A Strategic Guide to AI in Healthcare provides a complete strategic architecture for understanding and implementing artificial intelligence across hospitals, health systems, and governments.

While AI is advancing rapidly, most organisations lack the strategic frameworks, organisational readiness, and implementation know-how to adopt it safely and at scale. The book is therefore structured around the adoption journey. Part I builds awareness and technical literacy, sets out the landscape, and explains why so many AI integrations fail. Part II focuses on hospital-level strategy and implementation, with chapters on building the business case, AI literacy and training, running pilots, scaling to enterprise, workforce transformation, and governance and ethics. Part III extends these themes to government and national strategy, covering regulatory navigation, national data infrastructure and interoperability, and cybersecurity. Each of the seventeen chapters combines theory with practitioner case studies (Mayo Clinic, Kaiser Permanente, the NHS AI Lab, WannaCry, Synnovis), structured exercises for executive education, and implementation checklists usable directly in board meetings, AI governance councils, and procurement reviews.

A timely and important resource, the book will be essential reading for anyone responsible for the strategic development of hospitals or healthcare systems, and for researchers in this field.