<![CDATA[This study aims to analyze strategies for utilizing Artificial Intelligence (AI) in secondary education through Rogers’ Diffusion of Innovations theory (2003). The research employed a Systematic Literature Review (SLR) approach following the PRISMA framework. A total of 34 peer-reviewed articles from Scopus, Web of Science, ScienceDirect, and Sinta databases were systematically reviewed to identify adoption patterns, driving factors, and barriers in AI implementation within secondary schools. The findings indicate that the adoption of AI in secondary education is still at an early diffusion stage, with a sharp increase in research interest since 2021. Five innovation attributes—relative advantage, compatibility, complexity, trialability, and observability—significantly influence teachers’ and students’ adoption intentions. Relative advantage and compatibility were identified as the strongest drivers of adoption, whereas complexity remains a major barrier requiring system simplification and continuous professional training. The study proposes a conceptual model of AI innovation diffusion consisting of three strategic pillars: Human Readiness, Institutional Support, and Innovation Ecosystem. These pillars collectively emphasize the importance of human capability, institutional policy, and cross-sector collaboration to ensure ethical, inclusive, and sustainable AI adoption. Properly implemented, AI has the potential to transform secondary education into a more adaptive, data-driven, and equitable learning system in the digital era.]]>
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