Artificial Intelligence in Higher Education: A Critical Analysis in the Context of India’s National Education Policy (NEP) 2020

Abstract

Artificial Intelligence (AI) is poised to transform higher education systems in developing countries by enabling personalized learning, improving institutional governance, and accelerating research productivity. India’s National Education Policy (NEP) 2020 explicitly foregrounds technology as a lever for improving access, quality, and equity in higher education, and proposes institutional mechanisms (e.g., the National Educational Technology Forum) that can facilitate AI adoption. However, meaningful integration of AI requires confronting persistent challenges in the Indian context—digital infrastructure gaps, uneven faculty capacity, data governance deficits, and risks of algorithmic bias—that can undermine equity and trust. This paper examines the intersection of AI and higher education in India through the policy prism of NEP 2020. Drawing on policy documents, international guidance, and recent empirical and review literature, it (a) maps current and emerging AI applications across teaching, assessment, administration, and research; (b) synthesizes evidence on pedagogical and institutional impacts; and (c) articulates policy and institutional pathways to align AI deployment with NEP 2020 objectives of inclusion, academic autonomy, and research excellence. We argue that realizing NEP 2020’s vision requires a layered approach: national stewardship for standards and open infrastructure; institutional investment in capacity building and ethical governance; and the co-design of AI tools with educators and students to ensure cultural and pedagogical fit. The paper concludes with actionable recommendations for policymakers, university leaders, and educational technology developers to promote responsible, contextually appropriate AI ecosystems in Indian higher education. (≈200 words)