Popis kurzu
Tato část není lokalizována
AI Across the Audit Lifecycle
Apply AI across risk assessment, audit planning, continuous monitoring, fieldwork, evidence analysis, reporting, and follow-up.
Audit-Relevant AI Techniques
Use machine learning, natural language processing, generative AI, and predictive analytics for audit-relevant tasks.
Validation, Data Quality, and Professional Skepticism
Validate AI-generated outputs, identify errors and hallucinations, assess data quality, maintain traceable evidence, and document AI-assisted work so it remains reviewable and repeatable.
Responsible AI and Governance
Apply ISO/IEC 42001, NIST AI RMF, and the EU AI Act within an assurance context, with attention to ethics, privacy, confidentiality, bias mitigation, and human accountability.
Industry Application and Audit Leadership
Adapt AI-enabled audit techniques across six major industry contexts, coordinate assurance across the three lines in line with Standard 9.5, and communicate AI-driven insights to audit committees and boards.
