An organization is preparing its first AI audit program. The Chief Audit Executive asks what skills AI auditors need that traditional IT auditors may lack. Which capability is MOST uniquely required for AI auditing?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because AI auditing requires skills that traditional IT auditors typically lack: understanding of statistical model development, bias testing frameworks, machine learning performance metrics (AUC, F1, precision, recall), and the ability to evaluate whether validation approaches are appropriate for the use case. Network security (A) and SDLC (C) are relevant to general IT auditing.
Full explanation below image
Full Explanation
B is correct because AI auditing requires skills that traditional IT auditors typically lack: understanding of statistical model development, bias testing frameworks, machine learning performance metrics (AUC, F1, precision, recall), and the ability to evaluate whether validation approaches are appropriate for the use case. Network security (A) and SDLC (C) are relevant to general IT auditing. ERP procedures (D) are entirely unrelated. The distinctive competency for AI auditors is quantitative model literacy combined with understanding of AI-specific risks.