AI Adoption in Islamic Finance using Extended TAM Model with Moderation of Shariah Compliance Perception, Perceived Risk, Perceived Trust

Abstract

The unceasing rate of technical advancement that defines the digital era has made a major impact on the direction of the financial industry. One of the fastest-evolving technologies in the world is artificial intelligence. This study examined the relationship between TAM constructs and through an extension of the Technology Acceptance Model (TAM) with perceived risk, perceived trust, and perception of Shariah compliance as moderators, examined the adoption of artificial intelligence (AI) in Islamic banking. We proposed users' Perceived ease of use (PEOU), Awareness towards AI (AWS), and subjective norms (SN) affect perceived usefulness (PU), which in turn affect attitude towards AI (ATT). A positive attitude leads toward behavior intentions (BI) and ultimately continued intention (CI). We also contend that perceived risk of AI (PR), perceived trust in AI (PT), and perception of Shariah compliance (SCP) moderate the effect of PEOU, AWS, SN and PU on ATT, the effect of ATT on BI, and the effect of BI on CI respectively, in a way that higher level of PR, PT, and SCP will make these relationships stronger. This study is carried out as a quantitative, explanatory research technique, statistical data was collected from banking service users through a standardized questionnaire using an online platform in a cross-sectional temporal horizon. The literature is supported by online publications. A total of 350 respondents made up the study's sample size. SmartPLS was used for statistical analysis. The study's empirical findings clarify that all 9 direct hypotheses; perceived ease of use, awareness of AI, subjective norm, and perceived usefulness; all positively impact attitudes, behaviors, and continuance intentions to use AI in the banking industry. The analysis also revealed that all of the 18 moderators' hypotheses from the extension of constructs from the TAM framework, including perceived risk, perceived trust, and Shariah compliance perception, were disproved suggesting that users do not give religious judgment, risk perception, or degree of trust much thought while deciding whether to keep utilizing AI technology in the Islamic banking sector. The conclusions point to the importance of raising acceptability and adoption in Islamic banking by utilizing social influence, raising awareness, and easy-to-use AI solutions. The report provides valuable recommendations to policymakers and practitioners who wish to implement AI technology in a customer-oriented manner, alongside contributing to the growing literature on AI in banking.