The Future of Education

Bibliometric review critically examines the intellectual structure and evolving research trends surrounding the application of Artificial Intelligence (AI) in teaching reading, with a specific focus on personalisation, accessibility, and learning outcomes. Drawing on data from leading academic databases, the study employs bibliometric techniques to map publication trajectories, identify influential authors, analyse high-impact journals, and explore patterns of international collaboration. The findings indicate a significant increase in scholarly output over recent years, reflecting the growing importance of AI-driven technologies in education. Thematic analysis reveals that tools such as natural language processing, adaptive learning systems, and intelligent tutoring systems are central to enabling personalised learning pathways, enhancing learner engagement, and improving reading comprehension. Furthermore, the review highlights a strong and emerging emphasis on accessibility and inclusive education, particularly for multilingual learners and students from diverse socio-economic backgrounds. Despite these advancements, the study identifies critical gaps in literature, including limited attention to ethical considerations, persistent digital inequalities, and insufficient longitudinal evidence on learning outcomes. The analysis also uncovers distinct research clusters that signal future directions, particularly in integrating AI responsibly and sustainably within reading education. Overall, this study provides a comprehensive synthesis of the knowledge base, offering valuable insights for researchers, educators, and policymakers seeking to leverage AI for improved reading instruction.