Artificial intelligence has become a very useful prima donna in all business activities, especially in the world of accounting and auditing. This can be achieved by automating work processes in real time that prioritize reliability and accuracy. This study aims to map research in the field of artificial intelligence related to auditing and forensic accounting. This research uses a descriptive-qualitative method with a literature review approach. Data sources were collected from articles and journals indexed by Scopus and Sinta, totaling 47 journals with multiple pages such as Emerald, Science Direct, and Google Scholar. The objective of this research mapping is to focus on the application, challenges, opportunities, and strengths of artificial intelligence in fraud prevention and detection. The mapping results show that artificial intelligence related to auditing and forensic accounting is very useful in preventing and detecting financial fraud, with indicators of accuracy, reliability of data, information, and audit evidence. On the other hand, the implementation of artificial intelligence poses serious challenges that will erode the workforce, both in terms of layoffs and income inequality and data security.
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