The impact of AI Adoption on engineers’ Job Satisfaction and Organisational Culture: A Systematic Literature Review and Roadmap for Engineering Education

Authors

DOI:

https://doi.org/10.16920/jeet/2026/v39is3/26100

Keywords:

Artificial intelligence, Computer Engineering Occupation, Organisational Culture, Job Satisfaction, Socio- Technica Theory, Job Demands-Resources Model, Engineering Education

Abstract

This systematic review examines the impact of artificial intelligence (AI) adoption on the engineer’s well-being, job satisfaction, and the overall organisational culture. Our unconventional review is based on corporate data from leading consultancy firms such as PWC and Mackensy and 200 peer- reviewed articles that address the organisational environment for engineers in major industries such as energy, construction, and telecommunications. While AI enhances operational efficiency and skill development for engineers and supports the organisational culture, it concurrently exacerbates stress, autonomy erosion, and emotional labour in control-oriented environments. Our review pointed out six interconnected dimensions: (1) AI as opportunity versus threat, (2) gigification versus full automation, (3) emotional labour under algorithmic control, (4) human skills’ enduring relevance, (5) participatory implementation, and (6) ethical safeguards. These themes were conceptualised based on a mixed framework of Job Demands-Resources (JD-R) and Socio- Technical theories to explain how the workplace culture mediates AI’s psychosocial impacts on engineers. Our study presents evidence-based recommendations for human-centric AI integration in areas of co-design protocols, continuous upskilling, and transparent governance structures. This paper contributes to the foregrounding gap on “how AI reshapes the engineer’s well- being and the organisational culture as a whole”. It also has replicable findings for technical jobs that have a similar context to the engineers serving in the energy, construction, and telecommunication industries.

Downloads

Download data is not yet available.

Downloads

Published

2026-02-28

How to Cite

Mohamad, M., Saali, T., Laryeafio, M. N., Ayertey, S., & Nyame, D. (2026). The impact of AI Adoption on engineers’ Job Satisfaction and Organisational Culture: A Systematic Literature Review and Roadmap for Engineering Education. Journal of Engineering Education Transformations, 39(3), 79–90. https://doi.org/10.16920/jeet/2026/v39is3/26100

References

Arslan, A., Cooper, C., Khan, Z., Golgeci, I. & Ali, I. (2021). Artificial intelligence and human workers interaction at team level: a conceptual assessment of the challenges and potential HRM strategies.

International Journal of Manpower 43(1), pp. 75-88. https://doi.org/10.1108/IJM-01-2021-0052

Ashoer, M., Maseeh, H. I., Lim, X. J., Rofiq, A., & Zaenal, A. Z. (2025). Exploring the Role of Generative Artificial Intelligence Among Employees in the Hospitality Sector: Insights from an Extension of the Job Demands–Resources Theory. https://doi.org/10.1108/978-1-83662-586-520251001

Avik, S. C., Chowdhury, A., Al Maruf, M. A., Naha, R., & Ahammad, I. (2024, February).AI-Powered Resilience: Addressing the Mental Health Impact of Mass Layoffs in the Digital Age," 2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE), Vellore, India, 2024, pp. 1-6, doi: 10.1109/icETITE58242.2024.10493522

Brougham, D., & Haar, J. (2018). Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management & Organization, 24(2), 239–257. https://doi.org/10.1017/jmo.2016.55

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work progress and prosperity in a time of brilliant technologies. WW Norton & company.

Burdon, W. M., & Sorour, M. K. (2020). Institutional theory and evolution of “a legitimate” compliance culture: The case of the UK financial service sector. Journal of Business Ethics, 162, 47–80. https://doi.org/10.1007/s10551-018-3981-4

CIPD. (2023). People Profession 2023: International survey report. Available at: https://www.cipd.org/uk/knowledge/reports/peopleprofession-survey-2023/

Cummings-Koether, M. J., Durner, F., Shyiramunda, T. & Huemmer, M. (2025). Cultural Dimensions of Artificial Intelligence Adoption: Empirical Insights for Wave 1 from a Multinational Longitudinal Pilot Study. arXiv preprint. https://doi.org/10.48550/arXiv.2510.19743

Eldebeky, S. M., AlEnezi, S. S., Abdel-Maguid, M., Chowdhury, D., & Mohamad, M. (2025). Navigating AI in Education: Mobile Access, Opportunities, and Challenges in High Schools. International Journal of Interactive Mobile Technologies, 19(24).

Geroimenko, V. (2025). Generative AI: From Human– Computer Interaction to Human–Computer Creativity. In: Geroimenko, V. (eds) HumanComputer Creativity. Springer Series on CulturaComputing. Springer, Cham. https://doi.org/10.1007/978-3-031-86551-0_1

Gozman, D., Karanasios, S., Senyo, P. K., & Baba, M. (2022). FinTech ecosystem practices shaping financial inclusion: The case of mobile money in Ghana. European Journal of Information Systems, 31(1), 112–127. https://doi.org/10.1080/0960085X.2021.1978342

Hamed, A., Bansal, Y., Mohamad, M., Jimenez-Aranda, A., & Gaber, T. (2025). AI security in contactless payments and education: A review. Journal of Engineering Education Transformations, 20-25.

Hansen, C., Steinmetz, H., & Block, J. (2022). How to conduct a meta-analysis in eight steps: a practical guide. Management Review Quarterly, 72(1), 1-19. https://doi.org/10.1007/s11301-021-00247-4

Henkens B, Schultz CD, De Keyser A, Mahr D (2026), "The sound of progress: AI voice agents in service". Journal of Service Management, Vol. 37 No. 1 pp. 1–32, doi: https://doi.org/10.1108/JOSM06-2025-0269

Hutson, J., & Ceballos, J. (2023). Rethinking education in the age of AI: The importance of developing durable skills in the industry 4.0. Journal of Information Economics, 1(2).DOI:10.58567/jie01020002

Kaaria, A. G. (2023). Artificial Intelligence and Employee Well-Being: Balancing Technological Progressions with Human-Centric Workplace Strategies, a Research Agenda. East African Journal of Information Technology 7(1). https://doi.org/10.37284/eajit.7.1.2281

Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of management annals, 14(1), 366410. https://doi.org/10.5465/annals.2018.0174

Kinowska, H., & Sienkiewicz, Ł. J. (2022). Influence of algorithmic management practices on workplace well-being—Evidence from European organisations. Information Technology & People, 36(8), 21–42.

https://doi.org/10.1108/ITP-02-2022-0079

Koster, R., Balaguer, J., Tacchetti, A., Weinstein, A., Zhu, T., Hauser, O., Williams, D., Campbell-Gillingham, L., Thacker, P., Botvinick, M. & Summerfield, C. (2022). Human-centred mechanism design with Democratic AI. Nature Human Behaviour 6. https://doi.org/10.1038/s41562-022-01383-x

Kudina, O., & van de Poel, I. (2024). A sociotechnical system perspective on AI. Minds and Machines, 34, 21. https://doi.org/10.1007/s11023-024-09680-2

Kushnir, I. (2025). Thematic analysis in the area of education: a practical guide. Cogent Education, 12(1). https://doi.org/10.1080/2331186X.2025.2471645

Kyriakou, K., & Otterbacher, J. (2023). In humans, we trust: Multidisciplinary perspectives on the requirements for human oversight in algorithmic processes. Discover Artificial Intelligence, 3(1), 44.

Li, X., Seah, R. Y. T., & Yuen, K. F. (2025). Mental wellbeing in digital workplaces: The role of digital resources, technostress, and burnout. Technology in Society, 81, 102844. https://doi.org/10.1016/j.techsoc.2025.10284 4

Liu, N. C., Wang, Y. C., & Lin, Y. T. (2023). Employees’ adaptation to technology uncertainty in the digital era: an exploration through the lens of job demands– resources theory. IEEE Transactions on Engineering Management, 71, 7286-7297.doi: 10.1109/TEM.2023.3264293

Mason, S. A., & Kuttal, S. K. (2025). Diversity’s doubleedged sword: Analyzing race’s effect on remote pair programming interactions. ACM transactions on software engineering and methodology, 34(1), 1-45.

Mohamad, M., Balikel, A., Russell, C., Chowdhury, D., & Mahmoud, S. (2026). Artificial intelligence for business model innovation in digital sustainability companies: Multiple cases from the Netherlands.

World Journal of Entrepreneurship, Management and Sustainable Development, 22(1-2).DOI: 10.47556/J.WJEMSD.22.1-2.2026.7

Mohamad, M., Chowdhury, D., Russell, C., Balikel, A., & Kawalek, P. (2025). How GenAI transforms computer engineering education: The case of the Middle East and North Africa. Journal of Engineering Education Transformations, 3-19. https://doi.org/10.16920/jeet/2025/v39is1/25129

Mohamad, M. Niam, A. Bahadur, P. (2025) Tech-Driven Marketing: Strategic Integration of Information Systems in Marketing Management through Case Studies. Digital Horizons: Innovating Public Administration, Engineering, and Sustainable Business. Nova Science. https://doi.org/10.52305/TKMX3262

Montes, C. M., Penzenstadler, B. & Feldt, R. (2025). The Factors Influencing Well-Being in Software

Engineers: A Cross-Country Mixed-Method Study. arXiv preprint. https://doi.org/10.48550/arXiv.2504.01787

Naikar, N., Brady, A., Moy, G., & Kwok, H.-W. (2023). Designing human-AI systems for complex settings:

Ideas from sociotechnical systems and cognitive work analysis. Ergonomics, 66(11), 1669–1694. https://doi.org/10.1080/00140139.2023.2281898

Oliveira, P., Carvalho, J. M. & Faria, S. (2025). AI Integration in Organisational Workflows: A Case Study on Job Reconfiguration, Efficiency, and Workforce Adaptation. Information 16(9). https://doi.org/10.3390/info16090764

Ozer, M., Kose, Y., Kucukkaya, G., Mukasheva, A., & Ciris, K. (2024, July). Adapting to the AI disruption:

reshaping the IT landscape and educational paradigms. In World Congress in Computer Science, Computer Engineering & Applied Computing (pp. 366-374). Cham: Springer Nature Switzerland.

Pasca, R. (2022). Person–Environment Fit Theory. In Encyclopedia of Quality of Life and Well‑Being

Research. Springer. https://doi.org/10.1007/978-94-007-0753-5_2155

Qadir, J., Attique, M. A., Shoaib, S., & Ghaznavi, S. I. (2026). Can AI Chatbots Provide Coaching in Engineering? Beyond Information Processing Toward Mastery. arXiv preprint arXiv:2601.03693.

Radic A, Singh S, Singh N, Ariza-Montes A, Calder G, Han H (2025), "The good shepherd: linking artificial intelligence (AI)-driven servant leadership (SEL) and job demands-resources (JD-R) theory in tourism and hospitality". Journal of Hospitality and Tourism Insights, Vol. 8 No. 4 pp. 1494–1521, doi: https://doi.org/10.1108/JHTI-06-2024-0628

Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation

paradox. Academy of management review, 46(1), 192-210.https://doi.org/10.5465/amr.2018.0072

Rode, J. C., Huang, X., & Schroeder, R. G. (2022). Human resources practices and continuous improvement and learning across cultures. Journal of International Management, 28(4). https://doi.org/10.1016/j.intman.2022.100972

Routray, R., Choudhary, P. & Sinha, V. Intelligent technology and enhanced well-being: can artificial intelligence mitigate digital overload?. Futur Bus J 11, 268 (2025). https://doi.org/10.1186/s43093-025-00691-8

Ryan, R. M., & Deci, E. L. (2022). Self-Determination Theory. In Encyclopedia of Quality of Life and Well-Being Research (Living reference). Springer. https://doi.org/10.1007/978-3-319-69909-7_2630-2

Sadeghi, S. (2024). Employee Well-being in the Age of AI: Perceptions, Concerns, Behaviors, and Outcomes. arXiv preprint. https://doi.org/10.48550/arXiv.2412.04796

Sadeghian, S. (2022). The “artificial” colleague: Evaluation of work satisfaction in collaboration with non-human coworkers. In IUI ’22 (pp. 1–9). ACM. https://doi.org/10.1145/3490099.3511128

Schein, E. H. (2010). Organizational culture and leadership (4th ed.). Jossey-Bass. ISBN: 0470185864, 9780470185865

Seth, Jayshree. Amy C. Edmondson. (2026) How to Foster Psychological Safety When AI Erodes Trust on Your Team. Harvard Business Review. Available at: https://hbr.org/2026/02/how-to-foster-psychological-safety-when-ai-erodes-trust-on-your-team

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of business research, 104, 333-339.https://doi.org/10.1016/j.jbusres.2019.07.039

Thorpe, D., Bean, C., & Krieg, J. (2025). Associations between generative artificial intelligence usage, Job

Demands, Job Control and Burnout. AI & SOCIETY, 1-10.https://doi.org/10.1007/s00146-025-02764-2

Upeksha, S., Samarasinghe, D. T., Sanochana, M., Samarathunga, S. S., Rajamanthri, L., Samarakkody,

T., & Aluthwala, C. (2025, February). The Influence of Generative AI on work-life balance among female

software professionals in Sri Lanka. In 2025 5th International Conference on Advanced Research in Computing (ICARC) (pp. 1-6). IEEE. doi: 10.1109/ICARC64760.2025.10963119.

Van den Broek, S. J. C. E., Sankaran, S., de Wit, J. M. S., & de Rooij, A. (2024). Exploring the supportive role ofAI in participatory design: A systematic review. In PDC ’24 (Vol. 2) https://doi.org/10.1145/3661455.3669868

Wooten, K. C. (2001). Ethical dilemmas in human resource management: An application of a multidimensional framework, a unifying taxonomy, and applicable codes. Human Resource Management Review, 11(1-2), 159-175.https://doi.org/10.1016/S1053-4822(00)00045-0

Zadow, A., Loh, M. Y., Dollard, M. F., Mathisen, G. E., & Yantcheva, B. (2023). Psychosocial safety climate as a predictor of work engagement, creativity, innovation, and work performance: A case study of software engineers. Frontiers in Psychology, 14, 1082283.

Zárate-Torres R, Rey-Sarmiento CF, Acosta-Prado JC, Gómez-Cruz NA, Rodríguez Castro DY, Camargo J. Influence of Leadership on Human–Artificial Intelligence Collaboration. Behavioral Sciences. 2025; 15(7):873. https://doi.org/10.3390/bs15070873

Zayid, H., Alzubi, A., Berberoğlu, A., & Khadem, A. (2024). How do algorithmic management practices affect workforce well-being? A parallel moderated mediation model. Behavioral Sciences, 14(12), 1123. https://doi.org/10.3390/bs14121123

Zhang, A., Boltz, A., Wang, C. W., & Lee, M. K. (2022). Algorithmic management reimagined for workers and by workers: Centering worker well-being in gig work. In CHI ’22 (pp. 1–20). ACM. https://doi.org/10.1145/3491102.3501866

Zhao, X., Hossain, M. K., & Sun, P. P. (2026). The Facilitating Role of Enjoyment and Anxiety in Shaping (AI‐Mediated) Informal Language Learning and Confidence: An Explanatory Sequential Mixed‐Methods Investigation. Journal of Computer Assi