Identifying Opportunities and Challenges of AI-Based Decision-Making in Auditing Using the Grounded Theory Method
نویسندگان
1 Associate Professor, Department of Accounting, Ker.c., Islamic Azad University, Kermanshah, Iran
2 Assistant Professor, Department of Accounting, Ker.c., Islamic Azad University, Kermanshah, Iran
3 Assistant Professor, Department of Accounting, Ker.c., Islamic Azad University, Kermanshah, Iran
4 PhD Student, Department of Accounting, Ker.c., Islamic Azad University, Kermanshah, Iran
doi
10.22034/ijfma.2025.78409.2249چکیده
AbstractBased on conducted research, accounting and auditing researchers believe that artificial intelligence (AI) techniques can be used to achieve significant advancements in auditing. The aim of this study is to explain the opportunities and challenges of AI-based decision-making in the auditing process. This research is exploratory and developmental in nature. To achieve this, after interviewing 15 experts familiar with the subject, opportunities and challenges were identified, measured, ranked, and ultimately modeled into six main categories. Grounded theory was used for identification, the fuzzy Delphi method for measurement, and the analytic hierarchy process for ranking. The findings revealed that the challenges and opportunities of AI-based decision-making in the auditing process include skills and knowledge, implementation strategies, risk management, automated error detection, data interpretability, and big data analysis. This research holds value for auditors and researchers in creating frameworks for the use of AI in auditing, which should be considered by professional planners and governments
