Global Research Trends and Collaborative Networks on AI in Teacher Education: A Scientometric Investigation

The integration of artificial intelligence (AI) into teacher education has escalated over the past decade, necessitating a comprehensive analysis of the progression of this dialogue. This study does a bibliometric analysis of 246 peer-reviewed academic publications concerning AI in teacher education, published from 2014 to July 2025, emphasising pre-service instructors. Data were obtained from Scopus and analysed with VOSviewer to investigate publishing trends, prominent journals, influential authors, citation patterns, and collaboration networks. The results indicate a significant increase in publications post-2021, especially from the United States and China, with enhanced contributions from developing nations. High-impact journals have emerged as primary publication platforms, while keyword research underscores the growing significance of terms like “ChatGPT,” “AI literacy,” and “generative AI,” signifying a transition from technological acceptance to pedagogical reform. Co-authorship mapping reveals cohesive transnational clusters, although regional differences persist. This paper synthesises a decade of research, providing a thorough evidence base for teacher educators, curriculum designers, and legislators, and offers guidance for inclusive, ethically grounded, and future-oriented teacher training in AI-enhanced learning environments.