Generative artificial intelligence (GenAI) is rapidly reshaping language education and teacher education. However, limited attention has been given to how empirical studies investigate pre-service teachers’ engagement with GenAI. This study aims to synthesize empirical research on the characteristics, pedagogical uses, and major themes of GenAI in pre-service EFL/ESL teacher education. Following PRISMA guidelines, database searches in ERIC, Web of Science, and Scopus yielded 20 empirical studies published between 2022 and March 2026. Data were analyzed using descriptive analysis, inductive content analysis, and thematic analysis. Inter-reviewer procedures and coding validation steps were applied to enhance analytical consistency. The findings show that research in this area is still emerging, with most studies conducted in Asia and relying on qualitative approaches. Large language models, particularly ChatGPT, dominated the studies and were mainly used for instructional preparation, language and academic learning, professional competence development, and reflective practice. Three major themes emerged: teacher cognition and acceptance, pedagogical integration, and professional development, alongside challenges related to reliability, overreliance, ethics, and AI literacy. The findings suggest that GenAI is actively shaping pre-service language teacher education across cognitive, pedagogical, and developmental domains. They also highlight the need for more diverse GenAI tools and multimodal applications in future research, as well as greater support for critical and responsible AI integration in teacher education practice.
Xuerong Peng (Thu,) studied this question.