<![CDATA[The rapid advancement of artificial intelligence (AI) technologies has significantly influenced educational practices, particularly within adaptive learning systems at the secondary level. Although AI has demonstrated substantial potential in personalizing learning processes, its implementation in formal school settings remains constrained by multiple systemic challenges, including educator readiness and infrastructural disparities. This study aims to identify integration patterns of AI in adaptive learning, examine the evolving role of teachers, and explore obstacles and prerequisites for AI adoption in secondary education. Employing a literature review method, this research synthesizes relevant scholarly publications from the past decade and conducts thematic interpretation to uncover current trends in AI utilization. The findings reveal that AI facilitates personalization by adjusting content, pacing, and feedback based on learner profiles, while simultaneously redefining teachers as facilitators of data-driven instruction. Nonetheless, AI adoption continues to be hindered by limited infrastructure, inadequate policy support, and uneven digital competencies among educators. The study concludes that AI integration represents a systemic educational transformation requiring institutional readiness rather than a mere technological add-on. Further empirical research is recommended to validate implementation models across diverse school contexts.]]>
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