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

DOI

10.2991/978-94-6463-770-0_2How to use a DOI?

Keywords

intelligent audit; artificial intelligence; machine learning; AI-augmented

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.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Haoran Jin
PY  - 2025
DA  - 2025/06/26
TI  - Intelligent Audit: Enhancing Audit Efficiency and Quality Through the Instrumentation of Artificial Intelligence
BT  - Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025)
PB  - Atlantis Press
SP  - 7
EP  - 13
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-770-0_2
DO  - 10.2991/978-94-6463-770-0_2
ID  - Jin2025
ER  -