This study investigates how emerging technologies, especially Artificial Intelligence (AI) and Big Data, contribute to improving audit quality. By conducting a systematic literature review of Scopus indexed articles published from 2019 to 2024, the research highlights both the opportunities and challenges involved in implementing these technologies within auditing practices. The findings reveal that AI contributes significantly to audit quality by automating repetitive tasks, improving fraud detection, enhancing data analysis, and enabling more informed auditor judgment. Furthermore, the use of AI and digital tools has been shown to increase efficiency and reduce audit costs. Several challenges persist, including ethical concerns, data security risks, technological readiness disparities among audit firms, and a lack of clear regulatory standards. The study synthesizes theoretical and empirical insights using various frameworks such as Agency Theory, Institutional Theory, and the Technology-Organization-Environment framework, offering a multidimensional understanding of AI adoption in auditing. The results underscore the necessity for auditors to adjust to rapidly advancing technological developments while upholding ethical standards and professional skepticism. This study adds to the expanding discussion on the digital transformation of auditing practices by highlighting the balance between technological innovation and audit integrity.