<![CDATA[This research aims to examine the impact of Artificial Intelligence-based learning on education policy and school management, with a focus on how schools adapt to technological disruption. The research method uses a qualitative approach with case studies. Data was collected through semi-structured interviews, participant observation, and document analysis, then analyzed through the stages of data reduction, data presentation, and drawing conclusions. The research results show that Artificial Intelligence-based learning requires transformative policy changes in three main aspects: data use policies, continuous training for teachers, and personalized learning approaches. Effective data management policies are critical to protecting student privacy and supporting adaptive learning based on real-time analytics. Continuous professional development enables teachers to utilize Artificial Intelligence tools effectively, while personalized learning strategies increase student engagement and motivation through an individualized approach. The implications of this research emphasize that the integration of Artificial Intelligence in education must be accompanied by ethical, inclusive and planned policies. The contribution of this research is both theoretical and practical, providing a framework for policy makers to design strategic leadership, stakeholder engagement, and a culture of innovation to realize the maximum potential of Artificial Intelligence in education..]]>
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