Artificial Intelligence (AI), as a byproduct of a profound technological paradigm shift, has necessitated a conceptual reassessment across numerous disciplines. Enhanced data processing capabilities, the proliferation of big data analytics, and the widespread adoption of machine learning techniques facilitate the execution of auditing activities with greater comprehensiveness, velocity, and efficacy. Auditing stands at the forefront of these fields. Beyond serving as a supportive instrument, AI is evolving into a strategic component within decision-making mechanisms. As a consequence of digital transformation in auditing, various approaches targeting the analysis of vast datasets have emerged, elevating the significance of activities such as continuous auditing and instantaneous, real-time reporting. From this perspective, AI-powered auditing tools provide users with substantial advantages in risk assessment and the mitigation of potential risks.

The primary objective of this research is to evaluate the impacts induced by AI in auditing, delineate the resulting transformations, and provide a detailed exposition of its contributions to firms operating within this sector while prognosticating the future of the profession. By examining the impacts of AI on auditing through a multidimensional lens, this study aims to scrutinize the opportunities it presents. Furthermore, the utilization of AI in auditing is investigated from the perspectives of both external (independent) and internal audit.