The question isn't whether AI will transform your organization. It's whether that transformation will serve people or merely replace them.
Clayton Christensen's jobs-to-be-done framework taught us to ask what job customers really hire products to do. Now, as AI reshapes work itself, we need that same clarity of purpose. These eight books will give you the intellectual foundation to implement AI thoughtfully—starting with human needs, not technological possibilities.
Start Here: What People Actually Want
The Jobs-to-be-Done Pyramid by Scott Burleson offers the most comprehensive view of JTBD theory available. Burleson expands the traditional model from three dimensions to five levels: Product Jobs (tasks around using a product), Core Jobs (fundamental problems to solve), Role Identity Jobs (roles people want to embody), Image Identity Jobs (how people want to be seen), and Emotional Jobs (how people want to feel).
For our JTBD-to-AI manifesto, we chose the classical three dimensions (functional, emotional, and social) because they create a simpler, more actionable framework for AI implementation. Burleson's five-level pyramid reveals the complexity underlying each dimension while validating our approach.
When designing AI systems, you operate across all these layers: automating tasks, supporting professional identities, and shaping how people feel about their work and technology.
Co-Intelligence by Ethan Mollick offers the most practical guide for human-AI collaboration. Mollick treats AI as co-worker, co-teacher, and coach rather than threat or replacement. His book overflows with real examples of professionals using AI not to replace human judgment, but to enhance it. You'll learn to coordinate with AI, communicate with it, and develop shared ways of working.
Make It Work in Your Organization
Human + Machine by Paul Daugherty and H. James Wilson cuts through replacement anxiety with research from 1,500 organizations. They reveal how companies use AI to leap ahead by focusing on the "missing middle", where humans and machines collaborate most effectively.
The authors identify eight "fusion skills" essential for AI-enhanced workplaces, from "Rehumanizing Time" (freeing up time for distinctly human tasks) to "Relentless Reimagining" (creating new processes from scratch rather than automating old ones). People remain the architects of their roles and workplaces.
AI Leadership Handbook by Andreas Welsch addresses a harsh reality: 85 percent of AI projects fail, usually not because of technology but because of unrealistic expectations and employees unclear about AI's role in their jobs. Based on interviews with over 60 leaders, Welsch covers nine facets of AI leadership, from aligning AI with business strategy to keeping humans at the center. You'll learn why successful AI starts with outcomes, not technology.
Understand the Bigger Picture
Power and Prediction by Ajay Agrawal, Joshua Gans, and Avi Goldfarb takes the long view. They examine decision-making as the fundamental unit, explaining that decisions require both prediction and judgement, and AI's rise shifts prediction from humans to machines.
This sets up system-level innovation. Redesigning systems of interdependent decisions takes time, but when new systems emerge, they disrupt entire industries. The book helps you understand not just how to use AI, but how AI will reshape business models.
The AI Dilemma by Juliette Powell and Art Kleiner tackles the hard questions. AI misuse has led to wrongful arrests, denial of medical care, and even genocide. Their seven principles ensure machine learning supports human flourishing: rigorously determine human risk, make AI systems transparent, let people control their data, and confront embedded biases.
Transform Your Culture
AI Culture Shift by Adnan Iftekhar and Brian Moynihan addresses what most AI books ignore: culture. They present frameworks showing how to balance Intelligence Quotient, Emotional Quotient, and Adaptability Quotient to create resilient, innovative organizations.
This isn't about replacing humans with machines, it's about elevating both to create something greater than the sum of its parts.
Think in Systems
Thinking in Systems by Donella Meadows isn't about AI at all, and that's exactly why it belongs here. Meadows reminds us that the biggest problems facing the world are system failures that cannot be solved by fixing one piece in isolation.
AI doesn't exist in isolation either. It exists within organizations, communities, and societies that are themselves complex systems. Understanding stocks and flows teaches you how complex systems behave—essential knowledge for implementing AI that strengthens rather than fragments human systems.
What You'll Gain
Read these books, and you'll develop three critical capabilities: You'll see AI implementation as fundamentally about human needs, not technological features. You'll understand how to design human-AI collaboration that enhances rather than replaces human capabilities. And you'll think systematically about AI's impact on organizations and communities.
Most importantly, you'll have the intellectual framework to ensure AI serves human flourishing. Because we only get one chance to get this right.