This study systematically reviews the role of artificial intelligence (AI) in financial audit, identifying the opportunities and challenges posed by the transformation of the profession. Using a systematic literature review (SLR) approach based on the Petticrew and Roberts framework, the study covers empirical research between 2019 and 2024. The review results show that AI contributes to audit efficiency, accuracy, and productivity, primarily through automation of data analysis, anomaly detection, and predictive analytics for risk assessment. Critical factors for successful AI adoption include a robust technology infrastructure and a workforce with adequate analytical-technical skills. Key challenges include data privacy issues, ethics, and the shortage of AI experts in audit. The study also notes a shift in research focus from simply adopting AI to its impact on the role of auditors and audit quality. The findings offer guidance to accounting firms, educators, and regulators in developing policies and curricula that support the integration of AI in audit. The review provides insights for future professionals in navigating a technology-driven audit environment.