AI-Driven Continuous Auditing

 By Kavishka, January 2026

AI-Driven Continuous Auditing Revolutionizing IT Controls



Artificial Intelligence (AI) is transforming traditional IT audits from periodic snapshots to real-time, continuous assurance processes. This shift aligns with core IT control principles like those in COBIT and ISO 27001, enabling proactive risk detection through automated control testing on live data streams from cloud ERPs and automated workflows.

In practice, AI agents—self-directed systems—handle multi-step tasks like anomaly detection in transaction logs and vulnerability predictions using machine learning models trained on historical attack patterns. For instance, Deloitte highlights agentic AI for 2026 audits, where systems produce traceable evidence with confidence scores, reducing manual reviews by weeks and allowing auditors to focus on strategic judgment. A global example is SentinelOne’s Singularity platform, which integrates AI for real-time threat response during audits, enhancing efficiency in cybersecurity controls.


However, academic debates center on ethical challenges: AI introduces biases in decision-making and requires auditable governance to maintain trust. Critics argue that over-reliance erodes auditor skepticism, a key tenet of ISA 315 risk assessment. Best practices include hybrid human-AI models with explainable AI (XAI) to ensure transparency, as seen in NIST frameworks for cybersecurity audits.



To visualize, consider a control paradigm: Input (live data feeds) → AI Processing (anomaly detection via ML algorithms) → Output (real-time alerts with audit trails). This paradigm reflects experiential learning from module discussions on evolving ITGC (IT General Controls), urging auditors to upskill in AI oversight for 2026 compliance.

References

Comments

  1. Rangi Madhushika30 January 2026 at 07:53

    A very timely and well-structured post. I like how you connect AI-driven continuous auditing with established control frameworks such as COBIT and ISO 27001, while also addressing ethical concerns like bias and auditor skepticism. As agentic AI systems become more autonomous in audit testing, how can auditors ensure that professional judgment and independence are preserved, especially when relying on AI-generated evidence and confidence scores?

    ReplyDelete
  2. J W Sachini DIlhara30 January 2026 at 08:01

    Excellent insights, Kavishka! The shift to AI-driven continuous auditing is well explained. How can auditors ensure AI models remain unbiased and reliable over time, especially as new transaction patterns emerge?

    ReplyDelete
  3. Yalana Madurangi30 January 2026 at 08:44

    This comment has been removed by the author.

    ReplyDelete
  4. Yalana Madurangi30 January 2026 at 09:02

    A simple yet insightful article that makes AI-driven continuous auditing easy to understand.

    ReplyDelete
  5. Madhushan Gunawardhane 30 January 2026 at 09:23

    Very timely and insightful post. I like how AI-driven auditing is linked to COBIT and ISO 27001, while ethical concerns and auditor judgment are well highlighted.

    ReplyDelete
  6. Chamudi30 January 2026 at 10:07

    Great article! You explained AI-driven auditing in a clear and easy way.

    ReplyDelete
  7. Tharushi Nishadi30 January 2026 at 22:44

    Great illustration! I like how it shows AI-driven auditing and highlights the need for auditors to upskill in AI oversight for modern ITGC compliance.

    ReplyDelete

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