Abstract
The rapid adoption of artificial intelligence (AI), particularly generative artificial intelligence (GenAI) tools such as ChatGPT, has introduced profound opportunities and challenges for higher education. This paper presents a thematic scholarly review of recent empirical studies, systematic reviews, and conceptual analyses examining AI’s impact on teaching, learning, assessment, and institutional practice. The literature highlights substantial benefits associated with AI use, including increased academic productivity, personalized and adaptive learning pathways, enhanced accessibility for diverse learners, and new opportunities for pedagogical innovation. At the same time, significant risks emerge related to cognitive offloading, erosion of critical thinking, academic integrity, blurred authorship, assessment validity, algorithmic bias, and inequitable access. Findings consistently demonstrate that AI’s educational value is highly context dependent and shaped by pedagogical design, ethical framing, and institutional readiness rather than by the technology itself. Blanket prohibitions and surveillance driven approaches are widely critiqued as ineffective and inequitable. Instead, the literature supports proactive, context sensitive integration grounded in AI literacy, assessment redesign, transparent governance, and sustained human oversight. The review concludes that higher education’s central challenge is not whether to adopt AI, but how to shape its use in ways that preserve intellectual rigor, ethical integrity, and the core educational mission of universities.
Recommended Citation
McCleskey, Jim A.
(2026)
"Current Research on the Use of AI in Higher Education,"
Southwestern Business Administration Journal: Vol. 23:
Iss.
1, Article 2.
Available at:
https://digitalscholarship.tsu.edu/sbaj/vol23/iss1/2
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