Episode 93 — Build AI audit objectives that connect directly to business risk (Domain 3A)
This episode teaches you how to build audit objectives that connect directly to business risk, because AAIA scenarios often test whether you can write objectives that are meaningful and testable instead of generic. You’ll learn to express objectives in terms of what must be true for the AI use case to be acceptable, such as decisions being accurate enough for the purpose, fair within defined thresholds, compliant with privacy and policy constraints, and supervised with escalation paths that prevent ongoing harm. We’ll cover how to tie objectives to risk drivers like data quality, drift, third-party dependencies, and human oversight capacity, then translate each objective into the kinds of evidence you would expect to validate it. You’ll also learn how to avoid audit objectives that are too broad to test, or too technical to matter, by keeping the focus on outcomes and control intent. By the end, you should be able to read a scenario and choose the objective set that would produce a defensible audit conclusion aligned to business impact. 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.
