<![CDATA[Artificial Intelligence (AI) has emerged as a transformative force in contemporary education, creating new opportunities to address the limitations of traditional curriculum models that often fail to accommodate diverse learner needs, abilities, and learning preferences. Increasing demand for learner-centered education has encouraged educational institutions to explore AI-driven solutions capable of supporting adaptive instruction, individualized learning pathways, and data-informed decision-making. This study aims to examine the role of AI in transforming the traditional curriculum into a personalized learning experience and to explore its implications for learner engagement, self-directed learning, and educational satisfaction. A mixed-methods sequential explanatory design was employed. Quantitative data were collected from 450 participants, including students, teachers, curriculum developers, educational technology specialists, and academic administrators. Qualitative interviews were subsequently conducted to gain deeper insights into curriculum transformation processes and stakeholder experiences. Structural Equation Modeling and thematic analysis were used to analyze the data. Findings revealed that AI utilization significantly enhanced curriculum flexibility, personalized learning effectiveness, learner engagement, self-directed learning, and learning satisfaction. Personalized learning effectiveness emerged as a key mediating factor linking AI implementation to positive educational outcomes. Qualitative evidence further demonstrated that adaptive learning systems and learning analytics facilitated more responsive and individualized educational experiences. The study concludes that AI serves as a strategic enabler of curriculum transformation, supporting the development of flexible, learner-centered, and personalized learning ecosystems.]]>
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