MBA marketing professors (UVA Darden and Northwestern Kellogg) gives marketing leaders an actionable five-step framework for planning and executing AI initiatives at every stage of organizational maturity. Named "best AI marketing book overall" for 2026 by Aiifi and endorsed by CMOs at Ally Financial and Mastercard, it's the rare book that is both rigorous and practical.
Key takeaway: Brands that successfully weave AI into their marketing strategies share a common set of best practices—and those practices can be learned and applied by any marketing leader, regardless of where their organization is starting from.
Authors: Paul Roetzer & Mike Kaput
Why you should read it: The foundational text from Marketing AI Institute remains one of the most widely cited books in marketing AI education. It draws on years of research and dozens of interviews with AI marketers, executives, engineers, and entrepreneurs to lay out how AI will transform the practice of marketing—and what to do about it.
Key takeaway: AI-powered marketing may never achieve the sci-fi vision of fully autonomous systems, but even a little AI can go a long way toward dramatically increasing productivity, efficiency, and performance.
[AI Academy Book Club selection.]
Author: Geoff Woods
Why you should read it: Written by a former CGO and co-author of The ONE Thing, this book gives business and marketing leaders a clear-eyed look at how to use AI to make better decisions faster. It's earned a reputation as one of the most practical books for anyone trying to integrate AI into leadership workflows. Woods kickoffed off our AI Academy Book Club.
Key takeaway: Adopting AI as a leader isn't just about the tools—it's about developing new thinking habits and decision-making frameworks.
"Geoff Woods has a great approach and sparks lots of ideas." — A member of our community
Author: Katie King (2nd edition, 2025)
Why you should read it: Named "best executive guide" for AI marketing books in 2026 by Aiifi, this book from a recognized AI advisor to boards and governments bridges the gap between strategy and execution across marketing, sales, and customer experience.
Key takeaway: AI transformation in go-to-market functions only works when marketing, sales, and CX are aligned on a shared strategy—not siloed in separate AI experiments.
Author: Greg Kihlström
Why you should read it: Bestselling author and Forbes contributor Greg Kihlström zeroes in on generative AI specifically: what it means for brand strategy, marketing operations, and CX leadership. An earlier Agile Brand Guide title was on the 2023 Marketing AI Institute list; this generative-AI-focused follow-up is the version that matters most right now.
Key takeaway: Generative AI isn't just a content tool—it's a platform shift for how brands plan, create, and optimize marketing at scale.
Authors: Philip Kotler, Hermawan Kartajaya & Iwan Setiawan
Why you should read it: The father of modern marketing applies his signature Marketing X.0 framework to the age of AI. Aiifi lists it among the top three AI marketing books for 2026. If you want to understand how AI fits into the long arc of marketing evolution, this is the book.
Key takeaway: The future of marketing isn't human or machine—it's the thoughtful integration of both, designed around a deeper understanding of the customer.
Author: Ethan Mollick
Why you should read it: A New York Times bestseller from a Wharton professor who has become one of the most-cited voices on practical AI use. Mollick cuts through both the hype and the fear to give professionals a grounded, actionable framework for thinking about AI as a collaborator rather than a threat.
Key takeaway: The people who thrive with AI won't be those who master the tools—they'll be the ones who develop a thoughtful relationship with AI and learn to work alongside it intelligently.
"Really worth the time." — A member of our community
[An AI Academy Book Club selection.]
Author: Melissa Reeve
Why you should read it: A recent Marketing AI Academy book club selection, this book makes the case for why adaptability—not any specific AI skill—is the defining competency of the AI era. Particularly relevant for practitioners who feel like they can't keep up.
Key takeaway: The goal isn't to learn every AI tool. It's to build the mental and organizational agility to keep learning as tools evolve.
Author: Kevin Roose
Why you should read it: New York Times tech columnist Kevin Roose offers nine surprisingly practical rules for staying relevant—and finding meaning—as automation reshapes work. Less doom, more pragmatism. Roose will join us at MAICON 2026 as a keynote speaker.
Key takeaway: The humans who thrive in an automated world won't be those who compete with machines—they'll be those who do the things machines still can't.
Author: Janelle Shane
Why you should read it: AI researcher Janelle Shane uses humor, analogies, and her own experiments, including genuinely terrible AI-generated ice cream flavors, to give readers a real, intuitive understanding of how AI works and where it falls apart. One of the most accessible and entertaining entries in the entire genre. This one also appeared on our 2023 list.
