The Role of Deep Learning and Machine Learning in Enhancing Internal Audit Efficiency: An Analytical Exploratory Study

Abstract

The study examined the application of artificial intelligence techniques, particularly deep learning and machine learning, in enhancing the efficiency and effectiveness of internal auditing within the Iraqi environment. It aimed to explore auditors’ perceptions of the impact of these technologies on professional skepticism and professional judgment, and their role in improving the quality of audit decisions. The researcher employed a descriptive-analytical approach using a structured questionnaire distributed to a sample of auditors. The results revealed a positive relationship between the use of artificial intelligence techniques and the efficiency of internal auditing, highlighting the importance of organizational leadership and technological readiness in successful implementation. The study recommended developing the technological infrastructure, strengthening auditors’ skills in dealing with AI applications, and establishing governance frameworks that ensure transparency and accuracy in the use of artificial intelligence to support the digital transformation of Iraqi institutions..