INFLUENCE OF ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: TRANSFORMING TEACHING, LEARNING, AND INSTITUTIONAL PRACTICES
TL;DR
The evidence indicates meaningful potential for personalization, timely feedback, accessibility and operational efficiency, but also identifies risks involving inaccurate output, academic integrity, algorithmic bias, data privacy, unequal access and insufficient faculty preparedness.
Abstract
Artificial Intelligence (AI) is reshaping higher education through adaptive learning, intelligent tutoring, generative tools, learning analytics, research assistance and administrative automation. This structured narrative review synthesizes recent academic and institutional literature on the influence of AI on teaching, learning, research and university management. The evidence indicates meaningful potential for personalization, timely feedback, accessibility and operational efficiency, but also identifies risks involving inaccurate output, academic integrity, algorithmic bias, data privacy, unequal access and insufficient faculty preparedness. The review argues that AI should augment rather than replace educational judgment. Sustainable adoption requires clear governance, transparent assessment rules, faculty and student AI literacy, data protection, human oversight and regular evaluation of accuracy and equity. The paper also identifies the need for longitudinal research on learning outcomes and discipline-specific implementation.