<![CDATA[The rapid development of Artificial Intelligence (AI) has driven significant transformations across various sectors, including primary education. Although numerous studies have explored the application of AI in educational settings, comprehensive reviews focusing specifically on the adoption and diffusion of AI in primary education remain limited. This study aims to examine research trends, forms of AI implementation, factors influencing AI adoption and diffusion, implementation challenges, the implications of AI use for learning, and future research directions in the context of primary education. This study employed a Systematic Literature Review (SLR) approach following the PRISMA 2020 guidelines. Literature searches were conducted using Google Scholar and ERIC databases. From an initial pool of 70 identified articles, 18 studies met the inclusion criteria and were selected for further analysis. The findings reveal that AI implementation in primary education is predominantly characterized by the use of adaptive learning systems, intelligent tutoring systems, learning analytics, generative AI, and AI-assisted teaching tools. Key factors influencing AI adoption include AI literacy, teacher competence, institutional support, and technological infrastructure. However, several challenges remain, including limited teacher readiness, ethical and data privacy concerns, infrastructure disparities, and the lack of comprehensive policies governing AI use in education. Furthermore, AI contributes positively to personalized learning, student motivation, instructional efficiency, and the development of 21st-century skills. This study concludes that the successful adoption and diffusion of AI in primary education require not only technological advancement but also adequate human resource readiness and sustainable educational policies.]]>
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