Beyond AI in Healthcare

A proposal for an AI product usually reaches a board with three reassurances attached: it is validated, it is approved, and hundreds of hospitals use it. None of them says whether patients will be better off. Beyond AI in Healthcare is a reference for the people who must sign anyway: chief executives, board members, medical and nursing directors, heads of quality, safety and digital services, and the clinicians, commissioners and regulators who shape how care is delivered. Seventy chapters in four parts carry one argument. Part I explains how AI systems work, from data and prediction to language models, agents and robotics, without mathematics beyond fractions. Part II examines present uses across documentation, imaging, pathology, diagnosis, treatment, medicines, surgery, care at home, research, operations and finance, and weighs the evidence for each. Part III sets out the gaps that tools alone leave open, including fragmented care, accountability, human oversight, payment and the costs of moving too fast or waiting too long. Part IV states the book's own predictions, centred on the case for an AI doctor, and labels each one as a hypothesis with the signals that would confirm or defeat it. Every empirical claim is cited, every product fact carries its year, and no product is endorsed. A six-rung maturity ladder places each technology where its evidence stands, whatever its marketing suggests. Reference material includes a glossary, a map of technologies and evidence maturity, questions for evaluating vendors, a decision guide and a register of predictions.