A scientometric analysis and systematic review of artificial intelligence for pre-service teachers from 2011 to 2025

The rapid advancement of artificial intelligence (AI), particularly generative AI (GAI), is increasingly shaping teacher professional development. However, there remains a notable lack of studies that systematically map the development trajectory of research on pre-service teachers over time, despite their central role in AI-enhanced education. To address this gap, this study conducts a bibliometric and systematic review of 229 publications (2011–2025) retrieved from the Web of Science Core Collection, following PRISMA guidelines, with analyses supported by Bibliometrix and VOSviewer. The findings reveal a sharp increase in publications in recent years, largely driven by the emergence of GAI, alongside a shift in research focus from improving teaching efficiency toward fostering AI-literate educators. While existing research is predominantly concentrated in developed regions, the lowering barriers to AI adoption have facilitated growing contributions from developing countries. Keyword and thematic analyses identify three major research hotspots: core AI technologies, pedagogically oriented AI applications for competency development, and the integration of GAI into teaching practices. Collaboration network analysis indicates strong national clustering but relatively limited international collaboration. Overall, the thematic structure suggests that the field is gradually forming a more systematic knowledge base, while still remaining in an early and exploratory stage.