Artificial Intelligence, Audit and Fraud Risk Management: A Bibliometric Analysis Review

Artificial intelligence (AI) has evolved rapidly in recent years and has steadily become part of many aspects of life, including the field of audit and fraud risk management. Because of these developments, researchers have started to show a higher interest in the way AI can support auditors in identifying, assessing and reducing both audit and fraud-related risks. This paper presents a bibliometric study focused on the relationship of AI, auditing and fraud detection. The main objective of our study is to examine whether the existing literature identifies a clear connection, from an audit perspective, between the use of AI technologies and the way fraud is detected. To achieve this objective, the paper includes a bibliometric analysis of articles published in the ScienceDirect database over a period of almost three decades, more specifically from 1998 to 2025. Our analysis aims to identify the main research directions, the most frequent topics discussed by researchers and the extent to which AI tools are considered useful in fraud detection activities within auditing. The findings also point to several research gaps and underline the need for further investigation regarding the integration of AI into auditing practices. Particular attention should be given to the standardization of AI applications and to the development of auditors’ competencies required for the effective use of these existing technologies. Given the continuous technological changes shaping the modern business environment, further research on AI applications in auditing remains highly relevant.