AI isn’t a novelty any longer — it’s a must-have for your internal audit team. Through automation, data analysis, and large language models (LLMs), AI can help you work more efficiently and gain a more complete picture of your risk environment.
Auditors shouldn’t be afraid of AI. Outputs still need to be validated, but what matters most is what humans can do with the insights AI generates: Take action. AI is an excellent opportunity to spend time on more strategic advisory work, fulfilling the key message of the Internal Audit Foundation’s Vision 2035 report.
In this KPMG and AuditBoard guide, you’ll find practical, real-life examples of how audit teams are using AI and a clear roadmap for adopting it. It explores foundational lessons, from understanding security risks to the essential "human in the loop" role.
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Key lessons to keep in mind as you’re getting started.
12 use cases for AI in internal audit, from out-of-the-box options you can try immediately to higher-maturity capabilities.