The rapid expansion of artificial intelligence within educational systems marks a profound transformation in education as a social institution. The transition from chalkboard-based pedagogy to AI-mediated learning environments has significantly altered the dynamics of teaching, learning, authority, and interaction within classrooms. This paper examines the sociological implications of artificial intelligence in education, focusing on changes in teacher–student relationships, classroom governance, peer interaction, and the increasing role of data-driven decision-making. It argues that artificial intelligence does not function merely as a neutral technological aid but actively restructures power relations through surveillance, algorithmic governance, and the platformisation of education. Drawing upon detailed case studies from India and selected global contexts, including DIKSHA, SWAYAM, Telangana’s AI-enabled educational governance initiatives, and AI-driven learning recovery programs in the United States, the study analyses how artificial intelligence simultaneously expands access to education while deepening existing inequalities related to class, caste, gender, geography, and digital literacy. Situating AI in education within broader structures of capitalism, technocracy, and policy discourse, the paper highlights the urgent need for critical, inclusive, and ethically grounded approaches to AI deployment that prioritise equity, human relationships, and social justice over efficiency and automation.
Bhoje et al. (Sat,) studied this question.