In recent years, the use of artificial intelligence in the banking system has become essential for enhancing efficiency, reducing costs, and improving customer experience. The rapid development of digital technologies has compelled banks to reassess traditional processes and adapt to modern tools. This study employs a sequential exploratory mixed-method research approach. In the first phase, a qualitative approach was used, conducting semi-structured interviews with 12 experts from the banking industry. Through thematic analysis, 314 basic themes, 22 organizing themes, and 2 global themes were extracted. In the second phase, a quantitative approach was adopted, using a questionnaire survey and importance-performance analysis to prioritize the identified opportunities and challenges.
The findings of the study reveal 12 key opportunities and 10 major challenges in the AI-driven transformation of Iran’s banking system. Among the most significant opportunities are personalized banking services, the use of AI-powered chatbots for customer support, and anomaly detection and fraud prevention in transactions. On the other hand, regulatory frameworks, data privacy and security concerns, data accessibility, quality and integration issues, and the migration and shortage of skilled professionals are identified as the most critical challenges facing banks in this domain. The findings of this research can assist policymakers and banking executives in formulating effective strategies for the optimal utilization of artificial intelligence.