<![CDATA[The integration of artificial intelligence (AI) into education has gained significant attention over the past few years, driven by the potential of AI to revolutionize teaching and learning processes. Despite the growing body of research on the application of artificial intelligence (AI) in education, there remains a significant gap in understanding its trends and specific details within English Language Teaching (ELT). This study presents an analysis and snapshot of contemporary research trends in AI applications in ELT using bibliometric analysis. By leveraging publication from the 2019-2024 Scopus database, key patterns and themes within the existing literature are identified. The study systematically collected and analyzed 1,994 documents, including articles, conference papers, and reviews from 522 sources and 3,316 authors. The analyses identify the most productive authors, sources, affiliations, and countries. Additional bibliographic coupling analysis reveals seven main clusters. These clusters range from AI applications in contextual language learning to big data analysis in ELT. Co-occurrence network analysis further underscores the interconnectedness of various research topics, such as machine learning, natural language processing, and autonomous learning systems. The findings have several important implications. The growing body of research indicates that AI technologies are increasingly being integrated into educational practices, offering more personalized, efficient, and engaging learning experiences. This study provides a detailed overview of the current landscape of AI research in ELT. By understanding these dynamics, educators, researchers, and policymakers can better leverage AI technologies to enhance educational outcomes and address the evolving needs of learners in a rapidly changing digital world.]]>
