Reimagine internal audit with agentic AI to drive value

Artificial intelligence is rapidly transforming how companies work, including reshaping the internal audit and compliance landscape. Middle market businesses are increasingly focused on integrating agentic AI technologies that leverage autonomous AI systems to conduct continuous monitoring, evidence collection and risk assessments with reduced human intervention. These agentic AI internal audit strategies can provide real-time, always-on risk analysis, task automation and fraud detection, transforming the auditor's role from execution to higher-value strategy and oversight. 

In addition to considerable benefits, agentic AI internal audit strategies can face several challenges, including transparency and explainability of conclusions, as well as data security and access concerns. As agentic AI continues to revolutionize internal audit, companies must focus on implementing an effective AI strategy to set a foundational AI vision, manage related risks and gain a competitive advantage.

To illustrate the AI challenges companies face, the 2025 RSM Middle Market AI Survey: U.S. and Canada found that 92% of middle market executives experienced challenges with AI implementation. In addition, 62% said generative AI was harder to implement than expected, and 70% of those using generative AI report they need outside assistance to get the most out of that tool.

Furthermore, 76% have a dedicated AI budget, 88% of those with a generative AI budget expect a budget increase and 94% of those with an AI budget use it for AI tools and technology. However, successful AI deployment requires clear strategy, strong governance and risk management, industry-specific technological support, talent development and user adoption, and functional integration to ensure smooth adoption and value creation.

To highlight AI’s extensive internal audit and compliance potential, RSM US Directors Neil Kumar Venkateswaran, Sophie Tomeo and Joseph Fontanazza provided insights into how to enhance efficiency and create long-term value during RSM’s webinar Harnessing AI and automation for compliance and internal audit excellence.

Below, we explore highlights from that webinar for internal audit teams, focusing on the evolution of AI, practical use cases and effective AI governance.

Agentic AI within internal audit

Agentic AI, a step forward from traditional AI and robotic process automation, is integral to the creation of limitless automation and frictionless processes by leveraging the entire depth of domain expertise, similar to human subject matter experts in an organization. Moreover, agentic AI adds a layer of reasoning and adaptability, seamlessly aligning with a company’s technological landscape with minimal maintenance.

AI agents can significantly enhance efficiency and drive long-term value by streamlining several tasks, including:

• Understanding plain English instructions to perform even the most complex tasks
• Documenting all actions and decisions for transparent audit and compliance
• Aligning with your organizational policies, increasing productivity with minimal errors
• Operating continuously without fatigue and continually learning and adapting at minimal cost

However, to unlock the full potential of agentic AI, organizations need to shift their mindset: treat AI not as just another automation tool, but as a digital employee.

Fundamental to this approach is the acknowledgement that while, like humans, AI can certainly learn, adapt and execute complex tasks—it can also make mistakes (or, in the language of AI, hallucinate) just as an intern might. Realizing value with agentic AI requires the same thoughtful oversight you would use with a human employee, without overestimating its capabilities. Exercising human-in-the-loop control to retain final judgement and accountability is a key consideration for deploying a successful AI agent for internal audit, ensuring return on investment and success metrics are grounded within human oversight.

“Building a robust AI solution requires strong governance and careful selection of the right use cases. Success depends on identifying the most critical business areas and deploying AI where it can deliver consistent, immediate value,” says Venkateswaran. “Many AI initiatives fail because organizations aim for large, enterprise-wide, big bang implementations instead of following a crawl-walk-and-run approach and starting with smaller, high-impact opportunities.” 

Agentic AI solutions and use cases

End-to-end, AI-driven internal agents help automate important audit processes and greatly reduce manual work and time investments.

Proven use cases include:

“The AI agent significantly speeds up the process and produces a first draft in minutes, a task that typically takes auditors one to two days. However, it is important to conduct a human-in-the-loop review,” says Tomeo. “During user acceptance testing, we found that at times the agent would misinterpret details, such as using individual names instead of roles or combining multiple controls into one. Therefore, auditors must still review and refine outputs, confirm details with auditees, and ensure accuracy before moving to the testing phase.”

“You must be vigilant to verify that internal control descriptions and data fields are accurate before prompting the agent to create testing strategies,” says Tomeo. “When properly reviewed and refined, the agent can accurately generate testing procedures and document requests, saving auditors several hours of manual work by translating existing information into actionable audit steps.” 

 “The quality of output depends on detailed test data and strong human oversight, all while maintaining a strong engagement with the auditee,” says Tomeo.

“We are not here to chase any magic agent, but a responsible AI agent to help streamline internal audit processes to drive value and create long-term impact,” says Fontanazza. “These agents must comply with governance standards, designed to manage risk, uphold data integrity and ensure responsible AI deployment in audits.” 

You must always build an internal audit AI agent that operates within your enterprise security framework, ensuring compliance and data integrity within the enterprise walls. AI agents are designed to help reduce the time spent on manual tasks and drive efficiency. However, the output is directly proportional to the input and data quality. Therefore, adhering to the human-in-the-loop principle is a must as any AI-driven output may sometimes misinterpret nuances.

Additional opportunities to incorporate agentic AI in audits

There is always a new horizon to reach with agentic AI in the internal audit landscape. It can truly take your current AI approach to the next level, including its ability to seamlessly align outputs with the firm’s methodology. Some additional opportunities for agentic AI within the internal audit lifecycle include: