Auditing Artificial Intelligence

Auditing Artificial Intelligence: A Handbook for Audit, Risk, and Security Professionals, 1st Edition, provides systematic evaluation methodologies for examining complex computational implementations. Authored specifically for IT auditors, information security experts, and risk management professionals, this reference handbook outlines technical frameworks designed to inspect algorithmic structures, system integrity, and operational oversight mechanisms.

The text structures its primary focus around core operational domains, advancing from foundational oversight principles to specialized technical assessments. Detailed thematic coverage includes generative AI metrics, prompt engineering validation, and reinforcement learning models, offering targeted procedures to analyze operational input data, system decision behaviors, and model output reliability.

Divided into 24 targeted chapters spanning governance, risk management, compliance, and system auditing, the work provides a methodical progression for formal technical reviews. It offers IT auditors, security experts, and risk professionals structured methodologies for evaluating automated software deployments within modern enterprise computing environments.