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

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.