The aim of this study was to investigate the factors affecting the successful implementation of artificial intelligence in auditing, emphasizing the role of auditors' data analysis skills, institutions' technological maturity, and the quality of information systems. The present study was a descriptive-survey study, and data were collected through a questionnaire from 150 auditors working in reputable auditing firms. Advanced statistical methods such as structural equation analysis and regression were used to analyze the data.
The findings showed that there is a positive and strong relationship between auditors' data analysis skills and the effectiveness of implementing artificial intelligence. A positive and significant relationship was also observed between institutions' technological maturity and the quality of audit outputs. The mediating role of perception of the usefulness of artificial intelligence in the relationship between information system quality and independent use intention was also confirmed. The fit indices of the research model were evaluated as satisfactory.The results show that successful implementation of AI in auditing requires simultaneous attention to three key factors: developing data analysis skills in auditors, upgrading the technological infrastructure of institutions, and improving the quality of information systems. These findings can be a practical guide for audit firms in planning for digital transformation and effective use of AI. Attention to these factors will increase the accuracy, efficiency, and quality of the audit process and pave the way for wider adoption of new technologies in the auditing profession