Artificial Intelligence Adoption in Islamic Banking: Investigating the Effects of AI Transparency, Shariah Compliance, Customer Trust, and Customer Satisfaction
DOI:
https://doi.org/10.71317/jgst.2.7.2026.228Keywords:
AI Transparency, Shariah Compliance, Customer Trust, Customer Satisfaction, Islamic Banking, PLS-SEM, Explainable AIAbstract
The integration of Artificial Intelligence (AI) in Islamic banking presents unique challenges regarding technological acceptance and religious adherence. This study investigates the impact of AI transparency and perceived Shariah compliance on customer satisfaction, examining the mediating role of customer trust within the digital Islamic finance context. Adopting a quantitative, cross-sectional research design, data were collected from 412 retail customers who had actively used AI-powered banking services within the preceding six months. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the proposed conceptual model. Results indicate that both AI transparency (β = 0.185, p < 0.001) and perceived Shariah compliance (β = 0.248, p < 0.001) significantly enhance customer satisfaction. Furthermore, customer trust serves as a significant partial mediator, channeling the effects of AI transparency (indirect effect = 0.129, p < 0.001) and Shariah compliance (indirect effect = 0.157, p < 0.001) toward satisfaction. The structural model explains 54% of the variance in customer satisfaction and 48% in customer trust. These findings contribute to the literature by integrating technological adoption frameworks with Maqasid al-Shariah and validating trust as a psychological mechanism in algorithmic Islamic finance. Practically, the study underscores the necessity for Explainable AI (XAI) and proactive Shariah governance in AI development to foster cognitive and affective trust, thereby enhancing customer satisfaction in digital Islamic banking.
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Copyright (c) 2026 Rubi Naz, Dr. Mufti Aziz Ur Rehman, Dr. Asiya Khattak (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.



