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ABSTRACT This study explores how university educators in the UAE interpret and negotiate the integration of Artificial Intelligence (AI) in teaching and learning practices. Using a qualitative case study approach based on 20 semi‐structured interviews, the analysis identifies four interconnected tensions shaping AI integration. Their responses were thematically analyzed through NVivo‐15 and interpreted through the lenses of UTAUT2 and TPACK in the context of the adoption of AI and corresponding adaptation in the teaching practice. The analysis revealed four interconnected tensions shaping AI integration in higher education: (1) AI enhances personalized and adaptive learning but raises concerns about overreliance and unequal access; (2) teaching roles are shifting from knowledge delivery to facilitation of creativity, critical thinking, and emotional intelligence; (3) ethical and social issues, including bias, privacy, and inclusivity, require transparent governance; and (4) adoption barriers such as costs, training gaps, and infrastructure limitations demand institutional support. These tensions show that AI integration is not experienced as a straightforward improvement, but as a balancing process between pedagogical benefits, human expertise, and institutional constraints. The study reveals how educators navigate key tensions between AI‐driven personalization and cognitive dependency, automation and pedagogical identity, and innovation and ethical responsibility. By situating these dynamics within the UAE context, the study offers a process‐oriented understanding of AI integration and develops actionable insights for policy and practice. This study contributes by demonstrating how these tensions function as interconnected mechanisms shaping educator decision‐making, rather than as isolated benefits and challenges commonly reported in prior literature.
Albannai et al. (Mon,) studied this question.