A framework for halal certification compliance: leveraging AI technology to support Malaysian SMEs.

The halal certification process is crucial for ensuring that products in industries such as food, pharmaceuticals, and cosmetics comply with Islamic law and meet the ethical expectations of Muslim consumers worldwide. Despite increasing demand for halal-certified products, Small and Medium Enterprises (SMEs) in Malaysia face significant challenges in obtaining certification due to complex regulatory requirements, high costs, and inefficient manual verification processes. This research aims to develop a comprehensive AI-driven framework to streamline halal certification compliance and ingredient validation, focusing on the Malaysian context. The study employs a qualitative approach to investigate the current halal certification ecosystem. It includes interviews, document analysis, and focus group discussions with primary stakeholders such as SME business owners, halal certification officials, consultants, and IT experts to explore the current halal certification ecosystems. The resulting framework integrates Artificial Intelligence (AI) and Machine Learning (ML) technologies to automate critical processes such as document digitization, predictive compliance analysis, and ingredient verification. By addressing existing bottlenecks, the proposed framework aims to enhance efficiency, accuracy, and scalability in the certification process, enabling greater SME participation and improving Malaysia's competitiveness in the global halal market. The framework will be evaluated through pilot studies and expert reviews to ensure it is practical, effective, and adaptable. This research contributes to the digital transformation of halal certification by providing a scalable AI-driven model that can be applied to other countries facing similar challenges.