Reimagining Quality: Artificial Intelligence, Governance, and the Politics of Data in Higher Education

Artificial intelligence (AI) is rapidly reshaping how quality is defined, measured, and governed in higher education. This paper critically examines the cultural and ideological implications of AI integration in educational quality assurance, focusing on Vietnam as a site of contested technological translation. Drawing on Science and Technology Studies (STS), the study explores how algorithmic systems reconfigure traditional pedagogical values, hierarchical relationships, and conceptions of authority – shifting power from professional judgment to data infrastructures. In doing so, AI introduces a new epistemic regime that privileges quantification, predictability, and managerial control, often at odds with local traditions of moral education and dialogical learning. The paper argues that this transition is not merely technological but reflects deeper neoliberal logics and knowledge cultures that increasingly dominate global education policy. Through a mixed-methods approach combining bibliometric mapping, institutional case studies, and practitioner surveys, the research reveals both the promises and frictions of AI-driven quality assurance. Rather than treating AI as a neutral instrument, the paper positions it as a cultural actor that co-produces new forms of governance, visibility, and exclusion. It concludes by calling for more reflexive, participatory, and culturally situated approaches to educational technology.