Agentic AI and the Future of Internal Audit: Orchestrating Hybrid Intelligence
Alan M. Maran introduces a three-part series on Agentic AI, highlighting its potential to revolutionize internal audit beyond basic LLM assistance. He envisions a hybrid workforce where autonomous AI agents handle routine tasks, allowing human auditors to focus on complex risks and strategic judgment. This shift necessitates a new focus on designing, supervising, and governing these intelligent systems responsibly.
The Next Chapter: Agentic AI in Internal Audit
While large language models (LLMs) have already begun to assist internal audit in report writing and efficiency, the next significant evolution lies in Agentic AI. This advanced form of artificial intelligence moves beyond mere assistance, introducing autonomous agents capable of executing defined audit activities independently.
A Hybrid Workforce: Humans and Digital Agents
The future of internal audit, as envisioned by Alan M. Maran, involves a hybrid workforce where human auditors and digital agents collaborate seamlessly. This coordinated system leverages the strengths of both:
- Agents: Provide scale, speed, and pattern recognition, performing tasks such as continuous transaction monitoring, anomaly detection, evidence gathering, and structuring findings.
- Humans: Contribute skepticism, contextual understanding, ethical considerations, and accountability, focusing on complex risk assessment and strategic judgment.
Shifting Paradigms in Audit Operations
This integration of Agentic AI will fundamentally alter internal audit operations:
- From managing projects to orchestrating intelligence.
- From executing every test step to supervising risk systems.
- From periodic sampling to continuous visibility.
This evolution empowers audit teams to engage more deeply with strategic judgment and meaningful business engagement, strengthening the control environment and enhancing foresight.
Designing and Supervising Agentic AI
For Chief Audit Executives (CAEs) and their teams, the focus shifts from simply using AI to designing and supervising it effectively. This includes understanding:
- How agents are configured.
- How risk thresholds are established.
- How decisions are generated.
- How outputs are validated over time.
Responsible governance of these hybrid environments will be crucial for relevance in this new era.
Addressing Key Questions and Future Exploration
The introduction of Agentic AI raises important questions regarding governance, ownership, escalation protocols, and professional standards. Maran views these not as barriers but as leadership opportunities. His upcoming three-part series will delve into:
- The operating model shift to hybrid intelligence.
- Governance and accountability in an agentic environment.
- The implications for talent, audit committees, and the next generation of auditors.
The ultimate goal is not to choose between humans and AI, but to design their collaborative future in internal audit.
By Alan M. Maran
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