Exploring the landscape of AI in English language teaching: A comprehensive bibliometric analysis

This study provides a comprehensive bibliometric analysis of Artificial Intelligence (AI) applications in English Language Teaching (AI-ELT), focusing on global research trends, influential authors, and emerging themes from 1986 to 2024. The findings reveal a significant surge in AI-ELT publications since 2019, driven by technological advancements, the COVID-19 pandemic, and the growing integration of adaptive learning systems, natural language processing tools, and AI-driven chatbots. Notably, China leads in research output and citation impact, followed by contributions from Saudi Arabia, Indonesia, and the United States, underscoring regional disparities and opportunities for global collaboration. Key trends highlight the dominance of keywords like “teaching,” “students,” and “artificial intelligence,” reflecting a focus on personalized, student-centered learning and scalable AI-based interventions. Top-cited works explore themes such as the pedagogical potential of AI, chatbot integration, and reflective thinking mechanisms. However, the field faces challenges, including ethical concerns, regional inequities, and a need for more interdisciplinary, longitudinal research. The study emphasizes the transformative potential of AI in addressing traditional classroom limitations and fostering inclusive, flexible learning environments. This research contributes to the strategic development of AI-ELT, advocating for equitable access, teacher training, and ethical integration of AI technologies to shape the future of education.