CHALLENGES, OPPORTUNITIES AND IMPLICATIONS REGARDING THE INTEGRATION OF ARTIFICIAL INTELLIGENCE IN AUDIT PROCESSES

Mihaela PANAIT (ion) (), Marilena-Roxana Zuca (), Aura Oana MUSTÄ‚ÈšEA () and Victor Munteanu ()
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Mihaela PANAIT (ion): Valahia University of Targoviște, Romania
Marilena-Roxana Zuca: Romanian-American University, Romania
Aura Oana MUSTĂȚEA: Valahia University of Targoviște, Romania
Victor Munteanu: Valahia University of Targoviște, Romania

Journal of Information Systems & Operations Management, 2025, vol. 19, issue 1, 138-161

Abstract: In the context of rapid technological evolution and continuous changes in the business environment, auditing plays a significant role in ensuring the transparency, integrity and operational efficiency of entities. However, the increased complexity of activities and the growing volume of data with which auditors have to work have generated new challenges and required the continuous adaptation of audit methodologies and tools. In this context, artificial intelligence (AI) has emerged as a promising solution to improve the quality of the audit process. In this context, artificial intelligence (AI) has emerged as a promising solution to improve the quality of the audit process. AI technologies, such as machine learning, advanced data analytics, and natural language processing, provide auditors with powerful tools to perform deeper analysis, identify risks and anomalies, and streamline audit processes. These technologies allow the automation of repetitive tasks, the reduction of human errors and the provision of real-time information, thus contributing to increasing audit quality. The research focuses on exploring the potential of AI to improve the quality of the audit process. By analyzing the impact of AI technologies on traditional audit methods, it aims to identify the benefits, challenges, opportunities and implications associated with integrating AI into audit practice. The goal is to provide a deep understanding of how AI can contribute to optimizing the audit process and to propose practical recommendations for the effective implementation of this technology.

Date: 2025
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