PERSONALIZED LEARNING WITH ARTIFICIAL INTELLIGENCE

Artificial intelligence (AI) is reshaping personalized learning by enabling adaptive content sequencing, formative feedback, intelligent tutoring, and data-informed instructional support. This article critically examines the educational value, implementation requirements, and ethical limitations of AI-enabled personalization, with particular attention to higher education and emerging digital education contexts. A structured narrative review and comparative synthesis of peer-reviewed meta-analyses, reviews, and international guidance published primarily between 2023 and 2026 were undertaken. The synthesis distinguishes evidence of learning gains from broader claims about engagement, fairness, and scalability. The findings suggest that AI is most defensible as an augmentation of pedagogical judgement rather than a substitute for educators. Effective adoption requires accessibility, privacy protection, transparent evaluation, teacher preparation, and continuous monitoring of learning outcomes.