The rapid expansion of research on Generative Artificial Intelligence (GenAI) in English Language Teaching (ELT) has created both unprecedented opportunities and a need for critical synthesis. This paper presents a meta- bibliometric study that maps the evolution, scope and intellectual structure of this emerging field, offering an evidence-based overview of how GenAI is transforming language education research. Drawing on a purposively compiled corpus of 16 bibliometric studies on AI in EFL, retrieved from the Scopus database, and published between 2023 and 2025, we identify, quantify and visualize trends in publication output, collaboration networks, thematic foci and methodological orientations across this corpus. Building on previous bibliometric reviews of AI in education, our analysis introduces a meta-bibliometric layer by comparing existing bibliometric studies themselves thus assessing not only the growth of the field but also how it is being researched. Through co-word and citation network analyses, we uncover key clusters around AI integration, AI literacy, ethics and assessment and teacher education, alongside regional imbalances and evolving authorship patterns. Findings reveal an exponential increase in GenAI-related ELT research since 2022, dominated by conceptual and exploratory studies, with limited empirical classroom validation. We argue that a meta-bibliometric approach can inform more coherent research agendas, highlight underexplored intersections between pedagogy and technology and identify epistemological gaps in current discourse. The paper concludes by discussing implications for sustainable and responsible AI integration in language education and by outlining directions for future research collaboration between applied linguists, technologists and educators. Ultimately, this study contributes to a more reflexive and data-driven understanding of how GenAI is reshaping both the practice and the study of language teaching.