Artificial Intelligence (AI) is fundamentally reshaping the landscape of higher education, transitioning from a supplementary tool to a core driver of pedagogical innovation, administrative efficiency, and research acceleration. This paper provides a comprehensive analysis of AI's tripartite impact on the academic ecosystem, examining its role in enabling hyper-personalized learning through adaptive platforms and intelligent tutoring systems, revolutionizing student success initiatives via predictive analytics, and transforming research methodologies. Simultaneously, the paper critically investigates the profound ethical, practical, and philosophical challenges this integration poses, including algorithmic bias, the redefinition of academic integrity in the age of generative AI, data privacy concerns, and the evolving role of educators. Through a mixed-methods approach incorporating a systematic literature review, institutional case studies, and original survey data, this research identifies key implementation archetypes and success factors. It argues that the most effective adoptions follow a "pedagogy-first" framework, where technology is deployed to enhance clearly defined learning objectives and human relationships rather than replace them. The study further proposes a Cyborg Pedagogy Framework to conceptualize the synergistic partnership between human intuition and machine intelligence, and a Participatory Ethics Protocol for the responsible development and deployment of educational AI.
Tingare Shailaja Arvind (Thu,) studied this question.
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