The proliferation of generative AI tools in language education has prompted a deceptively simple question, what is the teacher for? This special issue takes a clear and argued position in response; the teacher is irreplaceable. Not because AI lacks power, it demonstrably does not, but because the core work of language education is fundamentally human. It involves relational attunement, pedagogical judgment, ethical responsibility, and the ability to read the learner as a whole person situated in a specific social and cultural context. These are capacities that no algorithm, however sophisticated, can replicate. This issue challenges the prevailing enthusiasm for AI-driven efficiency by centering the irreducible expertise that teachers bring to AI-mediated learning environments, and by asking what it means to teach well precisely when machines can do so much.

The primary goal of this special issue is to build a rigorous, theoretically grounded body of scholarship that asserts and examines the irreplaceable expertise of language teachers in AI-mediated educational contexts. We invite contributions that interrogate, complicate, and ultimately reaffirm what human teachers do that AI cannot, with particular interest in pedagogical decision-making, relational dimensions of teaching, teacher identity under technological pressure, and the ethics of AI integration in diverse language learning settings.

We welcome original empirical research articles, systematic review articles, theoretical and conceptual papers, and case studies. Contributions from diverse linguistic and cultural contexts are especially encouraged.

Through this special issue, we aim to produce a landmark collection that recentres the teacher at the heart of AI-mediated language education, not as a supervisor of machines, but as the irreplaceable expert whose professional knowledge, relational skill, and ethical judgment define what quality language teaching means. We welcome researchers from applied linguistics, language teacher education, educational technology, and TESOL to contribute interdisciplinary perspectives on this defining challenge of our moment. Your work will help shape how the field responds to AI not with anxiety or uncritical adoption, but with clarity, confidence, and scholarly rigour.