The role of artificial intelligence in internal audit procedures

Abstract

This thesis examines the relationship between the use of artificial intelligence (AI) and the success of internal control over financial reporting for US-listed companies. Based on the existing theory, we see AI as an advanced tool that can contribute to detecting internal control weaknesses (ICW) in internal audit procedures. Theory shows that there has been quite a lot of research on internal control and ICW. However, little to no research exists on how AI can impact internal audit procedures and ICW. This is why we wanted to investigate and aim to answer the following research question: Is it less likely for a firm to have internal control weaknesses when artificial intelligence is integrated into the internal audit procedures of the company? We predicted a significant relationship between the use of AI and ICW. We use archival data to conduct a univariate and multivariate test consisting of both logistic and ordinary least squares regression models. Our findings provide some empirical evidence that there is a weak significant relationship between the use of AI and the number of weaknesses, meaning that the use of AI is associated with a lower number of weaknesses.