AI-Powered Personalised Learning: Promise and Pitfalls

Deckker, Dinesh and Sumanasekara, Subhashini and Fakhrou, Abdulnaser (2025) AI-Powered Personalised Learning: Promise and Pitfalls. World Journal of Advanced Research and Reviews, 26 (3). pp. 2081-2095. ISSN 2581-9615

The integration of artificial intelligence (AI) into personalised learning is reshaping educational practices by enabling adaptive, learner-centred experiences. This narrative review, structured to synthesise recent empirical and conceptual research (2022–2025), assesses both the transformative potential and the challenges of AI-powered personalised learning. The findings demonstrate that AI can enhance student performance, motivation, and engagement through the provision of real-time feedback, tailored content delivery, and intelligent tutoring systems. Additionally, AI supports teacher efficiency by automating routine tasks and providing data-driven insights. However, the study also highlights pressing concerns, including data privacy, algorithmic bias, lack of explainability, and the erosion of essential human elements in teaching. The review identifies a significant gap in longitudinal and inclusive research, particularly involving underrepresented learner populations. Recommendations are offered for designing ethical, transparent, and inclusive AI systems, while advocating for balanced integration with human pedagogy. This work contributes to a comprehensive understanding of how AI can support learning equitably and effectively in diverse educational contexts.