Pengaruh Independensi, Profesionalisme, dan Kompetensi Terhadap Kualitas Audit Dengan Artificial Intelligence Sebagai Variabel Moderasi

الملخص

This study aims to examine the effects of auditor independence, professionalism, and competence on audit quality, as well as to investigate the moderating role of Artificial Intelligence (AI) in strengthening the relationships between these variables and audit quality. The study is motivated by the growing importance of AI adoption in enhancing the effectiveness and quality of auditing practices in the digital era. A quantitative research approach was employed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The study was conducted among auditors working in 17 Public Accounting Firms (Kantor Akuntan Publik/KAP) located in Yogyakarta, Indonesia. Data were collected through a structured questionnaire and analyzed to examine the relationships among the research constructs. The measurement model assessment demonstrated that all indicators satisfied the required validity and reliability criteria following the sequential elimination of indicators that failed to meet the established thresholds. Furthermore, the structural model exhibited satisfactory predictive and explanatory power, as evidenced by the values of R², Q², and the Goodness-of-Fit (GoF) index. The findings reveal that auditor independence, professionalism, and competence each have a positive and significant effect on audit quality. Moreover, Artificial Intelligence (AI) significantly strengthens the influence of these three factors on audit quality by enhancing the objectivity, efficiency, and accuracy of the audit process. These results suggest that audit quality is determined not only by auditors' internal professional attributes but also by the effective integration of AI technologies into auditing practices. This study provides valuable implications for audit practitioners, higher education institutions, and regulators in promoting higher audit quality in the digital era. It also offers a foundation for future research to expand the geographical scope and incorporate additional variables to achieve a more comprehensive understanding of the determinants of audit quality.