Post COVID-19, the incorporation of artificial intelligence in teacher education has grown-up, especially across Asia, where fast digitalisation and educational reforms are changing pedagogical methods. This study examines 2020–2025 scholarly research on AI in teacher education using bibliometric analysis. The study uses VOSviewer software to visualise patterns and intellectual structures from 303 Scopus-indexed peer-reviewed papers utilising advanced bibliometric approaches like co-authorship analysis, keyword co-occurrence, and co-citation mapping. After 2022, China, Indonesia, and Hong Kong led publication volume growth. Computers & Education and British Journal of Educational Technology are important distribution platforms. AI literacy, pre-service teacher preparation, digital pedagogy, and AI ethics are common study topics. Influential writers and institutions lead regionally but not internationally. Co-citation and keyword analyses show a transition from theoretical to applied research, especially in generative AI and personalised learning. The academic trends and knowledge structures underlying AI-infused teacher education in Asia are illuminated by this study. It also identifies crucial gaps in empirical validation, regional inclusion, and interdisciplinary engagement, guiding future research and policy in this rapidly evolving subject.