THE EXTENT OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IMPACT ON AUDIT EVIDENCE-AN EXPLORATORY STUDY ON A SAMPLE OF AUDITORS AT THE UNIVERSITY OF MOSUL

Abstract

Technological advancement has significantly influenced various industries, and one of them is auditing because artificial intelligence technologies are progressively used for multiple purposes. Key to the transformation of evidence collection and assessment is the promise that AI seemingly offers in this regard. This study is exploratory research which investigates the AI impact on audit evidence practices using a sample of auditors at University of Mosul. We use a mixed methods approach that includes qualitative interviews with auditors to understand their perceptions and experience working with AI-embedded tools, along with a broad quantitative survey designed to capture the ubiquity and types of various audit evidence gathering technologies. 50 questionnaires were distributed to the research sample consisting of auditors at the University of Mosul, and the SPSS statistical program was used to reach conclusions. Overall, our findings indicate that AI’s adoption in auditing is still nascent and far from pervasive; however, it is already having an impact on how auditors deal with evidence. In particular, AI allows them to examine additional data sources at a scale unheard of before and assures the feasibility of continuous audits including identifying more anomalies prevalent in audit data points "Challenges, on the other hand, remain with respect to validating the dependability of such AI-produced audit evidence. In twain subjects, this con-over presents a precious concomitatement to the escalating compute of elimination on the movables of AI in auditing. It provides an initial account of the current use of AI for audit evidence in a single university and link to explore later work on AI’s transforming effects on exam practices. The findings of this research could be beneficial to accounting firms, regulators, and educators seeking to gain a better understanding of the potential opportunities and risks associated with AI in respect of audit evidence.