Demystifying AI: Internal Audit Use Cases for Applying New Technology
The Internal Audit Foundation and AuditBoard sought to identify practical use cases of generative AI for internal audit functions. This report highlights the insights and experiences of four internal audit leaders who have integrated or explored AI within their teams. Before detailing how AI is applied based on their input, the report provides a high-level overview of global practitioners’ perspectives on the use of new technologies in the profession, drawing on recent research from Internal Audit: Vision 2035.
Key takeaways include:
- AI will ultimately enhance internal audit, not replace it. However, the profession must be prepared to step up.
- Building an AI strategy that is organization-wide helps create transparency and accountability on AI use and supports effective risk management.
- Internal audit functions must ensure that their team members understand and apply best practices when interacting with LLMs. This includes comprehending how prompts work and how to phrase queries to achieve optimal results.
- The human/machine interface provided by LLMs and generative AI is much more intuitive and user-friendly. It is also less likely to intimidate those who have not worked extensively with newer technologies.
This report is made possible thanks to generous donations to the Internal Audit Foundation. Donate to help the IAF continue publishing globally-focused, cutting-edge research.