Key takeaway: AI isn't magic, and it isn't going to take over the world. But understanding how it actually works (and fails) is the foundation for using it well.
"I would definitely recommend this one because it does a great job explaining the fundamentals with fantastic analogies for how AI actually works and what the different terminology means!" — A member of our community
Author: Christopher Penn
Why you should read it: Well-known marketing AI practitioner and educator Christopher Penn delivers something rare: a book about generative AI that's built around principles rather than products, meaning it holds up even as the specific tools change. It's earned enthusiastic word-of-mouth in AI practitioner communities.
Key takeaway: Understanding the underlying principles of how generative AI works gives you a durable foundation that doesn't expire every six months.
"Chris Penn's book is fabulous and pretty evergreen!" — A member of our community
Author: John Munsell
Why you should read it: This book offers a structured, actionable framework for embedding AI into an organization in a way that actually sticks. Recommended by practitioners in our community who are past the "what is AI" phase and ready to focus on implementation.
Key takeaway: AI adoption fails when it's treated as a project. It succeeds when it's ingrained as an operating principle.
"INGRAIN AI offers a unique and actionable framework for AI implementation." — A member of our community
Authors: Adam Brotman & Andy Sack
Why you should read it: Co-written with a trained AI agent named "Vera," this book is an experiment as much as it is a guide—showing rather than just telling what agentic AI looks like in practice. From two former MAICON speakers who are deep in the AI practitioner trenches, it's the most forward-looking book on this list about where AI is heading.
Key takeaway: AI agents aren't a future concept—they're already being built and deployed in ways that will fundamentally change how work gets done. Understanding them now is a competitive advantage.
"I haven't read it yet, but I'm fascinated by the concept of the 'living book.'" — A member of our community
"Fascinating. The future of books." — Another member of our community
"I'd say Agents, Inc. is the most relevant to the current state of AI progression, since it dives deep into how they're actually building and using the agent in the book." — A member of our community
Authors: Adam Brotman & Andy Sack
Why you should read it: The companion volume to Agents, Inc., this book zooms out to the strategic level—how do you actually build an AI-first business? Practical, opinionated, and written by practitioners who have done it.
Key takeaway: Building an AI-first business is less about technology and more about rethinking the assumptions underneath how your business operates.
Author: Mustafa Suleyman
Why you should read it: Written by the co-founder of DeepMind and now CEO of Microsoft AI, this New York Times bestseller is one of the most credible and urgent accounts of where AI is taking us—and why the next decade matters more than most people realize. Endorsed by Bill Gates and Yuval Noah Harari.
Key takeaway: The same wave of AI and synthetic biology that could solve humanity's greatest problems could also be its most destabilizing force—and how we respond in the next few years will determine which outcome we get.
Author: Yuval Noah Harari
Why you should read it: The #1 New York Times bestseller from the author of Sapiens places AI in the broadest possible context, as the latest in a long line of information networks that have reshaped human civilization. Essential reading for anyone who wants to understand not just what AI does, but what it means.
Key takeaway: Every major information technology in history—from writing to printing to the internet—has reorganized power, institutions, and what it means to be human. AI will be no different.
Authors: Reid Hoffman & Greg Beato
Why you should read it: LinkedIn co-founder and early OpenAI board member Reid Hoffman makes an unapologetically optimistic case for AI's potential. An instant New York Times and USA Today bestseller.
Key takeaway: The risks of AI are real, but so is its potential to expand human agency and address problems that have long seemed intractable.
Note: Kirkus gave it a critical review, calling its arguments underdeveloped. Worth reading alongside a more skeptical take on AI for a complete picture.
Author: Cade Metz
Why you should read it: New York Times tech reporter Cade Metz delivers one of the most readable accounts of how AI went from a niche academic field to a world-changing technology. Essential context for understanding where we are today. This was a 2023 pick as well.
Key takeaway: Artificial intelligence didn't emerge overnight. It was built over decades by a small, stubborn group of researchers who kept going when almost no one believed in them.
Author: Karen Hao
Why you should read it: A New York Times bestseller from one of the leading AI journalists working today. Hao delivers the most comprehensive account yet of OpenAI's rise—the ambitions, the conflicts, and the consequences of building one of the most powerful AI systems in history. Hao will join us on the stage at MAICON 2026 as a keynote speaker.
