If you’re feeling overwhelmed by the pace of change, you should be. Innovation is outpacing organizations’ ability to adapt and even to absorb what’s new, what’s possible, and what’s important.
We came across an article at the start of the year that suggested that a new top leadership skill is “critical ignoring." It’s an interesting suggestion. The one thing we do know: continuous learning is a must for data and AI leaders.
Those who learn the fastest and ignore the noise will be well equipped to keep up with the latest innovations and strategies to lead their companies through this tumultuous time.
The ThoughtSpot Analytics and AI Center of Excellence team has once again culled the best-seller lists, watched LinkedIn for great book reviews, and cultivated our annual must-read list. Be sure to check out our light-hearted beach reads too!
The list is sorted alphabetically by title. If you think I overlooked a critical one, do let us know! We learn best from one another.
Tune into The Data & AI Chief podcast to hear from three of the authors on this year’s list, and check out last year's podcast guests to round out your reading list. Be sure to check out our 2025 must-read list to see what you may have missed.
Here Are Our Top 10 Books About AI in 2026:
1. The Agentic AI Bible: The Complete and Up-to-Date Guide to Design, Develop, and Scale Goal-Driven, LLM-Powered Agents that Think, Execute, and Evolve by Thomas R. Caldwell
Reviewed by: Cindi Howson
There were multiple “AI bibles” on the market, often with a particular vendor slant. This one was agnostic, and we appreciate the breadth of topics at a depth appropriate for leaders as well as engineers.
Caldwell started this book as his own collection of notes as he was building agentic systems. MCP is covered here, a topic that too few leaders are versed in, and yet a protocol that further allows agent-to-agent communication and access to unstructured data. Caldwell notes that frameworks are still evolving here.
Those who serve on AI governance boards will appreciate the content on prompt injection handling and sandboxing. We like that each chapter includes a set of practical exercises and further reading.
Get your copy here.
2. Architected Intelligence: Principles for Building AI-First Organizations and Technologies by Jacob Miller & Jeremy Mumford
Reviewed by: Jane Smith
Had enough enterprise AI hype? Me too! Luckily, Jacob Miller and Jeremy Mumford have written an incredibly grounded operational guide, and as someone who lives and breathes enterprise AI transformation, I was keen to check this out. No breathless futurism here, rather a five-component structure covering output, input, model, observability, and enablement.
Leveraging Jacob and Jeremy’s many years of real-world experience, they guide data leaders through the essentials of driving business ROI. From clarifying value drivers and avoiding integration traps to mastering context engineering and model evaluation.
It’s a book of practical rubrics and decision frameworks, always being clear about trade-offs and AI ‘real-politik’.
Meticulous and highly detailed, it's not a holiday read. In fact, I’m not sure it’s even a ‘read’ as such. Keep it on your desk to dip into when you’re working on a problem, and I think you’ll find you have an invaluable AI manual that you’ll go back to again and again - I certainly will.
Get your copy here.
3. Designing and Implementing Semantic Data Layers by Dave Wells
Reviewed by: Cindi Howson
Whether you believe semantic layers are suddenly sexy, our industry’s Rosetta Stone, or the new battleground for control, they are an essential building block for the AI era. In the absence of semantic layers, AI hallucinates.
But how does one put this into practice when there are so many different definitions by domain, and meaning is often based on tribal knowledge?
Dave Wells gives both the foundational concepts as well as operating models. He lays out five types of semantic layers - that includes the Enterprise Core Layer as well as the Consumption Layer.
He describes the consumption layer as the most volatile layer as new use cases arise. In other words, we do need to get comfortable with messiness. Here too, Dave provides an operating model for resolving these conflicts.
I look forward to seeing how companies put these concepts into practice. This book also nicely includes relatable examples to understand the differences between semantics, ontologies, and knowledge graphs.
Fun fact: Dave was my former manager and a fellow instructor when I taught for TDWI. Data and AI Chief podcast guest Olga Maydanchik put this book on my radar.
Get your copy here.
4. Designing the AI-Driven Data Foundations: A Practical Guide to the Architecture, Frameworks, and Principles Behind AI-Ready Data Platforms by Sanjeev Mohan
Reviewed by: Sonny Rivera and Cindi Howson
Sanjeev Mohan and I met years ago when he caught my attention as an industry analyst who pushes back in the room with intellectual curiosity and honesty. Those characteristics are what made me pick up this book.
It’s a framework book that’s built to last, with its foundations based on decades of learning, from modernizing data to cloud journeys, and to FinOps. The book is not prescriptive. But it does surface the trade-offs that leaders need to know.
Sanjeev’s 9 guiding principles alone are worth the read. Concepts like “build modular”, “avoid lock-in”, and "securely govern from day one” aren’t exactly new, but this book brings them into a valuable framework.
Listen to Sanjeev Mohan on The Data and AI Chief podcast here, and get your copy here.
5. Genius at Scale: How Great Leaders Drive Innovation by Professor Linda Hill
Reviewed by: Cindi Howson
I first discovered Linda’s work while tuning into a podcast with Brené Brown several years ago. She talked about the importance of culture and true transformation in ways that few leaders had at that point in time.
Linda confessed that Genius at Scale took longer to bring to market than she had originally hoped, but it’s worth the wait. This book is packed with case studies of what works and what does not in driving innovation and disrupting the status quo.
Data and AI Leaders will appreciate the types of leaders Linda focuses on ABC: Architects, Bridgers, and Catalysts. I think the ideal CDAO and Chief AI Officer is indeed a bridger, where collaboration and being an unsung hero are the unwritten rules of the job description.
