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Bridging IT auditors and AI auditing: Understanding pathways to effective IT audits of AI-driven processes

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  • Li, Yueqi
  • Goel, Sanjay

Abstract

The increasing deployment of artificial intelligence (AI) in organizational accounting and other business processes necessitates the auditing of AI-driven processes. However, such processes can be difficult to audit, as the logic behind model decisions is often not explicit and hence less auditable than traditional IT processes. To address this issue, measures to render these processes auditable, alongside relevant auditor competencies, need to be established. Through a survey of 89 IT auditors, this exploratory study identifies and ranks auditability measures and competency requirements for auditors engaging in the auditing of AI-driven processes. Our findings suggest that while many traditional IT auditability measures remain important, auditing AI-driven processes requires additional AI-specific auditability measures, particularly those related to data governance processes and model explainability measures. IT auditors also need to be equipped with AI knowledge and specialized competencies in evaluating AI-driven processes, in addition to other IT auditing competencies. This research introduces key factors that affect the success of IT audits of AI-driven processes. Our findings can help guide the design of future AI auditability measures and training programs to better support IT auditors in evaluating AI-driven processes.

Suggested Citation

  • Li, Yueqi & Goel, Sanjay, 2025. "Bridging IT auditors and AI auditing: Understanding pathways to effective IT audits of AI-driven processes," Advances in accounting, Elsevier, vol. 69(C).
    • Handle: RePEc:eee:advacc:v:69:y:2025:i:c:s0882611025000379
    DOI: 10.1016/j.adiac.2025.100842
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    References listed on IDEAS

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