Auditing Transformation: A Model of Artificial Intelligence Adoption

Authors

  • Joseph B. O’Donnell Canisius University

DOI:

https://doi.org/10.33423/jabe.v26i6.7390

Keywords:

business, economics, artificial intelligence, auditing, accounting, Technology Acceptance Model (TAM), Innovation Diffusion Theory (IDT), generative AI, auditor AI adoption

Abstract

Auditors using artificial intelligence (AI) offers opportunities for transforming audits, and drastically improving audit effectiveness and efficiency. Generative AI, augmented AI, and AI performing an entire audit offer possibilities for enormous cost savings and the potential to dramatically improve audit quality. Obstacles to audit adoption include AI processing opaqueness, shortage of auditors with AI knowledge, a dearth of AI audit standards, and significant AI implementation costs. This paper develops a theoretical auditor AI adoption model utilizing innovation diffusion theory (IDT) and the Technology Acceptance Model (TAM). The paper provides suggestions for facilitating auditors’ adoption of AI.

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Published

2024-11-30

How to Cite

O’Donnell, J. B. (2024). Auditing Transformation: A Model of Artificial Intelligence Adoption. Journal of Applied Business and Economics, 26(6). https://doi.org/10.33423/jabe.v26i6.7390

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