The Applicability of Manual-Based IIA Global Standards in AI-Driven Internal Auditing: A Bridging-Gap Systematic Literature Review
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This paper examines whether and how the Institute of Internal Auditors’ (IIA) manual-based Global Internal Audit Standards (the 2024 Standards, effective 9 Jan 2025) remain applicable when internal audit engages with AI-driven systems and processes. Using a systematic literature review (SLR) approach and a thematic synthesis of practitioner guidance, standards texts, and academic research, the paper maps the overlap between principle-based IIA Standards and AI auditing needs, identifies gaps where the manual (traditional) interpretation of Standards is strained by AI characteristics and proposes a pragmatic bridging framework (policy, practice and capability) for auditors, stakeholders, and standards-setters. Key findings: the IIA’s Standards remain broadly relevant as high-level normative anchors, but practical application requires AI-specific procedural guidance, stronger access/transparency norms, and workforce upskilling; the IIA’s AI Auditing Framework is a critical complementary resource but does not completely eliminate operational gaps calling for targeted Topical Requirements and coordinated standard-setting for AI assurance.
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