AI FOR AI AUDIT - THE VISION FROM LEGACY AUDIT TO MULTI LAYERED ARTIFICIAL INTELLIGENCE IN AUDITING

This paper investigates the prospects and difficulties of applying AI in the audit field. It explores the possible benefits of AI in enhancing audit processes, alongside adoption concerns, and provides a rare glimpse into its future evolvement and opportunities. To ensure comprehensive analysis, we applied an innovative multidimensional approach, implementing exploratory viewpoints through a new AI-Audit evolution framework, including a forward-looking perspective. The analysis includes implications applicable for audit professionals and the audit ecosystem, offering a holistic view that goes far beyond mere technical issues. AI holds the potential to transform auditing by improving the effectiveness and quality of audit processes while reducing costs and streamlining operations. However, we emphasize the need for empirical evidence to gain a deeper understanding of AIs broader impact on enterprise outcomes, particularly for its future evolvement. Unlike other only exploratory reviews, we introduce an innovative concept of AI for AI-Audit, proposing an encompassing layer on top of current AI-based auditing tools. This new vision extends beyond contemporary practices that mimic human-like auditing, suggesting a more integrated AI system to improve contemporary audit outcomes. Alongside these advantages, we point to the necessity of empirical research to reassess AIs impact on audit quality and the overall transformation of the audit field, where ethical concerns and human oversight remain critical. While AI can significantly enhance auditing procedures, streamline processes, and affect audit-related costs, its adoption requires careful ongoing ethical monitoring. Finally, AI transformation in auditing raises questions about future auditor roles and the ethical implications of reduced human oversight, making compliance with ethical standards and maintaining human involvement essential.