<![CDATA[This study explores the integration of Generative Artificial Intelligence (Gen-AI) as a scaffolding tool for mastering English for Specific Purposes (ESP) within the field of Civic Education. By adopting a cross-regional perspective, the research examines how AI facilitates technical vocabulary acquisition and grammatical competence—specifically regarding Modal Verbs—among pre-service teachers in Indonesia and Uzbekistan, two nations currently undergoing significant digital transformations in their educational sectors. The research utilizes a descriptive-evaluative approach, integrating a pedagogical needs analysis from an Indonesian cohort with a comparative policy review of Uzbekistan’s recent foreign language reforms. Data were gathered through structured surveys focusing on linguistic barriers in "Civic English," AI interaction patterns, and student preferences for interactive, AI-driven learning modules. The results reveal a shared "linguistic gap" in both contexts, where traditional static materials (PDFs) fail to address the nuances of legal English. 61.5% of students exhibited difficulty in distinguishing Modal Verbs (Must, Should, Can) in constitutional contexts. However, the study identifies that Gen-AI acts as a "Linguistic Equalizer," with over 80% of respondents demanding AI-integrated modules that offer real-time feedback and debate simulations. The findings suggest that AI effectively lowers the "Affective Filter" for students in both Southeast and Central Asia, providing a standardized digital scaffolding that transcends geographical boundaries. The study argues for a shift toward "AI-Mediated Scaffolding" in ESP curricula. It highlights that educational policies in both Indonesia (Merdeka Belajar) and Uzbekistan (New Uzbekistan Strategy) provide a fertile ground for AI integration. The research recommends a collaborative framework for developing interactive, cross-cultural ESP modules that prepare future civic educators for global professional engagement]]>
