Episode 24 — Keep the AI inventory accurate with routine governance checks (Task 13)
This episode covers how to keep the AI inventory accurate through routine governance checks, reinforcing Task 13 with the exam-critical idea that inventories decay unless they are embedded into change management, vendor oversight, and operational review cycles. You’ll learn how governance routines detect drift such as new integrations, expanded data access, model swaps, feature flags that change behavior, and shadow deployments that bypass formal intake. We’ll use a practical scenario where a team adds a new plugin to improve productivity, but the change quietly expands the assistant’s access to sensitive repositories, and you’ll practice the correct governance response: update inventory records, re-run relevant assessments, adjust monitoring, and validate that approvals and policies still apply. Troubleshooting focuses on the most common failure patterns, including inventories owned by no one, updates that rely on manual memory, and inventories that omit prompts, datasets, or logging destinations that later become the root cause of an incident. 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.
