Employee Perceptions, Psychological Well-Being, and the Automation-Augmentation Paradox in the Age of Generative AI – A Qualitative Study
DOI:
https://doi.org/10.67177/arr2xb15Keywords:
Generative AI, Knowledge Workers, Psychological Well-beingAbstract
Automation boosts productivity but may endanger professional identity and well-being when generative and agentic AI enter knowledge jobs quickly. Human elements of AI adoption are understudied, especially qualitative methodologies that capture lived experiences. Productivity improvements are clearly established. Explore knowledge workers' emotional and psychological reactions to AI-driven developments and how they handle the automation-augmentation conundrum. This study contrasts technology-focused research with employee psychological adaption. Semi-structured interviews with 25 knowledge workers in financial services, creative industries, and professional services. Data evaluated using reflexive thematic analysis to discover perceptual, affective, and coping tendencies. Ambivalent acceptance – excitement and anxiety; identity friction – perceived deskilling versus augmented creativity; coping through re-crafting – proactive role redesign; and organisational buffers – psychological safety and transparent communication mitigate negative outcomes. Employee psychological adaptation to AI is modelled in this research, expanding the automation-augmentation conundrum with unique coping mechanisms and practical suggestions for human-centered AI governance. Organisational support, effective communication, and identity rebuilding are crucial to optimal adaption results.
Downloads
References
REFERENCES
Alawiye, P., Ishola, S., Okpara, B. I., Osakwe, C. C., & Odig, P. (2025). Leadership, Culture, and Employee Wellbeing in Dealing with Artificial Intelligence and Its Complexities: Effects on Mental Health in the Workplace. International Social Sciences and Education Journal, 3(4):114-130. https://doi.org/10.61424/issej.v3i4.603.
Atoyebi, T. A., & Sopuru, J. C. (2025). Humanizing AI in Service Workplaces: Exploring Supervisor Support as a Moderator in HPWSs. Sustainability, 17(17), 7892. https://doi.org/https://doi.org/10.3390/su17177892.
Badoo, A. N. A. (2026). Developing Organizational Psychology Frameworks to Prepare the U.S. Workforce for Artificial Intelligence Integration and Competitiveness. International Journal of Scientific Research and Modern Technology, 5(2), 62-72. https://doi.org/10.38124/ijsrmt.v5i2.1278.
Bankins, S., Ocampo, A. C., Marrone, M., Restubog, S., & Woo, S. E. (2023). A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice. Journal of Organizational Behavior, 45(2), 159-182. https://doi.org/10.1002/job.2735.
Barbosa, I., & Oliveira, E. R. D. (2026). Digital reskilling and workforce transformation: exploring identity, capability and adaptation in AI-mediated workplaces. Journal of Organizational Effectiveness: People and Performance, 1–19. https://doi.org/10.1108/joepp-12-2025-1109.
Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. SAGE Publications Ltd.
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Cooke, F. L., Decker, S., DeNisi, A. S., Dey, P. K., Guest, D., Knoblich, A. J., Malik, A., Paauwe, J., Papagiannidis, S., Patel, C., Pereira, V., Ren, S., … Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(4). https://doi.org/https://doi.org/10.1111/1748-8583.12524.
Dong, R. K. (2024). Psychological safety and psychosocial safety climate in workplace: A bibliometric analysis and systematic review towards a research agenda. Journal of Safety Research, 91(1), 1-19. https://doi.org/10.1016/j.jsr.2024.08.001.
Edmondson, A. C. & Bransby, D. P. (2022). Psychological Safety Comes of Age: Observed Themes in an Established Literature, Annual Review of Organizational Psychology and Organizational Behavior, 10, 55-78. https://doi.org/10.1146/annurev-orgpsych-120920-055217
Eshraghian, F., Hafezieh, N., Farivar, F., & Cesare, S. D. (2024). AI in software programming: understanding emotional responses to GitHub Copilot. Information Technology and People. 38(4), 1659–1685. https://doi.org/https://doi.org/10.1108/itp-01-2023-0084.
