Personalized Learning through Artificial Intelligence:  Opportunities, Risks, and Policy Perspectives

Lazar Stošić; Aleksandar Radonjić; Olja Krčadinac; Borivoje Baltezarević; Olga Mikhailova

doi:10.23947/2334-8496-2025-13-2-541-549

Authors

Lazar Stošić Faculty of Informatics and Computer Science, University Union—Nikola Tesla, Belgrade, Serbia; Don State Technical University, Rostov-on-Don, Russian Federation https://orcid.org/0000-0003-0039-7370
Aleksandar Radonjić Faculty of Informatics and Computer Science, University Union—Nikola Tesla, Belgrade, Serbia; Institute of Technical Sciences of the Serbian Academy of Sciences and Arts: Belgrade https://orcid.org/0000-0003-3715-468X
Olja Krčadinac Faculty of Informatics and Computer Science, University Union—Nikola Tesla, Belgrade, Serbia https://orcid.org/0000-0002-6299-371X
Borivoje Baltezarević The Institute for Serbian Culture Priština – Leposavić, Serbia https://orcid.org/0000-0002-6798-6981
Olga Mikhailova Department of Psychology and Pedagogy, Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University), Moscow, Russian Federation https://orcid.org/0000-0001-5046-1452

DOI:

https://doi.org/10.23947/2334-8496-2025-13-2-541-549

Keywords:

artificial intelligence, personalized learning, education policy, algorithmic ethics, adaptive learning systems

Abstract

Artificial Intelligence (AI) is redefining the landscape of personalized education by enabling adaptive systems that respond dynamically to individual learning needs. This paper explores how AI technologies-including machine learning, big data analytics, and intelligent tutoring systems-support the transformation of pedagogical models. Key opportunities discussed include real-time personalization of content delivery, increased student motivation, and inclusive learning environments. At the same time, the study critically examines potential risks, such as data privacy concerns, algorithmic bias, and the erosion of human-centered pedagogy. Policy implications are addressed with recommendations for regulatory frameworks to ensure ethical and responsible AI integration into education. The paper emphasizes the need for empirical research to validate AI-driven models in diverse educational settings. By aligning technological innovation with humanistic values, the paper contributes to ongoing discourse on how AI can support-not supplant-the role of educators. The findings provide a foundation for future research and policy design aimed at creating equitable, transparent, and effective personalized learning ecosystems.

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