Generative AI in Higher Education: A Systematic Literature Review of Stakeholder Perspectives, Uses, Risks, and Governance

Abstract

Generative artificial intelligence (GenAI) has become a major teaching, assessment, and governance issue in higher education. This systematic literature review synthesizes 17 peer-reviewed studies published from 2023 to 2025 within an eligible publication window ending March 8, 2026. Guided by PRISMA 2020 principles, the review profiles actor coverage, research designs, reported uses, benefits, risks, assessment implications, and governance responses. The evidence base is educator-focused and dominated by cross-sectional or early empirical studies. GenAI is associated with efficiency gains, feedback support, resource generation, and flexible teaching workflows, but also with assessment validity, academic integrity, hallucinated content, uneven preparedness, and limited policy support. Responsible adoption requires task-level assessment redesign, AI literacy, professional development, and coherent institutional governance.