<![CDATA[This research paper explores the difficulties faced by the implementation of Artificial Intelligence in audit work and its impact on audit quality. The overall goal of the research is to gain a holistic view of the impact of AI on auditing practice and its resulting technical, ethical, regulatory and professional challenges. This study is carried out using Systematic Literature Review (SLR) approach, which uses relevant articles found in Scopus, Web of Science and Google Scholar databases. The results show how Artificial Intelligence can use advanced data analytics and automation technologies to improve audit efficiency, fraud detection, continuous auditing, and risk assessment. But, there are data quality problems, legacy systems, algorithm transparency limitations, cybersecurity issues, regulatory uncertainty and inadequate auditor competencies to limit implementation of Artificial Intelligence. The study also shows that AI transforms the auditor's job from procedural tasks to analyzing the content and exercising professional judgement. The novelty of this research emerges from the integrative analysis, which is new to the study, and integrates several technology, ethical, regulatory and competency aspects into a single framework for the understanding of the adoption of Artificial Intelligence in auditing. The study suggests that the implementation of Artificial Intelligence in the audit process should be balanced, combining technological innovation, ethical governance, professional expertise, and institutional readiness for it to provide an effective, sustainable improvement in audit quality.]]>
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