This paper offers a practitioner’s view on how methodologies adopted by internal audit functions, largely designed for manual and deterministic internal audit work, are becoming misaligned with AI-enabled practices, and how they can evolve to address these gaps while preserving rigour and enabling responsible innovation.
This paper provides further Interpretation, Guidance, and Practical Considerations to the questions posed in Part 1.