From Digital Divide to AI Divide: A Sociological Study of Educational Inequality in Indian Higher Education

Abstract The rapid diffusion of Artificial Intelligence (AI) tools into higher education has introduced a new axis of inequality that extends beyond the conventional “digital divide.” While earlier scholarship focused on disparities in internet connectivity and device ownership, this study argues that access alone no longer captures the full picture of educational inequality in the AI era. It proposes the concept of an “AI Divide” — a multidimensional gap encompassing who has access to AI tools, who possesses the digital literacy to use them effectively, who derives genuine academic benefit, and how these disparities generate new forms of exclusion. Situated within Indian higher education — a context marked by significant socioeconomic, regional, and institutional diversity — the study draws on a randomly sampled cohort of 111 students to examine AI tool adoption, competence, and perceived academic impact. It investigates the factors shaping unequal access, disparities in skills required for effective academic use, variation in reported academic benefit, and the mechanisms through which AI adoption creates or reinforces existing educational inequalities. Drawing on the sociology of education and digital-inequality literature — including cultural capital, the “second-level digital divide,” and algorithmic literacy — this research moves the discourse from a binary understanding of access to a nuanced analysis of usage, skill, and outcome disparities, contributing to policy discussions on equitable AI integration in the Global South.