AI-Driven Shariah-Compliant Investment Platforms and Adoption Intention Among Muslim Retail Investors: A Systematic Review of Technology Acceptance, Algorithmic Transparency, and Compliance Trust

Islamic financial technology (fintech) adoption. This review examines the behavioral, cognitive, and trust-related factors that determine Muslim retail investors' intention to adopt AI-powered Shariah-compliant investment platforms. The domain spans technology acceptance, Islamic finance, explainable artificial intelligence, and investor financial decision-making. A secondary domain is investor financial wellbeing, operationalized as confidence in Shariah-compliant financial decision-making and reduced uncertainty in halal investment choices. AI-powered Shariah-compliant investment platforms represent an emerging category of Islamic fintech in which algorithmic systems autonomously screen investment assets against Islamic jurisprudence criteria. Despite rapid growth of this sector across Muslim-majority markets, no systematic review has synthesized the empirical literature on user adoption of these platforms. Three specific gaps motivate this review. First, technology acceptance models applied to Islamic fintech — predominantly TAM, UTAUT, and UTAUT2 — have been tested inconsistently across Malaysia, Indonesia, Pakistan, and Bangladesh, with no study conducted in Egypt, the largest Arab economy with over 90 million Muslims. Second, algorithmic transparency has never been empirically operationalized as a measured construct in Islamic finance research, despite repeated conceptual calls for explainable AI in Shariah screening contexts. Third, trust in AI-driven religious compliance determination has not been distinguished from general platform trust or institutional trust in the existing literature. No validated scale separates trust in algorithmic Shariah accuracy from trust in governance oversight from trust in religious outcome authenticity. A systematic review will establish the cumulative state of evidence, resolve construct-level inconsistencies, and provide a validated theoretical foundation for an extended adoption framework applicable to understudied Muslim investor populations. Screening follows PRISMA 2020. Synthesis uses thematic analysis with the TCCM framework. Quality assessment uses MMAT. Protocol registered prospectively before any screening or data extraction. Review team: Dr. Ahmad Yahya Shaheen (PI, AASTMT Egypt), Professor Arshi Naim (WASD UK), Dr. Abdullah Khataan (AASTMT Egypt). Funding: none. Conflicts of interest: none declared.