<![CDATA[Advancements in digital technology and Artificial Intelligence (AI), including Machine Learning, NLP, and RPA, have become crucial instruments for enhancing the efficiency and accuracy of the audit process, particularly in fraud detection. This study aims to comprehensively map the role of AI through a Systematic Literature Review (SLR) method guided by the PRISMA 2020 statement, combined with a bibliometric analysis using VOSviewer. Through a search of the Google Scholar and Scopus databases (spanning 2020-2025), 15 selected articles were analyzed using Hoque's (2014) five-dimensional framework. The results of the literature mapping identified four main thematic clusters: (1) AI & Fraud Detection, (2) AI in the Audit Process, (3) Auditor & AI Collaboration, and (4) Challenges & Regulations. This study confirms that AI has proven capable of automating audit tasks and detecting fraud anomalies in real-time. However, its implementation remains hindered by algorithmic bias, data privacy issues, a lack of standard regulations, and limited technological literacy among auditors in developing countries. This research contributes by presenting a synthesis of current research trends and providing strategic directional guidance for future research regarding the integration of AI within accounting information systems.]]>
Copyrights © 2026
