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Key takeaways:
- Don’t just “AI-ify” the old internal audit model. A traditional internal audit plan is quickly outdated in a dynamic environment. Redesign internal audit procedures leveraging agentic workflow to test and respond to risks as they occur.
- AI agents are becoming part of the internal audit workforce. Leaders will need to manage their roles, access, interactions and performance—and deliberately design where human judgment enters the workflow.
- As AI takes on more execution, human judgment becomes more valuable. Internal audit teams will need the expertise, critical thinking and professional judgment to interpret what agents uncover, challenge conclusions and determine what deserves attention.
- Move from possibility to practice in 90 days. Identify where agentic workflows could materially change assurance, design how agents and people will work together, then test an end-to-end pilot and use the results to decide where to scale.
Imagine an internal audit that scopes itself. An autonomous AI agent detects a pattern across systems that no single person could spot, gathers and tests the relevant evidence, and brings the chief audit executive (CAE) a potential finding the team didn’t know to look for. That kind of audit feels out of reach. With agents, it’s not.
A year ago, in The end of traditional internal audit: Human-led, agent-powered, we laid out a vision for an audit function transformed by AI agents taking on repeatable, labor-intensive tasks, continuously testing controls across vast data sets, and generating insights in real time. Now, that vision is taking shape. Audit teams may be at different points in their adoption of AI, but many are beginning to experience what agent-powered transformation could make possible.
Now comes the bigger opportunity. Internal audit now has to decide what to do with the capacity it has never had before.
The opportunity goes beyond automating today’s audit plan. It means rethinking the audit model around continuously available information and agentic workflows that can expand the breadth, depth, and timeliness of internal audit’s work. Getting there will require redesigning how the work gets done and managing agents as part of the workforce. Clear ownership, accountability, and governance will be critical, along with appropriate oversight of the data that agents rely on and the outputs they produce. It will also require developing the human experience and judgment needed to work alongside and measuring whether the new model is producing better outcomes. The aim is to use these capabilities to perform work that simply wasn’t possible before.
Discover what’s next for internal audit
Watch the webcast: AI's potential, AI's risk: What CAE's should know
As AI agents take on more of the work, internal audit’s bottleneck is moving from execution to judgment. What does that mean for CAEs, their teams and the way assurance gets delivered? Join our CPE eligible webcast on October 14 from 12-1:30 ET.
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