An Analytical Study of the Role of Artificial Intelligence in Individualized Learning and Student Participation in India

Artificial intelligence (AI) is increasingly proposed to deliver individualized learning at scale, yet evidence from India, where classrooms are large, heterogeneous and unevenly digitized, is fragmented and rarely examines student participation as the mechanism linking AI to learning. This study applies an integrative review design to (i) international and Indian research on AI-enabled individualized learning and student engagement, (ii) India's policy and platform ecosystem, and (iii) official school digital-infrastructure indicators from the Unified District Information System for Education Plus (UDISE+) for 2022-23 to 2024-25. A conceptual framework linking AI affordances, individualization mechanisms and the behavioral, emotional and cognitive dimensions of engagement is developed, and five testable propositions are derived. The findings indicate that intelligent tutoring and adaptive systems yield moderate-to-large learning gains in controlled studies and that Indian experimental evidence is encouraging. Readiness, however, is sharply uneven: computer and internet facilities were reported in 64.7% and 63.5% of schools in 2024-25, and only 34% of government schools with Classes VI and above reported ICT labs. Infrastructure, teacher capacity, vernacular content, data governance and equity safeguards emerge as binding constraints. The study contributes a participation-centered framework, a state-level readiness diagnosis and a staged policy and research agenda. Because it relies on secondary evidence, the propositions require empirical testing.