COURSE DESCRIPTION

Artificial intelligence is being adopted across the organization — in finance, human resources, operations, customer service, and supply chain — and most internal audit functions do not yet have a documented AI risk universe or specific evaluation criteria in place. This session provides a practical framework for identifying, classifying, and assessing emerging AI risks in any organization. Participants learn to distinguish between risks that arise from using AI (hallucinations, algorithmic bias, lack of traceability) and risks that arise from its absence (adoption gap, loss of competitiveness, regulatory non-compliance). The session includes a risk mapping exercise that participants can apply directly in their next annual risk assessment.

LEARNING OBJECTIVES

•    Classify AI risks by source: model risks, data risks, governance risks, and operational risks

•    Apply an AI risk taxonomy to the existing audit universe to identify new auditable areas