<![CDATA[The transformation of academic quality assurance in higher education is rapidly advancing with the rise of artificial intelligence (AI). This article reviews 41 peer-reviewed articles published between 2022 and 2025 to examine AI implementation in quality assurance across three dimensions: (1) the use of AI in monitoring and evaluation, (2) governance of academic integrity in the AI era, and (3) institutional readiness for technological change. Findings indicate that successful AI adoption depends on balancing technological effectiveness, ethical clarity, and adaptive, human-centred institutional support. While AI enhances efficiency in evaluation and adaptive assessment, challenges such as algorithmic bias, uneven staff capacity, and reactive policy frameworks persist. As a conceptual contribution, this article proposes an AI-based quality assurance framework comprising four components: automated and ethical evaluation, adaptive governance, human-centred institutional support, and AI–pedagogy alignment. Together, these components foster a reflective, collaborative, and sustainability-oriented academic quality ecosystem, while emphasising ethical values, local contexts, and institutional capacity-building. This study provides an early conceptual foundation for more responsive AI-informed quality assurance systems.]]>
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