Generative Artificial Intelligence (GenAI) is reshaping education by introducing tools that enhance teaching methodologies, personalize learning, and streamline administrative tasks. However, adoption of these tools remains uneven, raising concerns about disparities in AI literacy and competency across geographic regions and educational contexts. Through the lens of Innovation Diffusion Theory, we investigated the adoption of GenAI tools among second language (L2) teachers in the United States, Colombia, Germany, and Macau. Using survey data, we assessed four areas: accessibility of GenAI tools, teacher knowledge of potential applications, integration in teaching practices, and the nature of professional development provided. Our results indicated substantial intra- and inter-context variance, with U.S. and Colombian educators reporting higher familiarity and usage compared to those from Germany and Macau. Additionally, university and high school teachers were more likely to access professional development and leverage GenAI for tasks like assessment and differentiation than elementary or middle school educators, regardless of geographic setting. These disparities align with broader trends in AI adoption, reflecting heterogeneity in cultural attitudes, systemic barriers, and institutional support. These findings contribute to Innovation Diffusion Theory by illustrating how accessibility, knowledge, and institutional support interact across diverse contexts. They offer practical guidance for policymakers and educational leaders to develop targeted interventions that promote equitable GenAI integration in language education worldwide.
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