AI Divide in Education: A systematic review of the role of Socioeconomic status, Geography, and Educational Institutions.

Abstract

Artificial Intelligence (AI) is reshaping educational landscape by making learning more personalized, academic tasks more automated, and education more technologically advanced. But despite advancements, in terms of access to AI resources and tools, it can potentially result in digital divide among students. The current study addresses the role of socio-economic stratification, geographic disparity, and educational institutional constraints in creating AI Divide in education. To evaluate the current state of literature, systematic literature review was conducted to identify themes and trends. Rigorous selection process involving 86 records, published between 2020- 2025, and focused on 1^st level of digital divide (theory) literature, from databases such as Web of Science, Scopus, and google scholar was carried out. Using thematic analysis approach, various themes and subthemes identified in the study include high and low socio-economic status, free and paid AI tools, rural and urban divide, global north and global south countries, wealthy and private, and underfunded and government educational institutions. The findings reveal that students belonging to high socio-economic status and are enrolled in private wealthy educational institutions in the developed countries have better access to AI resources in education. In contrast, students from low socio-economic status lack financial resources, infrastructure, and institutional support to access AI resources. This difference results in digital divide in terms of access to digital technologies and AI tools. Consequently, it creates AI divide in education and exacerbates educational inequalities.