AI in Audit: The FRC’s Risk Framework

Learning Objective: By completing this Nano Learning course, participants will be able to:

• Identify the FRC's three categories of AI risk to audit quality and explain how misuse and non-compliant methodology can cause audit failures even when the AI output is correct
• Define the five LLM output deficiency types and the three risks specific to agentic AI systems — goal drift, amplification risk, and interface/combination risk