Artificial Intelligence and Big Data Strategies to Enhance Islamic Banks’ Competitiveness and Sustainable Development - Ahmad Hisham Alnajjar; Majdi Ali Ghaith (Journal of Islamic Monetary Economics and Finance, 2026)
This study investigates the impact of artificial intelligence and big data strategies on Islamic banks' competitiveness and sustainable development in Jordan, employing an integrated theoretical framework combining the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT). The research targets 487 managers and department heads from 15 Islamic banks, with a sample size of 214 participants selected through stratified random sampling. It employs a quantitative cross-sectional design, using PLS-SEM for data analysis. The findings reveal that AI implementation, big data analytics capabilities, and data management practices are significantly and positively associated with both bank competitiveness and sustainable development performance. Employee digital competency significantly affects competitiveness but shows no significant impact on sustainable development performance. The results provide valuable implications for banking executives, policymakers, and practitioners in implementing digital transformation strategies. The study contributes to the existing literature by integrating technological capabilities with Islamic banking principles, offering a comprehensive framework for understanding digital transformation in religious-based financial institutions. The originality of this research lay in its examination of the combined effects of AI and big data strategies in Islamic banking, particularly in the Middle Eastern context, while considering both competitive and sustainable development outcomes.