The Impact of Artificial Intelligence Applications on Enhancing the Efficiency and Effectiveness of Internal Auditing in Iraqi Banks

Abstract

This study aimed to demonstrate the impact of artificial intelligence (AI) applications on enhancing the efficiency and effectiveness of internal auditing in Iraqi banks, in light of the rapid digital transformations occurring in the banking sector. The study adopted a descriptive-analytical approach and used a questionnaire as the primary data collection tool. The questionnaire was administered to a sample of 60 internal auditors and employees working in the financial, supervisory, and administrative departments of several Iraqi banks.

The data were analyzed using SPSS software, employing descriptive and inferential statistical methods such as the arithmetic mean, standard deviation, Pearson correlation coefficient, and simple linear regression analysis. The results showed a statistically significant positive correlation between AI applications and the efficiency and effectiveness of internal auditing, as well as a significant positive impact of these applications on improving audit performance.

The study concluded that the adoption of AI applications by Iraqi banks contributes to raising the quality of internal audit work, strengthening oversight, and improving the ability to detect errors and risks. It also emphasized the importance of providing the necessary technological infrastructure and developing the skills of human resources to achieve optimal utilization of these applications.