From Individualization to Personalization of Education: Theoretical Aspects and Practical Implementation Based on Artificial Intelligence Solutions

Introduction. The digital transformation of education necessitates a rethinking of fundamental pedagogical concepts. The traditional distinction between individualization and personalization of learning requires conceptualization in light of the development of artificial intelligence technologies. The aim of this study is to define a conceptual framework for analyzing the transition from individualization to personalization of learning under the influence of artificial intelligence technologies and to establish the feasibility of achieving true personalization in its philosophical and pedagogical sense using modern systems.Materials and Methods. The study is based on an interdisciplinary approach. Methods of conceptual, comparative, and systemic analysis are applied. A review of international (Squirrel AI Learning, Carnegie Learning, Knewton) and Russian (Contribution to the Future, university systems) adaptive learning platforms is conducted. Aspects of personalization models, the role of the student and teacher, the flexibility of educational trajectories, and the results achieved are considered. The empirical part consisted of a cross-sectional descriptive and analytical survey of 191 teachers and university professors conducted between October 6 and 27, 2025, at Moscow Pedagogical State University.Results. Artificial intelligence technologies significantly expand the practical possibilities of an individualized approach, but the personalization they enable remains limited. Current systems primarily adapt the format, pace, and sequence of instruction while maintaining consistent goals. Full personalization, which involves student participation in goal setting and co-creation of the educational trajectory, remains under-utilized. A practical need for a methodology for applying artificial intelligence based solutions to achieve individualization and personalization of learning was identified. Artificial intelligence should be viewed as a new educational environment. True personalization requires changes in pedagogical design, ensuring the transparency of algorithms, and active student participation in goal setting.Conclusion. The study opens up prospects for developing a theory of digital subjectivity and integrating the humanistic goals of education with the capabilities of technologies artificial intelligence. The results are significant for the academic community, digital education specialists, and educational platform developers.