Examining the role of artificial intelligence in auditing and fraud detection: The moderating effect of machine learning within accounting information systems

This study investigates how AI and ML influence the efficiency of the Auditing and Fraud detection in AIS in the industrial companies that listed on PEX through (the new postings) at Palestine. A systematic checklist was adopted for obtaining information with quantitative method. The survey was distributed to 766 finance and accounting managers across industries, with a total of 368 useful responses. The questionnaire included demographics and questions for each key sub-construct: AI in AIS adoption, ML features, perceived fit of AI and ML, and effectiveness of audit and fraud detection. Responses were on a five-point Likert scale. Statistical software STATA was applied for analysis of the data including reliability test, descriptive statistics and multicollinearity tests. Cronbach’s alpha for all dimensions was 0.70 and above, reflecting acceptable internal consistency of the measures. The results confirm the positive impact that AI and ML have on the effectiveness of fraud detection and audits. The results may provide analytical evidence for the potential of smart technology in supporting financial audit as well as risk management and demonstrate the innovative prospect of AI – enabled AIS to influence the organization’s governance and control.