GenAI accelerates surface localization but not deeper culturally responsive teaching in UAE higher education

Abstract Generative artificial intelligence (GenAI) is rapidly reshaping higher education teaching practices, yet we still know little about how faculty in culturally specific, non-Western contexts evaluate and adapt GenAI outputs for culturally responsive teaching (CRT). This qualitative interpretivist study examines how faculty members in UAE higher education use GenAI to support cultural fit in multicultural classrooms while navigating local norms, institutional expectations, and ethical constraints. Drawing on Gay’s CRT framework, we conducted semi-structured interviews with 20 faculty members across disciplines and national backgrounds who actively use GenAI in their teaching. Using reflexive thematic analysis, we identified four themes: (1) Culturally responsive pedagogical strategies using GenAI; (2) Faculty sensemaking of GenAI for cultural responsiveness; (3) Cultural and relational benefits of GenAI-supported teaching; and (4) Institutional, ethical, and cultural risks/barriers. Findings suggest that GenAI primarily functions as an accelerator of surface localization (e.g., examples, tone, translation) rather than a driver of deeper CRT transformation unless faculty apply explicit cultural decision rules and critical consciousness to interrogate bias, representation, and epistemic authority. Implications highlight the need for UAE-specific guidance, culturally grounded professional development focused on evaluative judgment, and shared vetted case resources to support responsible GenAI use at scale.