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Abstract
Artificial Intelligence (AI) has become one of the most discussed innovations in education, and its role in teaching English has gained increasing scholarly attention. This study examined the research landscape of AI in teaching English through a bibliometric analysis of 266 publications indexed in LENS from 2010 to 2025. Using VOSviewer to analyze co-authorship, co-citation, and bibliographic coupling, the study identified leading authors, research clusters, and thematic directions in the field. The findings revealed that research activity was predominantly concentrated among a few influential scholars and institutions, leading to uneven collaboration across regions. Two dominant themes emerged: one strand focused on technology-driven applications, such as chatbots, automated writing support, and adaptive learning systems, while the other emphasized pedagogy-oriented concerns, including teacher readiness, ethical implications, and cultural contexts in the adoption of AI. Despite the growing body of work, gaps remained in empirical classroom-based studies and in the development of culturally responsive AI tools tailored to local needs. The study concluded that while AI offered significant potential for enhancing English language teaching, its impact would depend on broader teacher training, cross-institutional collaboration, and strong policy support for ethics and inclusivity. It recommended integrating bibliometrics with content analysis, longitudinal research, and multi-database sources to provide a fuller picture of AI’s contributions to English education.
