This study presents a comprehensive bibliometric analysis of scholarly research at the intersection of artificial intelligence (AI) and audit quality, covering publications from 2017 to 2025. Drawing on 125 Scopus-indexed articles, the analysis reveals a significant increase in research output, particularly in 2023 and 2024, reflecting growing academic interest in the transformative potential of AI in auditing. Citation metrics, including an h-index of 15 and g-index of 34, highlight a solid core of influential early contributions, with a shift in recent years toward more diverse but less-cited works due to recency. Co-occurrence analysis of 99 author keywords using VOSviewer identified five key thematic clusters: (1) automation and ethical technology, (2) quality management systems and audit reporting, (3) digital transformation and internal auditing, (4) data analytics, audit risk, and big data, and (5) audit firm performance and service quality. Overlay and density visualizations further reveal a thematic shift toward emerging areas such as sustainability, compliance, and stakeholder trust. The findings demonstrate a transition from foundational, technology-centric studies to more interdisciplinary research addressing strategic, regulatory, and ethical dimensions of AI in auditing. This bibliometric review offers valuable insights for researchers, practitioners, and policymakers by mapping the intellectual landscape, identifying underexplored areas, and proposing directions for future inquiry into AI’s role in enhancing audit quality.