AI Anxiety and Adaptability among Teachers in Higher Education: A Systematic Literature Review

Abstract

The rapid integration of artificial intelligence (AI) into higher education has sparked significant interest in understanding its psychological and practical implications for teachers, particularly concerning AI-related anxiety and adaptability. While AI offers transformative potential for teaching and learning, its adoption has also introduced uncertainties and challenges that may affect educators’ emotional and professional responses. This systematic literature review examines the multifaceted relationship between AI anxiety and adaptability among higher education teachers, synthesizing existing research to identify key themes, gaps, and future directions. We analyze studies across dimensions such as adoption and acceptance of AI, its impact on teachers and students, teaching practices, psychological factors, assessment integrity, and AI literacy. The review employs a rigorous methodology to systematically identify, evaluate, and interpret relevant literature, ensuring a comprehensive understanding of the current scholarly landscape. Findings reveal that AI anxiety often stems from concerns about job displacement, ethical dilemmas, and inadequate training, while adaptability is influenced by institutional support, professional development, and personal attitudes toward technology. The interplay between these factors shapes teachers’ willingness and ability to integrate AI into their pedagogical practices. Ultimately, this review highlights the need for targeted interventions to mitigate anxiety and foster adaptability, suggesting that a balanced approach to AI implementation can empower educators to navigate the evolving educational landscape effectively.