Audit Quality in the Digital Era: A Systematic Analysis of the Use of AI and Data Analytics in Auditing

Abstract

This study reviews the development and application of Artificial Intelligence (AI) and Data Analytics in auditing and their impact on audit quality in the digital era. Using a Systematic Literature Review (SLR) based on the PRISMA framework, 45 peer-reviewed articles published between 2019 and 2025 were analyzed thematically. The findings show that AI and Data Analytics enhance audit quality by improving fraud detection, increasing efficiency through automation, and strengthening audit evidence reliability. However, effective adoption depends on auditors' technological competence, digital infrastructure readiness, and robust governance frameworks. The review also identifies research gaps, including limited longitudinal studies, insufficient evidence in the Indonesian context, and a lack of focus on ethical governance and return on investment. This study provides insights for auditors, audit firms, and regulators to support accountable and sustainable audit digitalization.