Digital Transformation in the Audit Process: A Systematic Review of Innovation, Challenges, and its Impact on Audit Quality

Abstract

The rapid advancement of digital technologies has driven a fundamental transformation in auditing practices, shifting from manual, sampling-based methods toward automation and data analytics. Although innovations such as Artificial Intelligence, Big Data Analytics, Blockchain, Cloud Computing, and Robotic Process Automation have been introduced, a comprehensive understanding of their applications, challenges, and impacts on audit quality remains limited. This study aims to (1) identify digital innovations applied in the audit process, (2) analyze key challenges in their implementation, and (3) evaluate the impact of digital transformation on audit quality in terms of effectiveness, efficiency, transparency, accuracy, and timeliness. The research employs a systematic literature review (SLR) using the PRISMA protocol and the PICOC framework, covering 84 academic articles published between 2015 and 2025. Data were analyzed through thematic synthesis and narrative synthesis. Findings reveal that AI and data analytics dominate digital audit innovations, while Blockchain enhances transparency and RPA accelerates routine procedures. Key challenges include limited IT infrastructure, organizational resistance, auditors’ skill gaps, and a lack of specific regulations for digital auditing. Nevertheless, digital transformation significantly improves accuracy, efficiency, and real-time anomaly detection, although issues of data integrity and professional ethics persist. Digital transformation enhances audit quality and repositions auditors as strategic partners within organizations. However, its success largely depends on technological readiness, human capital competence, and adaptive regulatory frameworks.