Scoping review reveals expanding AI integration across university admissions pipelines, highlighting fundamental shifts in institutional definitions of merit, assessment fairness, and governance.
Artificial Intelligence (AI) is increasingly integrated into higher education admissions systems. This scoping review maps and critically synthesises peer-reviewed research published between 2020 and 2026 on AI in higher education admissions. Following PRISMA-informed search procedures across ERIC, Scopus, and Web of Science, 673 records were screened, and 25 studies met inclusion criteria. Descriptive analysis indicates a rapidly expanding body of research that is predominantly quantitative and geographically concentrated in the United States. Reflexive thematic analysis identifies three interconnected themes: (1) AI used by institutions in admissions systems; (2) AI used by applicants in performance-based assessments; and (3) AI, fairness, and the governance of admissions. The review argues that AI in admissions extends beyond efficiency gains, reshaping how merit is defined, how performance is interpreted, and how fairness is perceived and justified within high-stakes higher education decision-making systems.
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Berna Sena Civan (2026) studied this question.
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