Global and Educational Disparities in AI Integration: A Study of L2 Teacher Training and Usage Patterns

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. Here we investigate the adoption of GenAI tools among second language (L2) educators in the United States, Colombia, Germany, and Macau—professionals uniquely positioned to benefit from and highlight barriers to GenAI integration. Using survey data, we assess 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-country 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. Our findings highlight the critical need for targeted strategies that mitigate these emerging gaps in AI literacy, competency, and professional development.