Your customer clicked, paused, hovered-and then left. Your analytics platform logged a visit. Your dashboard marked it as "engaged." But your system had no idea what actually happened. It saw the click. It missed the regret.
Every day, we design products and services that collect behavioral data-yet fail to understand real behavior. We obsess over clicks and conversions while ignoring the hesitation, doubt, fatigue, and friction that drive human decision-making. We build AI systems that are technically perfect and behaviorally oblivious.
This book is about fixing that. (With more practical frameworks and fewer existential crises than you might expect.)
Business analytics professor and behavioral data science pioneer Ganna Pogrebna has spent over a decade building-and watching others build-AI systems that predict behavior without understanding it. The results? Countless quietly furious customers who got exactly what the algorithm said they wanted.
These systems rarely "fail" in ways that trigger post-mortems or media scrutiny. Instead, they produce recommendations that are locally coherent yet globally misaligned-nudging customers toward choices they later regret, steering employees toward compliance rather than insight, and locking organisations into feedback loops that reward short-term efficiency at the expense of long-term value. The damage accumulates quietly: rising friction in customer journeys, unexplained drop-offs in adoption, frontline staff overriding tools they no longer trust, and leaders mistaking stable metrics for healthy systems.
From financial services and public policy to digital platforms and enterprise decision support, the pattern repeats. Models predict behavior with increasing precision, yet remain blind to motivation, hesitation, fatigue, and context. What looks like intelligence in the dashboard often feels like coercion or confusion on the receiving end. The gap is not computational power or data volume; it is the absence of behavioral understanding at the core of system design. This tension-between what AI can optimise and how humans actually behave-has become one of the defining risks of modern decision systems. It is also the reason why any business's work needs to be increasingly focused not on better prediction, but on designing AI that understands behavior as something dynamic, situated, and ethically consequential, rather than as a static signal to be exploited.
In THE MISSING B IN AI, she introduces the Built on Behavior(TM) framework-a model for designing systems that finally listen to what people mean, not just what they do. Drawing on over two decades of cutting-edge research, her own executive experience, and real-world wins and failures (heavy on the failures-they're more educational), Ganna reveals why most business pipelines misfire-and how to rebuild them from the inside out.
You'll learn:
- Why customers abandon "successful" experiences-and how to detect regret before it happens
- How personalization often backfires-and what adaptive systems must do instead
- How to design for trust-not just consent
- Why behavior is the most underused strategic asset in business
- How to ask one behavioral question that changes everything
Whether you're an executive, founder, product leader, designer, strategist, or engineer, this book will change how you think about your products, your services, and the people who use them. It's rigorously researched, surprisingly readable, and contains practical tools you can actually use on Tuesday.
Because your system isn't broken. It's just not listening.
And your competitors are starting to hear what you're missing.
