From crisis to catalyst: How U.S. world language teachers are leveraging GenAI to navigate systemic challenges

Abstract

The arrival of generative artificial intelligence (GenAI) in educational settings has sparked debate over how it will transform teaching and learning. Language education is already grappling with teacher shortages, workload intensification, and shifting program viability. While conceptual work has outlined theoretical use cases, little empirical research has examined how world language teachers actually use GenAI or the challenges they encounter. In this study, we used a mixed‐methods design to survey U.S. world language teachers, followed by interviews with eight teachers who were highly proficient in GenAI implementation. Findings revealed various factors shaping GenAI adoption and challenged claims that GenAI diminishes teacher expertise or undermines critical thinking. Access to GenAI and policies for its use were uneven across school districts and grade levels. Without institutional guidance, many teachers were self‐taught, underscoring the need for targeted professional development. We discuss how, with appropriate guidance, emerging AI‐integrated pedagogical models have the potential to revitalize and sustain language education programs through strategic, teacher‐led use of GenAI.