Generative Artificial Intelligence (Gen-AI) has emerged as a transformative tool in enhancing educational practices, particularly in Malay language assessment following the Policy for the Teaching and Learning of Science and Mathematics in English (PPSMI). The ongoing discourse surrounding PPSMI highlights concerns regarding the effectiveness of Malay language assessment, yet the role of Gen-AI in addressing these gaps remains underexplored. This conceptual paper adopts a qualitative approach through a structured review of relevant literature to examine how Gen-AI can support assessment practices in the post-PPSMI context. The findings reveal several key applications, including the translation of technical terminology into Bahasa Melayu, the facilitation of personalized learning through adaptive materials, the provision of real-time linguistic feedback, the generation of multimedia resources for oral assessments, and the rapid development of diverse question banks. Despite these benefits, concerns related to academic integrity, authenticity of students’ work and over-reliance on technology must be addressed. Additionally, issues of infrastructure, digital access, and teacher readiness remain critical. This study provides insights for educators and policymakers in integrating Gen-AI to support more adaptive, inclusive, and sustainable Malay language assessment practices in the digital education landscape.
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