"AI-Powered Auditing: A Systematic Analysis of Uses, Benefits, and Limitations"

Abstract

The future of auditing is in artificial intelligence (AI) that is slowly transforming the professionalism of auditor to no longer manually sample data, but to constantly build and data-driven and algorithm-supported assurance in the form of continuous data. This work is a research based on systematic review of available scholarly literature on AI-driven auditing synthesizing the evidence on its major applications, advantages, and limitations. The review is based solely on the secondary data obtained through the peer-reviewed journal articles; therefore, it combines the results of the latest systematic reviews, conceptual studies, and empirical research published since 2021 to 2025. The findings have shown that AI increases coverage, efficiency, accuracy of detecting fraud, and risk assessment capabilities in financial, internal, and IT, and ethics-oriented auditing areas by a significant margin. Nevertheless, the literature also singles out the existent issues of algorithm bias, unexplainable nature, skills gap, governance issues, and immature regulatory frameworks. The research paper concludes that AI-based auditing has to pursue a socio-technical route that entrenches ethical values, human control, and systematic governance systems in order to maintain audit integrity and public confidence.