Leading AI Adoption in Healthcare: AI Doesn't Adopt Itself Paperback – February 13, 2026

Organizations have invested $30–40 billion in AI.According to MIT (2025), 95% produced no measurable return.Only 5% made it into daily workflows.If you’re reading this, you’re either trying not to become that statistic—or you’re early in pilots and trying to make sure you don’t.The problem isn’t bad technology.Most AI failures don’t begin at scale—they begin during pilots, when early success creates confidence without revealing the risks that only surface once AI is embedded in real workflows, real teams, and real decisions under pressure.AI initiatives fail because organizations focus on building and buying tools, while overlooking how AI actually behaves once it enters daily clinical and operational work. What looks controlled during pilots often creates new risks over time: unsafe decisions that go unchallenged, front-line concerns that stop surfacing, accountability gaps, and missed value that does not appear on dashboards until it is too late.Most leaders believe they are governing AI through pilots, performance metrics, and oversight committees. And yet problems still accumulate. Decisions get made faster, but with less scrutiny. Risk scales quietly while leadership believes things are under control.This book explains why.Leading AI Adoption in Healthcare shows why AI initiatives that look successful on paper often fail in practice—and what leaders must do differently to prevent unintended consequences before they surface as patient safety events, lawsuits, or workforce turnover.Drawing on real-world healthcare leadership experience and operational science, the book introduces clear leadership frameworks for governing AI where consequences actually land: in day-to-day workflows, team decisions, and moments where human judgment still matters.Written for executives with real accountability and limited time, this book is intentionally concise—focused on the decisions that protect patients, retain staff, and preserve trust, without jargon, hype, or performative complexity.This is not a book about slowing innovation.It is about making adoption real—so AI delivers durable performance instead of quiet failure.If you are responsible for AI outcomes, risk, and accountability, this book will change what you pay attention to—and what you insist on before you scale. Read more