<![CDATA[This study aims to examine the role of artificial intelligence as a driver of innovation in contemporary auditing practices. The research method used is a Systematic Literature Review (SLR) of reputable scientific articles obtained from the Scopus, Web of Science, and Google Scholar databases. The literature selection process was carried out systematically through the stages of identification, screening, eligibility, and inclusion. The results of the study show that the application of AI in auditing can improve the efficiency, accuracy, and quality of audits, particularly in data processing, risk assessment, and anomaly detection. However, the implementation of AI still faces challenges in the form of human resource readiness, data quality and security, as well as ethical and regulatory issues. This study emphasises that the successful integration of AI in auditing requires technological support, auditor competence, and an adequate regulatory framework.]]>
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