IMPACT OF AI ADOPTION IN HIGHER EDUCATION ON FACULTY JOB INSECURITY: AN EXAMINATION OF AI-INDUCED OCCUPATIONAL STRESS IN DEEMED AND PRIVATE UNIVERSITIES

Abstract

The rapid integration of Artificial Intelligence (AI) into higher education has transformed instructional processes, administrative efficiency, and research productivity, yet it has simultaneously introduced new psychological and professional challenges for faculty members. This study investigates how AI adoption—measured through AI automation, AI-powered pedagogical tools, and AI-based research and data analytics—shapes faculty job insecurity and occupational stress in deemed and private universities in India. Using a quantitative research design, data were collected from 138 faculty respondents through a structured questionnaire and analyzed using Structural Equation Modeling (SEM). The results indicate that AI adoption significantly predicts job insecurity, as faculty perceive AI-driven tools as potential threats to their professional relevance, control over academic tasks, and long-term job stability. Findings also reveal that job insecurity strongly influences occupational stress, while AI-driven workload increase, role ambiguity, and mental health strain exert additional direct effects on stress levels. Collectively, these outcomes highlight the multidimensional nature of AI-induced pressure on academic staff and the need for supportive institutional strategies. The study underscores the importance of training initiatives, transparent communication, and organizational support systems that can empower faculty to adapt to technological shifts rather than experience them as threats. Although limited by its cross-sectional design and institutional scope, the research offers valuable insights for policymakers and university leaders aiming to implement AI responsibly. Future studies may explore longitudinal impacts, cross-institutional variations, and protective psychological factors related to AI integration in academia.