AI is making consequential decisions inside your organisation — right now.
Credit approvals, fraud detection, hiring screens, legal drafts, clinical recommendations. AI models are embedded in core operations at most large organisations. The question is no longer whether to use AI — it's whether you're governing what it does on your behalf.
Mastering AI Model Risk is the definitive executive guide to understanding, managing, and governing AI model risk in the era of binding regulation. Written for boards, C-suite executives, and senior risk professionals, this practical guide cuts through the technical complexity to give leaders the mental models, frameworks, and action plans they need.
What you'll learn:
- Why AI model risk is a board-level issue — and the real financial, legal, and reputational costs of getting it wrong
- The EU AI Act decoded — mandatory requirements, risk classifications, conformity assessments, and penalties up to €35m or 7% of global turnover
- The AI model lifecycle — where risk enters at every stage from data sourcing to decommissioning
- LLM and agentic AI risks — hallucination, prompt injection, autonomous action, and how to govern systems that act faster than humans can react
- Governance frameworks that work — clear accountability structures, model inventories, risk tiering, and escalation paths that reach the board
- Practical mitigation strategies — model validation, explainability, red-teaming, bias audits, and human oversight mechanisms
- Building a resilient AI risk culture — from shadow AI to board-level AI literacy
- Real-world case studies — discriminatory hiring tools, flash crashes, regulatory enforcement, and reputational failures
Includes an Executive Glossary of 25+ AI risk terms, a 90-day action plan with role-level owners, regulatory framework references (EU AI Act, NIST AI RMF, ISO/IEC 42001, GDPR, PRA SS1/23), and a curated toolkit of governance platforms and academic references.
Who this book is for:
CEOs, CFOs, CROs, CDOs, General Counsels, Board Directors, Non-Executive Directors, Chief Compliance Officers, and any senior leader whose organisation deploys or plans to deploy AI systems in consequential contexts.
The executive who understands AI model risk has a meaningful advantage. The one who delegates it entirely to the data science team is exposed.
