AI Resilience All-in-One by Kai London
Your organisation now depends on AI it did not fully plan for, some of it adopted without asking. This book treats that dependency as an operational risk: knowing where AI sits in your processes, detecting when it degrades, responding when it fails, and keeping the trust of customers who were affected.
Available on Amazon.
What is inside
Finding shadow AI
Discovering unsanctioned tools and embedded AI features, and bringing them into governance without shutting the business down.
Model risk in operation
Drift, degradation, silent failure and the monitoring that catches a model that has quietly stopped being right.
AI incident response
Classifying an AI incident, containing it, and dealing with harm that is reputational as often as it is technical.
Dependency and concentration
Provider outages, model deprecation and the fallback path when the API you built on changes.
Secure AI operations
Change control, evaluation gates, rollback and the discipline of running models as production systems.
Digital trust
Disclosure, redress and communication that preserves customer and regulator confidence after an AI failure.
Who it is for: CISOs and technology risk leaders, AI and MLOps teams, resilience and continuity planners, and executives accountable for AI-dependent services.
A model does not announce that it has stopped being right. That is the resilience problem.
About the author
Professor Kai London — CISSP, CISM.
An internationally recognised cybersecurity executive, board advisor and Founder & CEO of Quantum AI Systems Security LLC, writing at the convergence of AI, governance and operational resilience. Honorary Professor and Researcher at UCL.