The increasing digitalization of organizations has elevated the importance of automated audit tools in strengthening audit quality within information systems environments. Despite their growing relevance, research on how these tools influence audit outcomes remains fragmented. This study aims to systematically review empirical evidence on the adoption of automated audit tools and their effect on audit quality. Using PRISMA guidelines, 36 eligible studies, published between 2015 and 2025 were analyzed across major scientific databases. The review found that automated tools such as Computer-Assisted Audit Techniques (CAATs), data analytics, Artificial Intelligence (AI), blockchain, and Robotic Process Automation (RPA) significantly enhance audit accuracy, fraud detection, efficiency, and internal control reliability. However, adoption is shaped by organizational support, auditor IT competence, perceived usefulness, and technological readiness, while challenges include skill gaps, high costs, system risks, and limited regulatory guidance. The study concludes that automated audit tools are essential for improving audit quality and calls for greater investment in digital capabilities to support their effective implementation.