Artificial Intelligence in Indian Higher Education: Adoption Determinants, Academic Engagement and Learning Motivation Among Generation z — An Integrative Review

Abstract

Purpose: Artificial intelligence has emerged as a transformative force in higher education worldwide; in India, its integration has gained strategic importance through the National Education Policy 2020 and the Digital India initiative (Shabana, 2026). For Generation Z — the first true cohort of digital natives — AI-powered tools such as adaptive platforms, chatbots and generative AI systems are rapidly becoming part of everyday academic life (Alruthaya et al., 2021). This paper presents an integrative review of the literature on AI adoption among Gen Z students in Indian higher education and its relationship with academic engagement and learning motivation. Design/Methodology/Approach: An integrative, thematic review of peer-reviewed studies published between 2019 and 2026 was conducted, informed by recent systematic reviews in the field (Bhutoria, 2022). Evidence was organised into seven themes; an empirically grounded conceptual framework integrating the Technology Acceptance Model, UTAUT2 and self-determination theory is proposed. Findings: Motivation-related constructs — learning interest, achievement goals, self-efficacy and subjective norms — are central drivers of AI adoption (Pasupuleti et al., 2025). AI-integrated tools are significantly associated with academic engagement and performance (Shaikh, 2025). Indian students are simultaneously optimistic about AI's potential and concerned about over-reliance, privacy and academic integrity (Patidar, 2026). Contextual factors (habit, facilitating conditions) outweigh social influence in shaping adoption (Jasrai, 2025; Sudan et al., 2024). Originality/Value: The review proposes an integrated conceptual framework and a ten-point research agenda addressing the underexplored intersections of motivation theory, technology acceptance and equity in Indian AI enabled higher education.