Revolutionizing education through AI-powered personalized learning: A systematic literature review

Transforming education with AI continues to attract public attention in recent times as a viable alternative to traditional learning approaches. This shift reflects growing interest in how AI can provide adaptive, personalized learning experiences that cater for diverse educational needs, enhance engagement, and streamline administrative processes. Educationist, administrators and Information systems (IS) and other related fields’ scholars continue to explore the evolution of these emerging disruptive education innovations. However, there is a lack of systematic overview that focus on the transforming education with AI -driven personalized learning. Thus, the objectives of this work are: (1) to explore the current trends and applications of AI-driven personalized learning across various educational settings; (2) to identify and analyze the challenges associated with implementing AI in education; and (3) to examine potential future research directions for advancing AI-driven personalized learning and addressing identified challenges. The review analyses the existing literature published between the years of 2018 to 2024. This period was chosen because integration of modern AI with personalize learning phenomenon is a relatively new field. The results of the review show that there is an inadequate utilization of universal data privacy and ethical guidelines to ensure safe AI integration in educational environments, also most studies lack detailed utilization of IS theories and methods in reporting their findings. This paper presents challenges of AI integration in educational environments. Finally, the paper concludes by discussing the potential open research opportunities.

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Publication Details

Journal
Multidisciplinary Reviews
Published
2025-08-14
DOI
https://doi.org/10.31893/multirev.2026084
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Revolutionizing education through AI-powered personalized learning: A systematic literature review

Usman Abdullahi, Ahmad Mohamed Martadha, Mohamad Sukeri Khalid, Khadeem Ali Dhahi Al-Amrani
Multidisciplinary Reviews
Online Learning and Analytics
article

Revolutionizing education through AI-powered personalized learning: A systematic literature review

Usman Abdullahi, Ahmad Mohamed Martadha, Mohamad Sukeri Khalid, Khadeem Ali Dhahi Al-Amrani
article en

Abstract

Transforming education with AI continues to attract public attention in recent times as a viable alternative to traditional learning approaches. This shift reflects growing interest in how AI can provide adaptive, personalized learning experiences that cater for diverse educational needs, enhance engagement, and streamline administrative processes. Educationist, administrators and Information systems (IS) and other related fields’ scholars continue to explore the evolution of these emerging disruptive education innovations. However, there is a lack of systematic overview that focus on the transforming education with AI -driven personalized learning. Thus, the objectives of this work are: (1) to explore the current trends and applications of AI-driven personalized learning across various educational settings; (2) to identify and analyze the challenges associated with implementing AI in education; and (3) to examine potential future research directions for advancing AI-driven personalized learning and addressing identified challenges. The review analyses the existing literature published between the years of 2018 to 2024. This period was chosen because integration of modern AI with personalize learning phenomenon is a relatively new field. The results of the review show that there is an inadequate utilization of universal data privacy and ethical guidelines to ensure safe AI integration in educational environments, also most studies lack detailed utilization of IS theories and methods in reporting their findings. This paper presents challenges of AI integration in educational environments. Finally, the paper concludes by discussing the potential open research opportunities.

Multidisciplinary ReviewsVol. 9(2)
Nigerian Defence Academy (NG), Sohar University (OM), Northern University of Malaysia (MY)
Openalex Percentile: Top 70%
Online Learning and Analytics
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Revolutionizing education through AI-powered personalized learning: A systematic literature review — Usman Abdullahi, Ahmad Mohamed Martadha, et al. · Multidisciplinary Reviews (2025) | TGRS Research Map | TGRS