Trends in the Use of Artificial Intelligence (AI) in Education: A Systematic Literature Review

This study aimed to provide a systematic review of the trends in AI utilisation in education over the past decade (2015–2025). The Systematic Literature Review (SLR) method was employed following the PRISMA protocol, with data sources drawn from four major databases: IEEE Xplore, Scopus, Web of Science, and Google Scholar. The total number of selected and analysed articles offered in-depth insights into various forms of AI implementation, such as intelligent tutoring systems, adaptive learning, educational chatbots, automated assessment, and learning analytics. The findings of the review indicated that AI significantly contributed to personalised learning, educational management efficiency, and early detection of potential academic failure. However, notable challenges also emerged, particularly concerning ethics, data privacy, and algorithmic bias. In addition, technical and social barriers such as the digital divide and resistance from educators continued to hinder the equitable adoption of AI. This review concluded that strategic and ethical approaches were required in the development and implementation of AI in order to ensure greater inclusivity and sustainability. These findings were expected to serve as a foundation for educational policy and future research directions.