Abstract:

The research focus of this paper is based on the analysis of the application of Data Analytics and Artificial Intelligence in internal auditing, with a particular emphasis on the research gap related to the recent implications of using these modern technologies in internal auditing. The paper examines the reasons for the adoption of these technologies, their impact on the audit process, and the implications of long-term use of Data Analytics and Artificial Intelligence in internal auditing through the lens of the Technology Dominance theory. The research questions are focused on discovering what recent empirical research reveals about internal auditors’ adoption and reliance on Data Analytics and AI at different stages of the audit process; what short-term benefits and challenges of applying Data Analytics and AI does the existing literature identify in the context of internal audit effectiveness, quality, and performance as well as potential long-term implications regarding the use of Data Analytics and AI in internal auditing.