COURSE DESCRIPTION

Artificial intelligence is being adopted across organizations (in finance, human resources, operations, customer service, and supply chain), yet most internal audit functions lack a documented AI risk universe or specific assessment criteria. This session provides a practical framework for identifying, classifying, and assessing emerging AI risks within any organization. Participants will learn to distinguish between risks arising from AI usage (hallucinations, algorithmic bias, lack of traceability) and risks arising from its absence (adoption gap, loss of competitiveness, regulatory non-compliance).

LEARNING OBJECTIVES

•    Classify AI risks based on their origin: model risks, data risks, governance risks, and operational risks.

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