Model Smart Audit System Based Artificial Intelligence in Increase Efficiency and Accuracy of the Audit Process

Abstract

The rapid development of digital technology is driving organizations to adopt audit systems that use Artificial Intelligence (AI) to improve the effectiveness and accuracy of the audit process. This study was conducted to analyze the implementation of an AI-based Intelligent Audit System and its impact on audit time efficiency and the accuracy of audit findings in a modern accounting information system. This study uses a panel data approach covering 98 MSME owners registered with the South Sumatra MSME Cooperative Office during the period 2000–2025, resulting in a total of 2,548 observations (assuming a balanced panel). Data analysis was conducted using multiple linear regression methods to examine the effect of AI implementation in auditing on audit effectiveness. The results of this study indicate that an AI-based Intelligent Audit System has a significant impact on improving the efficiency of the audit process by accelerating transaction analysis, reducing human error, and improving real-time anomaly detection capabilities. Furthermore, it has been shown to improve audit accuracy by utilizing predictive algorithms and data analytics techniques that can provide deeper insights into risky transaction patterns. These findings suggest that integrating AI in auditing can provide a strategic solution for companies to strengthen internal controls, improve the quality of financial reports, and facilitate more accurate decision-making in the digital era.