<![CDATA[Background. Artificial Intelligence (AI) has rapidly transformed twenty-first-century education, evolving from a supplementary tool into a central component of data-driven pedagogical ecosystems. Previous bibliometric studies have focused mainly on thematic trends or specific contexts, with limited integration of publication dynamics, collaboration networks, citation structures, and thematic evolution within a single framework. Existing studies also often cover publications only up to 2023 or 2024, leaving recent generative AI developments underexplored. Purpose. This study provides a comprehensive bibliometric analysis of AI research in education indexed in Scopus from 2008 to 2026, examining publication trends, collaborative networks, citation impact, and thematic evolution, with particular focus on the generative AI era. Method. A total of 1,094 journal articles were analyzed using Biblioshiny (Bibliometrix-R). Performance analysis and science mapping techniques assessed annual growth, scholarly impact, international collaboration, thematic evolution, and keyword network structures. Results. Findings reveal a 23.55% annual growth rate, with sharp acceleration after 2017 and peak productivity in 2025, averaging 35.28 citations per document and a 27.97% international co-authorship rate dominated by China and the United States. Thematic evolution shows a shift from conceptual discussions toward adaptive learning, machine learning, learning analytics, classroom implementation, and AI-based assessment. Conclusion. AI in education has evolved into a globally interconnected pedagogical paradigm, offering insights for future policy and responsible AI integration.]]>
