Episode 108 — Utilize AI to enhance audit execution while preserving evidence quality (Task 23)
This episode teaches you how to use AI to enhance audit execution while preserving evidence quality, because Task 23 scenarios often test whether efficiency improvements still produce defensible workpapers and conclusions. You’ll learn where AI can assist safely, such as summarizing large policy sets, clustering exceptions, proposing sample stratification ideas, and drafting test steps, while you maintain control over evidence collection, evaluation, and documentation. We’ll cover how to preserve evidence quality by grounding AI-assisted outputs in original records, retaining traceability to source artifacts, and documenting what was verified versus what was merely suggested. You’ll also learn how to avoid execution risks like accepting AI-generated interpretations of logs without validation, losing version context for models and data, or letting AI narratives replace actual control testing. By the end, you should be able to answer AAIA questions by choosing AI usage patterns that improve speed but keep audit evidence reliable, traceable, and reviewable. 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.
