Mapping the Intersection of Artificial Intelligence and Audit Quality: A Bibliometric Analysis of Research Trends

The integration of artificial intelligence into audit practice has attracted considerable academic interest, particularly with regard to its impact on improving audit quality. This study aims to examine the emerging trends in academic research at the intersection of artificial intelligence and audit quality through a bibliometric lens. A comprehensive dataset was extracted from the Scopus database based on documents published between 2008 and 2025, with a total of 122 documents included in the final analysis. The results show a notable increase in publications, reflecting the growing academic interest in the application of AI in auditing. The keyword analysis revealed that audit quality and artificial intelligence are the most frequently used and cited terms, highlighting them as fundamental topics. To summarise, this study provides a comprehensive bibliometric overview of the current state and future development of research on artificial intelligence and audit quality. It provides valuable insights for academics, practitioners and policy makers who want to understand the development of the field, identify influential contributions and uncover potential gaps for future research. As artificial intelligence continues to reshape the auditing profession, continued interdisciplinary collaboration is essential to ensure that technological advances do not jeopardise audit quality and professional integrity.