Uneven But Accelerating: AI Adoption in Higher Education

Abstract

Artificial Intelligence (AI) is increasingly recognized as a transformative force in higher education, yet adoption remains patchy and often confined to partial implementations. Using the PRISMA protocol, this study systematically reviews 74 Scopus-indexed articles published between 2015 and 2025. Publication activity rose sharply after 2020, led by contributions from China, the United States, and Saudi Arabia. Across the corpus, Perceived Usefulness and the Technology Acceptance Model (TAM) are the most frequently applied constructs, while ethical and policy dimensions remain underexamined. Thematic analysis delineates five clusters: adaptive learning and personalization; ethics and trust; digital literacy and readiness; AI in assessment and evaluation; and organizational transformation. Despite growing attention, regional gaps persist—especially in developing countries, where constrained infrastructure, funding, and digital literacy impede adoption. To address these challenges, the study proposes a multi-level conceptual framework integrating TAM, UTAUT, TPACK, and TOE to connect individual, institutional, and external factors for sustainable AI-driven education. Overall, the review underscores that AI adoption is not merely an efficiency tool but a strategic lever to advance the Sustainable Development Goals (SDGs), particularly by fostering inclusive, equitable, and innovative higher education systems.

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