EFEKTIVITAS PENGGUNAAN ARTIFICIAL INTELLIGENCE (AI) DALAM AUDIT INTERNAL

Abstract

This study aims to measure the effectiveness of using Artificial Intelligence (AI) in improving the quality of internal audits in the Asian region. The research focuses on the effectiveness of applying AI in internal auditing, taking into account the benefits, ethical challenges, and potential risks. This qualitative study utilizes a Systematic Literature Review (SLR) method to identify and analyze relevant research published from 2020 to 2025. The data analysis method employed the latest artificial intelligence program, Google Colab. The results show that AI significantly contributes to increasing the effectiveness of internal audit execution. AI is proven to enhance efficiency and accuracy by processing large amounts of data, detecting patterns and anomalies, and mitigating human error. Descriptive statistical analysis across 25 journals indicated that the Risk component (Mean 0.404861) received the most consistent and dominant attention in the literature. However, the study concludes that AI’s long-term benefits outweigh the initial investment and associated risks. Furthermore, AI reinforces ethical aspects, data privacy, transparency, and accountability, while also driving the demand for new auditor competencies.