Listen to Linda Hill on The Data and AI Chief podcast here, and get your copy here.
6. How Not to Use AI: 50 Contrarian Principles for the Imagination Age by Abi Awomosu
Reviewed by: Jane Smith
How Not to Use AI is Abi Awomosu’s rousing challenge to Silicon Valley’s obsession with automated extraction, essentially ‘strip mining’ everything in its path. Rather than treating AI as a glorified shortcuts that get us bland, generic outputs, she frames AI as a listening medium trained on the breadth of human experience.
Drawing on her experience as a former big-tech insider, Abi provides practical commercial frameworks, prompting rules, and enterprise case studies that show leaders how to challenge assumptions and listen deeply rather than force hasty answers.
Drawing on the wisdom of the elders, other cultures, and business success stories, she lays out a clear case for the fact that most business leaders, including AI & Data leaders, are likely only using a fraction of the life-changing potential of AI.
Get your copy here.
7. Human Edge in the AI Age: Eight Timeless Mantras for Success by Nitin Seth
Reviewed by: Cindi Howson
As AI becomes as smart as humans and, in some cases, better at problem-solving, this book poses the question of how humans can still compete. It is a book that is more mainstream, useful not only to leaders but to anyone trying to navigate this generational shift, rethinking business models and the future of work.
It takes a broad historical perspective of how humans have adapted to previous generational shifts and considers how we can best prepare for this shift.
I especially like Nitin’s POSSIBLE framework for what skills to hone and how to learn faster, with 2035 to 2040 being the age of uncertainty for job impact. Fractional roles may become more our norm.
He suggests, “the ability to unlearn and relearn will become the most valuable skill of all.” Get your copy here.
8. Igniting the Data Dance by Dr. Joe Perez
Reviewed by: Jane Smith
Who among us has not sighed at the words ‘data governance’? (Not me, obviously!)
Sigh no more - Dr. Joe Perez, a man I know and have had the pleasure of sharing a panel with, sees it differently. Inspired by a tower he saw on holiday in Lithuania, his central hypothesis is that data governance is not bureaucracy but the foundation for good decisions.
His ten-part framework is rich in metaphor and storytelling in navigating the tensions between the business and IT. I loved his insistence that transformation requires discipline and that a journey to something better requires resilience, courage, and perseverance.
As a practitioner, I found his advice on selling the story and value of data governance (beautifully compared to another dataset - the English language, which thrives because people know its rules, its standards are documented, and most importantly, it has a clear purpose)
This is data governance as we’ve never heard it told before… and you’re going to want to hear this.
Get your copy here.
9. Practical Data Modeling by Joe Reis
Reviewed by: Sonny Rivera
Before I started reading, I wondered if data modeling was a worn-out topic or if there was something genuinely new. What I found was that the basis is classic data architecture, but the framing and urgency for the AI era are entirely new.
This book connects data modeling directly to agentic architecture, graph-based RAG, and treats semantic models as living operational infrastructure. It gives a very traditional enterprise problem a new take and new sense of urgency.
Joe Reis has taken a modern approach to writing this book by releasing it on Substack, chapter by chapter, as he has been writing. What makes it even better is the level of access readers have had to the development of his ideas.
The physical book will be released in Sept 2026, and I’ll definitely get mine on day one. Read the Substack version here.
10. When Data Moves by Harveer Singh
Reviewed by: Cindi Howson
When Harveer first messaged me about his new book, I was initially discouraged by the title. I did not want to read a book on ELT or streaming data. This book is anything but!
In fact, Harveer specifically says if you are looking for a how-to and architectural best practices book, this is not it (even though he certainly has the technical chops to write such one).
Instead, as he says in early chapters, this book is for the burned-out. He wants you to feel an emotional connection with data and how it impacts people. I found this book refreshing, poignant, and humorous.
Listen to Harveer Singh on The Data and AI Chief podcast here, and get your copy here.
Bonus Noteworthy Reads
A few books were just coming to market as we were reading and reviewing. These will be on our reading list next based on early reviews.
The Ontology Pipeline: a Framework for Building Knowledge Infrastructure by Jessica Talisman
One of the most notable releases in information architecture and knowledge engineering this year, Jessica’s book publicly develops many of the ideas she explores in her Substack, Intentional Arrangement. And it’s here where she offers the industry a much-needed blueprint for structuring semantic knowledge.
You can pre-order the book which is set for publication by Technics Publications in September/October 2026.
The Psychology of AI Adoption at Work by Gleb Tsipursky
Tsipursky draws on over twenty five years of experience to provide an essential guide to overcoming resistance to AI in the workplace in order to supercharge efficiency and innovation.
On the Lighter Side: Our Favorite Personal Reads
We are continuous learners and readers, so in sharing our favorite non data and AI books for 2026, here were our pics:
Cindi: The Correspondent by Virginia Evans
I was inspired by her decades-long journey to be a writer. The format of story through letter writing brought characters to life across generations. It’s a beautiful story of relationships and regrets as a judge. It inspired me to handwrite a letter to my favorite aunt, age 92, for the first time in many years.
Sonny: The Keeper by Tana French
Released this summer, it’s the third book in the series. The New Yorker says French is an iconic crime writer who “inspires cultic devotion in readers” (yeah, that describes me). She has been called “incandescent” by Stephen King, “absolutely mesmerizing” by Gillian Flynn.
The plot: Retired Chicago copy, Cal Hooper, has friends now in a small Ireland village where he lives. But the town is being torn in two by the death of a young lady who was soon to be married. Cal’s hunt to justice threatens to bring old unhealed wounds.
