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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67907
Volume:
10 |
10 |
Oct 2026
Pages:
1-8
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Department of Commerce
BGS B School

Department of Management
BGS B School
Artificial Intelligence (AI), including Generative AI tools such as ChatGPT, Gemini, Microsoft Copilot, and Claude, is increasingly being adopted in higher education for teaching preparation, research, assessment creation, and learner-centred teaching. While AI adoption offers opportunities to improve productivity, teaching effectiveness, and research capabilities, it also raises concerns related to technostress, AI anxiety, cognitive load, ethical challenges, professional identity, and technological adaptation. This review synthesizes literature on AI adoption and faculty mental well-being, with particular emphasis on the Indian higher education context. It examines the drivers and barriers influencing AI adoption and explores how technological, institutional, motivational, and individual factors shape faculty experiences. The review draws on the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Self-Determination Theory (SDT) to understand technology acceptance and faculty well-being. Existing literature indicates that perceived usefulness, ease of use, institutional support, AI literacy, professional autonomy, and empowerment encourage adoption, whereas technostress, digital fatigue, ethical concerns, and professional identity threats may negatively affect well-being. Despite growing research, evidence on the mental health implications of AI adoption among Indian faculty remains limited. The review highlights the need for longitudinal and mixed-methods research to develop AI adoption strategies promoting faculty well-being.
KEYWORDS
Artificial Intelligence is becoming part of everyday academic work and is transforming the way in which faculty members engage with teaching, research, assessment, and administration. The literature reviewed in this study sheds light on the factors that influence Generative AI adoption, highlighting the importance of technology perceptions, institutional conditions, individual capabilities, and psychological outcomes. Technology-acceptance models emphasize the relevance of usefulness, ease of use, social influence, and facilitating conditions, while motivational approaches highlight the role of autonomy, competence, and relatedness. At the same time, the reviewed literature suggests that Generative AI can positively impact faculty experiences by reducing the need for routine work and contributing to enhanced teaching effectiveness and research productivity. Such benefits are closely linked to the risks of AI adoption, such as AI anxiety, technostress, ethical concerns, and additional responsibilities. One of the most significant limitations of the reviewed literature is the lack of research that addresses the influence of Generative AI on the mental well-being of faculty members in India. While most studies examined faculty adoption, readiness, and behavioral intentions, few addressed concerns related to mental well-being. India is a particularly interesting context for further research, as its higher education institutions differ significantly in terms of infrastructure, governance arrangements, disciplinary requirements, faculty readiness, and organizational culture. Future studies should therefore adopt mixed-method, longitudinal approaches to understand the ways in which Generative AI can be integrated into academic work while enhancing well-being. Particular attention should be paid to the role of AI literacy, institutional support, organizational culture, ethical climate, professional autonomy, workload, and job security. In doing so, future research can go beyond questions of adoption and readiness to examine ways in which institutions can transform education in a manner that is conducive to faculty well-being and sustainable academic work environments.
Jeya, S. F., & Saravanakumar, A. R. (2026). Exploring faculty perspectives on Artificial Intelligence adoption in higher education: An analysis using the UTAUT framework. Innovare Journal of Education, 14(2), 22–30. Abbas, J., Aman, J., Nurunnabi, M., & Bano, S. (2024). The impact of artificial intelligence on higher education: Opportunities, challenges, and future directions. Education and Information Technologies, 29(3), 2561–2583. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. Dotan, A., Parker, S., & Radzilowicz, L. (2024). Responsible adoption of generative AI in higher education: Developing a "Points to Consider" approach based on faculty perspectives. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12871-0 Cambra-Fierro, J. J., Fuentes-Blasco, M., López-Pérez, M.-E., et al. (2024). ChatGPT adoption and its influence on faculty well-being: An empirical research in higher education.
Publication Date
10/13/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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