This study examines the development of Artificial Intelligence (AI) research in Islamic finance and analyses its regulatory and institutional implications for central banks and financial supervisory authorities. Specifically, the study maps scholarly trends on AI-enabled Islamic finance and assesses regulatory strengths, weaknesses, opportunities, and threats faced by public financial authorities in governing AI adoption. Using bibliometric analysis of Scopus-indexed publications from 2017 to 2024, the study identifies research trends, key contributors, institutional affiliations, and thematic evolution in this field. The findings show a steady increase in scholarly output, with 47 publications over the past decade, led by authors including Shahnawaz Khan and Mohammad Irfan, and significant contributions from institutions in Malaysia and Bahrain. Topic mapping reveals that AI adoption in Islamic finance is increasingly associated with innovation, blockchain integration, and sustainable development, raising significant regulatory concerns. To support this objective, a SWOT analysis is employed and reframed as a regulatory and institutional assessment that evaluates how central bank innovation mandates and supervisory instruments constitute strengths and opportunities, while legal uncertainty, algorithmic bias, data protection, and supervisory capacity represent key weaknesses and threats. The study concludes that although AI holds substantial potential to enhance efficiency and governance in Islamic finance, its effective deployment depends on coherent regulatory frameworks, strengthened coordination between central banks and Sharia authorities, and sustained capacity-building to manage emerging legal and institutional risks.
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