This study aims to explore the application of Artificial Intelligence (AI) in managing financial risks within Islamic finance, ensuring alignment with Sharia principles. The research employs a qualitative approach, utilizing a Systematic Literature Review (SLR) methodology based on the PRISMA framework, analyzing 45 scholarly articles from 2015 to 2024 sourced from databases such as Scopus and Web of Science, alongside primary data from annual reports of leading Islamic banks in Indonesia, Malaysia, and the Middle East. The findings reveal that AI enhances financial risk detection efficiency by 20%, reduces non-performing loans (NPLs) by up to 16.67% as demonstrated by Bank Muamalat Indonesia, and improves market risk management and Sharia compliance. Additionally, AI automates decision-making processes, cutting contract verification time by 25-40%, and supports maqasid al-shariah by optimizing zakat distribution and fostering financial inclusion, with a 15% increase in rural access in Nigeria. Regional case studies highlight Malaysia’s leadership in AI adoption and Indonesia’s challenges with digital literacy, while the Middle East leverages AI for liquidity resilience. The novelty of this research lies in its Sharia-based risk evaluation framework, integrating five dimensions—accuracy, efficiency, compliance, scalability, and social impact—providing a model for practitioners, academics, and regulators. The implications suggest that despite high implementation costs and skill gaps, government incentives and ethical oversight could drive sustainable AI integration, positioning Islamic finance as a competitive alternative in the digital era.