SYSTEMATIC REVIEW article
Front. Educ.
Sec. Digital Education
Artificial Intelligence in Education: A Systematic Review of Personalised Learning Trends and Future Directions
Maryam Ikram 1
Shamsiah Banu Mohamed Hanefar 1
Syed Muhammad Umer Saleem 2
Fariha Zulfiqar 3
1. INTI International University, Nilai, Malaysia
2. Ilma University, Karachi, Pakistan
3. The Women University Multan, Multan, Pakistan
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Abstract
Abstract Purpose-The objective of this research is to compile a thorough review of existing literature, highlighting how artificial intelligence and personalised learning have shaped emerging research opportunities. Research Methodology-This study employs the PRISMA review protocol alongside a meta-literature review to analyse pertinent works sourced from the Scopus database, spanning the years 2013 to 2025. Findings - The study examines the progress and deficiencies in the integration of artificial intelligence and personalised learning in education. It underscores a transition in global research priorities from dominant regions such as China, USA and Europe to broader Asia, signaling new opportunities for educational improvement. However, the findings reveal that the swift expansion of AI, combined with persistent concerns about educational standards in developing countries, may create additional institutional pressures that influence the effectiveness of education. Implications-The findings from this review present significant implications for research, practice, and policy. For educators and academic institutions, the results highlight the necessity of professional development that goes beyond technical proficiency, emphasising pedagogical integration and digital literacy. Furthermore, policymakers are urged to develop ethical frameworks for AI implementation in education, addressing critical issues such as data privacy, algorithmic bias, and unequal access. Originality-The significance of this study lies in its effort to bridge a gap in the existing literature by systematically analysing and reviewing research on Artificial Intelligence and Personalised Learning using PRISMA and meta-literature review methodologies. This comprehensive analysis offers researchers a clearer understanding of key developments and emerging trends within the field. Moreover, it identifies promising avenues for future inquiry and serves as a foundational reference for subsequent investigations.
Summary
Keywords
artificial intelligence, Education quality, Meta-literature review, Personalised learning, Systematic Literature Review
Received
11 January 2026
Accepted
20 February 2026
Copyright
© 2026 Ikram, Hanefar, Saleem and Zulfiqar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Maryam Ikram
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.