Intelligent Audit: Enhancing Audit Efficiency and Quality Through the Instrumentation of Artificial Intelligence

Haoran Jin ()
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Haoran Jin: Zhejiang University of Finance and Economics

A chapter in Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025), 2025, pp 7-13 from Springer

Abstract: Abstract The evolution of audit practice is gradually moving towards the integration of advanced technologies to improve efficiency and audit quality. This paper constructs a strong theoretical framework based on the audit and information systems literature to examine how AI technologies can reduce the limitations inherent in human auditors, enabling broader data review, identifying complex patterns, and reducing the time and errors associated with manual audit tasks. Through a series of simulations and real-world case studies, this study shows that AI can significantly accelerate audit tasks while improving the accuracy and reliability of audit results. The results show that AI-enhanced audits not only improve risk assessment and fraud detection, but also improve the decision-making process by providing deeper data-driven audit evidence. In addition, the application of AI in the audit process is aligned with regulatory requirements and standards, heralding a paradigm shift towards more forward-looking and predictive audit practices. The article concludes with a discussion of the implications for auditors, companies, and regulators, suggesting that smart auditing is not just a technological advancement, but an evolution needed in the face of an increasingly complex financial environment.

Keywords: intelligent audit; artificial intelligence; machine learning; AI-augmented (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-770-0_2

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DOI: 10.2991/978-94-6463-770-0_2

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