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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66789
Volume:
10 |
8 |
Aug 2026
Pages:
1-13
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 Management
Srinivas University
Department of Management
Srinivas University
Artificial Intelligence (AI) is a game changing technology transforming organizational processes, workforce arrangements and employment relationships across many different industries. AI delivers huge gains in productivity, efficiency, innovation and decision making. But it has also raised concerns about job displacement, employability and workforce sustainability. The aim of this study is to review the existing literature regarding Employee’s attitude towards Artificial Intelligence and Impact of Artificial Intelligence on job security in today’s work places with a special focus on banking industry in private sector. This review uses a systematic literature review methodology to synthesize findings from peer-reviewed journal articles, scholarly databases, policy reports, and industry publications published between 2020 and 2026. This study investigates the important constructs of AI awareness, perceived AI capability, exposure to AI adoption, perceived benefit of AI, perceived threat of job displacement, reskilling readiness, job insecurity, perceived organizational support and job security perception. The results show that employees have positive and negative perceptions toward AI. They are aware of the operational and strategic benefits of AI, however, fears of automation and job losses and changing skill requirements still influence concerns about job security. The review also found that AI awareness, readiness to reskill and organizational support is positively associated to employees’ adaptability and confidence and perceived threat of job displacement is associated to higher job insecurity. The research indicates that a human-cantered approach such as employee development, continuous learning, open communication and organizational support is essential for successful AI implementation. This way of working allows for technological transformation while keeping employees happy, engaged and secure in their long term jobs.
KEYWORDS
The studies analyzed show that the perception of job security is a function of technological developments and the interpretation of the development by the employees. Awareness, experience, perceived benefits, perceived threats, readiness to learn and organizational experiences contribute to employees' perceptions of AI. Thus it is not the adoption of technology per se that leads to perceptions of job security but rather a complex psychological and organizational process. The synthesis therefore suggests that organizations need to move beyond the purely technological considerations and embrace a human-centric approach that stresses employee development, communication and support for the successful deployment of AI. This approach can help the workforce adapt and ensure technological innovation contributes to organizational performance and employee well-being.
Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3 Ahmed, S., Rahman, M., & Islam, T. (2024). Organizational support and employee adaptation during AI transformation. Journal of Organizational Change Management, 37(1), 45–63. Araujo, T., Helberger, N., Kruikemeier, S., & de Vreese, C. H. (2020). In AI we trust? Perceptions about automated decision-making by artificial intelligence. AI & Society, 35(3), 611–623. Arntz, M., Gregory, T., & Zierahn, U. (2016). The risk of automation for jobs in OECD countries: A comparative analysis. OECD Social, Employment and Migration Working Papers, No. 189. Autor, D. H. (2022). The work of the future: Building better jobs in an age of intelligent machines. Journal of Economic Perspectives, Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman. Benbya, H., Pachidi, S., & Jarvenpaa, S. (2021). Artificial intelligence in organizations: Implications for information systems research. MIS Quarterly Executive, 20(4), 1–16. Brougham, D., & Haar, J. (2020). Technological disruption and employment: The influence on job insecurity and turnover intentions: A multi-country study. Technological Forecasting and Social Change, 161, 120276. https://doi.org/10.1016/j.techfore.2020.120276
Publication Date
8/15/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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