In this episode of our Internal Audit podcast series, John Heagy, Senior Manager, and Scott Peyton, Partner in our Risk Advisory practice, discuss the evolving role of internal audit in artificial intelligence (AI) oversight. They unpack the differences between traditional and generative AI, explore how internal audit function is leveraging these technologies, and examine the risks that come with AI adoption—while providing risk mitigation and identification strategies.This is the final episode in our four-part internal audit series. Catch up on the first three episodes The Evolving Role of Internal Audit: Unpacking IIA’s Vision 2035 Report, Top 3 Critical Skills for the IA Profession and The Client's Guide to Data Analytics in Internal Audit.Tune in to learn more about:A breakdown of AI types andhow traditional AI differs from generative AIHow internal audit teams are leveraging AI for tasks like fraud detection, control documentation and data analysisThe risks of AI, including bias, hallucinations, outdated data and ethical concernsKey elements of a strong AI governance framework, including transparency, accountability and responsible use policiesWhat to include in an AI audit scope, from understanding training data to evaluating cybersecurity and user behaviorRelated Insights:Podcast: https://www.cbh.com/insights/podcasts/a-guide-to-iias-vision-2035-for-audit-teams/ Article: 2025 Internal Audit Risks and Hot Topics Podcast: https://www.cbh.com/insights/podcasts/top-3-skills-for-internal-audit-profession/ Podcast: The Client's Guide to Data Analytics in Internal AuditView All Podcasts from this Series

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