Episode 30 — Define AI security metrics leaders can understand and act on (Task 18)
This episode focuses on Task 18 by teaching you to define AI security metrics that leaders can use to make decisions, because AAISM favors measurable, outcome-linked reporting over technical noise that cannot drive prioritization or accountability. You’ll learn how to select metrics that reflect governance health, risk exposure, and control performance, such as inventory completeness, assessment coverage for high-impact use cases, access review outcomes, model change review compliance, monitoring signal quality, incident trends, and time-to-remediate for AI-specific findings. We’ll work through a scenario where leadership wants proof that AI rollout is “safe,” and you’ll practice converting that vague request into clear metrics with targets, thresholds, and escalation triggers that map to tasks and control owners. Troubleshooting covers vanity metrics, inconsistent measurement across teams, and reports that do not connect to actions, because on the exam the best answer is the one that supports decisions and accountability. 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.
