Episode 8 — Set governance routines that keep AI security decisions consistent (Task 1)
This episode explains how governance routines turn intent into repeatable action, which matters for Task 1 because AAISM expects you to sustain AI security decisions over time, not just design them once. You’ll build a practical cadence of reviews and checkpoints for AI intake, impact assessment timing, inventory updates, control health, incident learnings, and vendor status, and you’ll learn how to structure meetings and artifacts so they produce evidence instead of opinions. We’ll cover best practices like defining triggers for out-of-cycle reviews, using standardized decision templates for approvals and exceptions, and ensuring outcomes feed metrics and risk reporting. Troubleshooting focuses on common failures: routines that are too frequent to maintain, too vague to be auditable, or disconnected from change management, causing drift in model behavior and untracked exposure. You’ll leave with a governance rhythm that maps cleanly to exam scenarios. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
