The role of artificial intelligence in supporting internal auditors to reduce financial and administrative corruption

This study explores the role of Artificial Intelligence (AI) in enhancing the effectiveness of internal auditing to reduce financial and administrative corruption. In the digital era, AI has emerged as a transformative tool capable of analyzing vast datasets, detecting anomalies, and supporting evidence-based decision-making—thereby strengthening institutional oversight and governance. The research examines three key dimensions through which AI can influence audit performance: independence and objectivity, competence and professional capabilities, and methodology and work procedures. A structured questionnaire was distributed to internal auditors across selected institutions, and data were analyzed using SPSS to assess reliability (Cronbach’s α) and inter-dimensional correlations.\r\nResults revealed that AI significantly enhances auditors’ independence (Mean = 3.91, α = 0.817), competence (Mean = 3.86, α = 0.724), and methodological efficiency (Mean = 3.78, α = 0.780). Moderate positive correlations were found among these dimensions (r = 0.221–0.364, p < 0.05), indicating that AI’s impact operates through interconnected improvements in professional practice. These findings confirm that AI supports a proactive, data-driven auditing environment that can improve transparency and early detection of irregularities.\r\nThe study concludes that AI integration is not merely a technical upgrade but a governance necessity that empowers internal auditors to effectively mitigate corruption risks. It recommends developing AI-based audit infrastructures, continuous auditor training, and regulatory frameworks to ensure ethical and effective AI use in auditing.\r\n