Governance
Forthcoming professional field guide
Medical AI governance, made practical.
A serious, accessible guide for executives, quality leaders, regulatory professionals, AI owners, clinicians, and technology teams responsible for governing AI in medical contexts.
What the reader gains
A bridge from governance concepts to repeatable decisions.
The book is designed to help readers build a coherent operating model: know what AI exists, determine what rules apply, assign accountability, validate proportionately, maintain evidence, and respond when change creates new risk.
- A medical AI governance lifecycle
- Role and accountability models
- Risk, validation, and evidence frameworks
- Practical assessment and remediation tools
Planned chapters
The medical AI governance problem
From intended use to accountability
AI inventory and classification
Risk across the medical AI lifecycle
Validation in context
Controls, evidence, and traceability
Governance remediation
Continuous monitoring and change
Executive oversight and decision-making
Building the operating discipline
Planned editions