AI Security & Governance Annual Update Methodology: Regulation, Standards, Threats, Incidents, Controls, Assurance, Board Reporting, and Evidence for ... 12-Month Implementation Worksheets

Part of the AI Security & Governance All-in-One Series by Professor Kai London. This volume is a substantive annual update methodology for the AI Security & Governance All-in-One Series. It explains how to review regulatory change, standards updates, threat developments, incidents, controls, assurance expectations, board reporting, and evidence requirements each year, and how to turn each change into an implemented control and a defensible record. It sets out the annual update operating model and the detailed methods for updating regulation and standards, threats and incidents, controls, and board and audit reporting - illustrated throughout with worked examples, full case studies, a maturity model, and guidance on scoping, prioritisation, evidence, and sustaining the discipline. Written for the person accountable for AI governance and the team that runs the annual cycle.