This study examines how Artificial Intelligence (AI) enhances Sharia compliance within Islamic Financial Institutions (IFIs) by improving operational efficiency, ensuring transparency, and addressing ethical and technical challenges. A quantitative survey across five Saudi regions resulted in 450 validated responses, analyzed using descriptive statistics, ANOVA, and regression models. The findings reveal that while AI significantly enhances transparency and compliance processes, its impact on operational efficiency is limited. Key barriers include high implementation costs, insufficient structured Sharia datasets, and integration complexities. Regional and professional differences further underscore the need for tailored adoption strategies. It introduces a novel framework integrating ethical governance, Sharia compliance, and operational scalability, addressing critical gaps in the literature. It offers actionable recommendations for AI adoption in Islamic finance and contributes to the global discourse on ethical AI practices. However, the Saudi-specific focus highlights regional dynamics that may limit broader applicability. Future research could extend these findings through cross-regional comparisons to validate and refine the proposed framework. By fostering transparency and ethical governance, AI integration aligns Islamic finance with socio-economic goals, enhancing stakeholder trust and financial inclusivity. The study emphasizes the need for targeted AI training, the development of structured Sharia datasets, and scalable solutions to overcome adoption challenges.

Many studies have called for more research and increased knowledge about Family Businesses (FB), notably their sustainability. This work aims to reduce this limitation through a narrative literature review and thus contribute to knowledge about FB’s compliance and sustainability design. The results suggest that interest in sustainability practices is growing but still low, and implementation is challenging. This work presents scientific contributions, notably to the Theories of Vision Based on Resources, Dynamic Capabilities, and Stewardship. At the same time, it contributes to the operationalization of FB, as they can design their sustainability practices and compliance strategies similar to those of others. The value of this work culminates in the original proposal of a framework identifying the leading information representative of the main challenges for the sustainability of FB.