This bibliometric review discusses artificial intelligence (AI) adoption in auditing and accounting, with emphasis on the rapid growth of research interest in this area since 2025. The study assesses publication volume patterns, prevailing themes, and influence of AI technologies such as machine learning, robotic process automation (RPA), and natural language processing (NLP) on traditional accounting. Key findings indicate that AI is transforming audit processes, sharpening risk assessment, and improving fraud detection strength. The critique also points towards certain serious regulatory and ethical challenges, including data privacy and bias in algorithms, which must be addressed to enable the responsible use of AI. Furthermore, certain research gaps are identified on organizational resistance to AI implementation, long-term implications on workforce dynamics, and the effectiveness of AI in financial reporting. The study concludes with suggestions for future research, including interdisciplinary research, longitudinal workforce implications research, and the development of ethical frameworks to guide AI use in accounting and auditing. This review serves as a guiding document for scholars, practitioners, and policymakers to use when addressing the issue of AI deployment in finance.
Batool et al. (Wed,) studied this question.