THE MEDIATING ROLE OF AI-ENABLED INTERNAL CONTROL EFFECTIVENESS VIA ARTIFICIAL INTELLIGENCE UTILIZATION AND SUSTAINABLE AUDIT QUALITY IN POWER ENGINEERING PROJECTS

With the growing scale and complexity of large-scale power engineering projects, traditional audit approaches face increasing challenges in supporting continuous governance and risk management. Although artificial intelligence has been widely introduced into auditing practices, the mechanisms through which it contributes to sustainable audit quality remain insufficiently understood. This study examines how artificial intelligence utilization influences sustainable audit quality through the effectiveness of artificial intelligence–enabled internal controls. Using survey data collected from participants involved in large-scale power engineering projects in China, this study applies structural equation modeling to analyze the relationships among artificial intelligence utilization, internal control effectiveness, and sustainable audit quality. The results show that artificial intelligence utilization has a significant positive impact on sustainable audit quality. In addition, artificial intelligence utilization enhances the effectiveness of internal controls, which in turn contributes to improved audit quality. Further analysis confirms that internal control effectiveness partially mediates the relationship between artificial intelligence utilization and sustainable audit quality.These findings indicate that artificial intelligence enhances sustainable audit quality not only through direct technological effects but also by strengthening internal control execution as a governance mechanism. This study contributes to the literature on artificial intelligence–enabled auditing and provides practical insights for improving audit governance in large-scale engineering projects.