The advancement of Artificial Intelligence (AI) has accelerated the transformation of learning toward a more adaptive and learner-centered approach through the implementation of personalized learning. This article aims to analyze the concepts, implementation, challenges, and strengthening strategies of AI-based personalized learning within the context of general education. The study employed a qualitative descriptive library research method by reviewing scientific publications published over the last five years. The findings indicate that AI supports the analysis of learners' characteristics, develops adaptive learning pathways, provides timely feedback, and facilitates the creation of learning materials tailored to individual needs. This approach has significant potential to improve learning effectiveness, student engagement, and the development of twenty-first-century competencies. Nevertheless, its implementation continues to face challenges related to teachers' readiness, AI literacy, data privacy, algorithmic bias, and ethical considerations. Therefore, the successful implementation of AI-based personalized learning requires synergy among technological innovation, teachers' pedagogical competence, responsible governance, and educational policies that promote adaptive, inclusive, and sustainable learning.
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