Feng, Y., Feng, Y., & Liu, Z. (2025). The Influence of Perceived Organizational Support on Sustainable AI Adoption in Digital Transformation: An Integrated SEM–ANN–NCA Model. Sustainability, 17(24), 1-39. https://doi.org/10.3390/su172411373.
Gölgeci̇, İ., Ritala, P., Arslan, A., McKenna, B., & Ali, I. (2024). Confronting and alleviating AI resistance in the workplace: An integrative review and a process framework. Human Resource Management Review, 35(2). https://doi.org/https://doi.org/10.1016/j.hrmr.2024.101075.
Gonzalez, K., Kanitz, R., & Briker, R. (2024). “AI Can’t Steal My Soul”: In the Age of AI, the Human Touch is Paramount for the Craft of Managing Change. The Journal of Applied Behavioral Science, 60(2). https://doi.org/https://doi.org/10.1177/00218863241279916.
Huffstadt, K. (2026). The Silent Impact of AI: Unveiling Motivational Side Effects in the Digital Workplace. AHFE International. https://doi.org/10.54941/ahfe1007094.
Ioannou, A. (2023). Mindfulness and technostress in the workplace: a qualitative approach. Frontiers in Psychology, 14. https://doi.org/https://doi.org/10.3389/fpsyg.2023.1252187.
Jia, J., Ning, X., & Liu, W. (2025). The consequences and theoretical explanation of workplace AI on employees: a systematic literature review. Journal of Digital Management, 1(1). 1-23. https://doi.org/https://doi.org/10.1007/s44362-025-00016-3.
Kim, B. J. & Kim, M. J. (2024). How artificial intelligence-induced job insecurity shapes knowledge dynamics: the mitigating role of artificial intelligence self-efficacy, Journal of Innovation & Knowledge, 9(4). https://doi.org/10.1016/j.jik.2024.100590
Kumar, A., Krishnamoorthy, B. & Bhattacharyya, S. S. (2023). Machine learning and artificial intelligence-induced technostress in organizations: a study on automation-augmentation paradox with socio-technical systems as coping mechanisms. International Journal of Organizational Analysis, 32 (4), 681-701. https://doi.org/10.1108/IJOA-01-2023-3581
Kunz, W. H., Sajtos, L., & Flavián, C. (2025). Beyond replacement: Human-machine collaboration in the age of AI. Journal of Service Management, 36(4), 477–494. DOI:10.1108/JOSM-04-2025-0194.
Lajoie, P., & Gendron, Y. (2025). From “audit machines” to tech‐savvy auditors: Auditors’’ quest for professional security with respect to digital transformation. Contemporary Accounting Research, 42(4). https://doi.org/https://doi.org/10.1111/1911-3846.70002.
Ley, M. (2023). Care Ethics and the Future of Work: a Different Voice. Philosophy & Technology, 36(1). https://doi.org/https://doi.org/10.1007/s13347-022-00604-5.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage Publications.
Liu, Y., Lei, H. & Qu, X. (2026). Approach or avoidance? A dual-pathway model of job crafting in response to generative AI and its impact on career sustainability, Frontiers in Psychology, 17. https://doi.org/10.3389/fpsyg.2026.1779227.
Liu, Y., Sheng, F., & Liu, R. (2025). Generative AI adoption and employee outcomes: a conservation of resources perspective on job crafting, career commitment, and the moderating role of liking of AI. Humanities and Social Sciences Communications, 12(1). https://doi.org/https://doi.org/10.1057/s41599-025-05656-4.
Mdrs, G., & Rebecca E. (2026). The Impact of AI Awareness on Counterproductive Work Behaviors of It Industry Workers in Colombo District: The Mediating Effect of Job Insecurity and The Moderating Role of Perceived Organizational Support. International Journal of Research and Innovation in Social Science, 10(1), 280-289. https://doi.org/10.47772/ijriss.2026.10100025.
Nguyen, M., Nham, T. P., Alghafes, R., Rahman, O., & Imre, G. (2026). Human-GenAI-based agent collaboration: How employee perceptions shape knowledge sharing, thriving, and well-being. Acta Psychologica, 263. https://doi.org/10.1016/j.actpsy.2026.106271.
Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). Sage Publications.
Qiao, Z. (2026). AI-induced job crafting: a systematic review of cognitive appraisal pathways. Frontiers in Psychology, 17. https://doi.org/10.3389/fpsyg.2026.1788385
Rachid, M., Maliki, S. E., Boussouf, Z., & Khal, M. Z. (2025). Generative AI and the Psychological Experience of Employees: Creative Opportunities and Risks of Cognitive Dependence. 2025 4th International Conference on Embedded Systems and Artificial Intelligence (ESAI). https://doi.org/10.1109/ESAI67033.2025.11438766.
Roemmich, K., Schaub, F., & Andalibi, N. (2023). Emotion AI at Work: Implications for Workplace Surveillance, Emotional Labor, and Emotional Privacy. Conference: CHI '23: CHI Conference on Human Factors in Computing Systems, 588, 1-20. https://doi.org/https://doi.org/10.1145/3544548.3580950.
Sandelowski, M. (2000). Focus on research methods: Whatever happened to qualitative description? Research in Nursing and Health, 23(4), 334–340. https://doi.org/10.1002/1098-240X(200008)23:4<334::AID-NUR9>3.0.CO;2-G
Sanseverino, D., & Ghislieri, C. (2026). Profiles of Chatbot Users in the Workplace: A Person‐Centred Exploration of Differences in Psychological Ownership and Performance. Advances in Public Health, 2026 (1). https://doi.org/10.1155/adph/4408159.
Schilhabel, S., Sankaranarayanan, B., Subedi, M., & Muraski, J. (2026). Exploring the impact of artificial intelligence on psychological well-being and inclusivity in higher education. Journal of Information, Communication and Ethics in Society. 1-17. https://doi.org/10.1108/jices-09-2025-0238.
Sebastian, R. & Sebastian, K. (2021). Artificial Intelligence and Management: The Automation–Augmentation Paradox. Academy of Management Review, 46 (1). https://doi.org/https://doi.org/10.5465/amr.2018.0072
Sharma, P., Deepthi, J. R., Naveen, S., Choudhary, P., Shree, N. B. & Patnayak, D. (2026). Digital Fatigue and Technostress in AI-Driven Organizations: An Empirical Analysis of Employee Burnout and Coping Mechanisms. Social Science Research Network. https://doi.org/10.2139/ssrn.6658838.
Sun, L., Hu, R., & Su, H. (2026). Unlocking human potential in the AI Age: how employee-AI collaboration transforms work engagement through dual psychological pathways. Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1705671.
Tasneem, F., Yasin, I., & Hashim, R. (2026). Exploring Job Satisfaction in Pakistan’s IT Industry: Impact of Generative AI (ChatGPT), Low Self-Esteem, and Job Crafting Within JD-R Theory. International Journal of Applied Research in Business and Management, 7(2). https://doi.org/10.51137/wrp.ijarbm.467.
Tracy, S. J. (2010). Qualitative quality: Eight “big-tent” criteria for excellent qualitative research. Qualitative Inquiry, 16(10), 837–851.
Westover, J. H. (2025). The Wellbeing Paradox in an AI World. Human Capital Leadership Review, 29(2). https://doi.org/10.70175/hclreview.2020.29.2.1.
Xu, J., Tang, X., Chang, E.-C., & Peng, H. (2024). Working with AI: the impact of organizational intelligent service strategy on employees’ perception of career achievement. Humanities and Social Sciences Communications, 11(1). https://doi.org/https://doi.org/10.1057/s41599-024-03265-1
Yanhong, G., & Li, W. (2025). AI technology adoption and intergenerational knowledge transfer among older employees. Frontiers in Psychology, 16. https://doi.org/https://doi.org/10.3389/fpsyg.2025.1673730.
Zhang, Y., Hsieh, C. W. & Liu, F. (2025). Employee Response to GenAI: Exploring the Effect of ChatGPT Dependence on Work Effort in a Public Service Context. Public Performance & Management Review, 48 (6). 1302-1330. https://doi.org/10.1080/15309576.2025.2537107.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 SHING FUNG CHOI (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.