Episode 104 — Follow up AI audits so fixes stick and risk stays reduced (Domain 3E)
This episode explains how to follow up AI audits so remediation actually sticks and risk stays reduced, because Domain 3E recognizes that AI environments change quickly and “we fixed it” can evaporate after the next retrain or deployment. You’ll learn how to design follow-up work that verifies corrective actions are implemented, operating, and still aligned to the original criteria, including evidence checks like updated monitoring rules, documented approvals, improved lineage records, revised reviewer guidance, and confirmed access control changes. We’ll cover how to validate effectiveness using trend data, such as reduced exception volume, faster escalations, fewer repeat incidents, and more consistent documentation quality in change packages. You’ll also learn how to manage follow-up when remediation depends on vendors, shared platforms, or multiple teams, and how to document residual risk if timelines slip. By the end, you should be able to choose exam answers that treat follow-up as ongoing assurance with measurable verification, not a one-time status request or a closed ticket with no proof. 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.
