ARTIFICIAL INTELLIGENCE DALAM PROSEDUR AUDIT SEBUAH SYSTEMATIC LITERATURE REVIEW

Abstract

This study aims to examine the role of Artificial Intelligence (AI) in auditing procedures and evaluate its benefits and challenges. Using a Systematic Literature Review approach based on the PRISMA method, this research analyzes 14 relevant scientific articles published between 2014 and 2024. The findings indicate that AI has been widely applied across various stages of the audit process, including planning, internal control testing, substantive procedures, and reporting. Technologies such as Robotic Process Automation (RPA), Machine Learning (ML), Natural Language Processing (NLP), and Optical Character Recognition (OCR) have proven effective in improving audit efficiency, accuracy, and coverage by automating routine tasks and detecting anomalies in real time. However, the adoption of AI also faces challenges such as algorithm transparency limitations, data bias, privacy issues, and auditors’ limited understanding of the technology. The study concludes that the successful integration of AI into auditing depends heavily on auditor readiness, the development of transparent and accountable systems, as well as supportive regulations and ethical frameworks. This research is expected to contribute both academically and practically to the auditing profession in the era of digital transformation.