Key takeaway: The story of OpenAI is the story of AI's promise and peril in miniature—a cautionary tale and an inspiration, often at the same time.
Author: Parmy Olson
Why you should read it: Winner of the 2024 FT Business Book of the Year Award, this book chronicles the race between Google's DeepMind and OpenAI and what it means for the rest of us.
Key takeaway: The AI race isn't just a business story—it's a power struggle with global stakes, playing out faster than most institutions can respond.
Author: Sebastian Mallaby
Why you should read it: Financial historian Sebastian Mallaby goes inside DeepMind to tell the story of Demis Hassabis and one of the most ambitious scientific projects in human history. A rich, deeply reported narrative for anyone who wants to understand what the pursuit of AGI actually looks like from the inside.
Key takeaway: Understanding the how of AI's development gives you a much deeper appreciation for both its potential and its limits.
"It's an interesting look inside and gave me a greater appreciation for 'how' the AI we have today was created." — A member of our community
Author: Chris Miller
Why you should read it: FT Business Book of the Year 2022. You cannot fully understand AI without understanding semiconductors—and you cannot understand semiconductors without reading this book. Miller writes the history of the global chip industry with the pacing of a thriller.
Key takeaway: The AI race is, at its core, a chip race. Whoever controls the semiconductor supply chain controls the future of AI.
"I read Chip War and now I totally get what's going on with Taiwan. The book reads like a novel. I passed it on to someone who also loved it, who then passed it on to his grandson!" — A member of our community
Author: Stuart Russell
Why you should read it: Russell co-authored the standard AI textbook used in universities around the world. In Human Compatible, he makes the case for why the way we currently build AI systems is fundamentally dangerous—and what we need to do differently.
Key takeaway: Intelligence without alignment to human values isn't just useless—it's potentially catastrophic. We need to rethink AI development from the ground up.
Author: Brian Christian
Why you should read it: One of the most thorough and accessible accounts of the core challenge in AI: getting systems to do what we actually want. Essential reading for anyone who wants to understand why AI safety is hard.
Key takeaway: Building AI that reliably does what humans intend—rather than what we literally specify—is one of the hardest unsolved problems in computer science.
Authors: Eliezer Yudkowsky & Nate Soares
Why you should read it: Yudkowsky is a foundational, and deliberately polarizing, figure in AI safety. This book makes his case in full: that building superintelligent AI without solving the alignment problem first is an existential risk. You don't have to agree to find it clarifying.
Key takeaway: The stakes of getting AI wrong may be higher than almost anyone in mainstream AI development is willing to say out loud.
"I'd go with The Coming Wave or If Anyone Builds It if you want to stir up some existential crisis vibes." — A member of our community
Authors: Arvind Narayanan & Sayash Kapoor
Why you should read it: Two Princeton researchers deliver a much-needed counterweight to AI hype, showing which AI claims are real, which are exaggerated, and how to tell the difference. A skeptic's essential companion.
Key takeaway: Not every AI claim is meaningful, and the ability to evaluate them critically is becoming one of the most valuable skills a professional can have.
Author: Kate Crawford
Why you should read it: Crawford takes a forensic look at the real-world costs of AI—environmental, political, labor. Widely assigned in AI ethics courses, it's the essential counterpoint to the AI triumphalism that dominates most coverage of the technology. A repeat recommendation from 2023.
Key takeaway: AI systems don't exist in a vacuum. Every model trained, every inference run has material consequences for workers, communities, and the planet.
Futurism & Speculation
Author: Ray Kurzweil
Why you should read it: The sequel to his influential 2005 book from one of AI's most prominent long-term thinkers, now serving as Google's Director of Engineering. Whether you agree with his predictions or not, Kurzweil's framework for thinking about technological acceleration is worth understanding.
Key takeaway: The exponential growth of AI capabilities is not slowing down—and the next decade will bring changes that make the last decade look modest.
A Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains
Author: Max Bennett
Why you should read it: Bennett traces the evolution of intelligence across 500 million years to illuminate what it actually means for machines to be "intelligent." A well-reviewed, refreshingly different angle on the AI conversation.
Key takeaway: Understanding how biological intelligence evolved gives us a richer framework for understanding what AI can—and can't—do.
We’d love to hear your recommendations, especially if you’re an author or know one who might like to participate in our AI Academy Book Club. Email bookclub@smarterx.ai to make a recommendation or learn more.