Artificial Intelligence Adoption and Employee Relations: A Conceptual Model of Trust as the Mediating Mechanism Linking AI-Assisted HR Decision-Making and Workforce Adaptability to Organizational Outcomes

References

[1] Bakir, A., Aydin, E., & Yildiz, S. (2025). Artificial intelligence awareness, career resilience, job insecurity and behavioural outcomes. PMC. https://pmc.ncbi.nlm.nih.gov/articles/PMC12481535/

[2] Berretta, S., Tausch, A., Peifer, C., & Kluge, A. (2023). Embracing the digital shift: Leveraging AI to foster employee well-being and engagement in remote workplace settings in the Asia Pacific region. Asia Pacific Management Review, 28(4), 390-400. https://doi.org/10.1016/j.apmrv.2024.02.001

[3] Brynjolfsson, E., Li, D., & Raymond, L. R. (2023). Generative AI at work (NBER Working Paper No. 31161). National Bureau of Economic Research.

[4] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008

[5] Ekuma, K. (2024). Artificial intelligence and automation in human resource development: A systematic review. Human Resource Development Review, 23(2), 199-229. https://doi.org/10.1177/15344843231224009

[6] Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627-660. https://doi.org/10.5465/annals.2018.0057

[7] Harper, R., & Millard, J. (2023). Algorithmic discrimination in human resource decision-making: Legal and organizational responses. Journal of Business Ethics, 184(3), 489-507.

[8] Langer, M., & König, C. J. (2023). Introducing a multi-stakeholder perspective on opacity, transparency and strategies to reduce opacity in algorithm-based human resource management. Human Resource Management Review, 33(1), 100881. https://doi.org/10.1016/j.hrmr.2021.100881

[9] Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46(1), 50-80. https://doi.org/10.1518/hfes.46.1.50_30392

[10] Malin, C., Fleiß, J., & Thalmann, S. (2025). Stakeholder-specific adoption of AI in HRM: Workers' representatives' perspective on concerns, requirements, and measures. Frontiers in Artificial Intelligence, 8, Article 1561322. https://doi.org/10.3389/frai.2025.1561322

[11] Moin, M. F., Behl, A., Zhang, J. Z., & Shankar, A. (2025). AI in the organizational nexus: Building trust, cementing commitment, and evolving psychological contracts. Information Systems Frontiers, 27(4), 1413-1424. https://doi.org/10.1007/s10796-024-10561-3

[12] Morandini, S., Fraboni, F., De Angelis, M., Puzzo, G., Giusino, D., & Pietrantoni, L. (2023). The impact of artificial intelligence on workers' skills: Upskilling and reskilling in organisations. Informing Science: The International Journal of an Emerging Transdiscipline, 26, 39-68.

[13] Nawaz, N., Arunachalam, H., Pathi, B. K., & Gajenderan, V. (2024). The adoption of artificial intelligence in human resources management practices. International Journal of Information Management Data Insights, 4(1), Article 100208. https://doi.org/10.1016/j.jjimei.2023.100208

[14] Obi, C. K., & Frempong, J. (2025). Artificial intelligence and the dual paradoxes: Examining the interplay of efficiency, resource consumption, and labor dynamics. arXiv. https://arxiv.org/abs/2504.10503

[15] Park, H., Ahn, D., Hosanagar, K., & Lee, J. (2021). Human-AI interaction in human resource management: Understanding why employees resist algorithmic evaluation at workplaces. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 1-15. https://doi.org/10.1145/3411764.3445304

[16] Prasad, K. D. V., & De, T. (2024). Generative AI as a catalyst for HRM practices: Mediating effects of trust. Humanities and Social Sciences Communications, 11(1), Article 1362. https://doi.org/10.1057/s41599-024-03842-4

[17] Priyanghaa, M. (2025). AI adoption in HR: Resistance, readiness, and the role of change management. Journal of Marketing & Social Research, 2(8), 104-110. https://doi.org/10.5455/jmsr.2025.401

[18] PwC. (2021). Hopes and fears 2021: The views of 32,500 workers. PricewaterhouseCoopers.

[19] Rousseau, D. M. (1995). Psychological contracts in organizations: Understanding written and unwritten agreements. Sage Publications.

[20] Shekhar, A., & Saurombe, M. D. (2026). Algorithmic anxiety: AI, work, and the evolving psychological contract in digital discourse. Frontiers in Psychology, 17, Article 1745164. https://doi.org/10.3389/fpsyg.2026.1745164

[21] Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285. https://doi.org/10.1207/s15516709cog1202_4

[22] Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42. https://doi.org/10.1177/0008125619867910

[23] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540

[24] Wen, Y., Wang, J., & Chen, X. (2025). Trust and AI weight: Human-AI collaboration in organizational management decision-making. Frontiers in Organizational Psychology, 3, Article 1419403. https://doi.org/10.3389/forgp.2025.1419403

@article{1719434,
      author = {Collins Vincent Tamunoseipriye, Dr. Helen Nneka Ofor},
      title = {Artificial Intelligence Adoption and Employee Relations: A Conceptual Model of Trust as the Mediating Mechanism Linking AI-Assisted HR Decision-Making and Workforce Adaptability to Organizational Outcomes},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {1},
      pages = {148-163},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719434.pdf},
      abstract = {The accelerating diffusion of artificial intelligence (AI) into human resource management has outpaced scholarly understanding of how AI-related organizational change actually shapes the employment relationship. Existing research tends to treat AI-assisted decision-making, employee adaptability, and employee trust in AI as parallel, co-equal predictors of relational outcomes such as satisfaction, engagement, and workplace trust, despite accumulating evidence that trust performs a mediating rather than a merely additive function. This conceptual paper addresses that gap by synthesizing the technology acceptance, unified technology acceptance and use, psychological contract, and trust-in-automation literatures into an integrative model, termed the AI-HR Relational Trust Cascade, in which employee trust in AI systems is positioned as the conversion mechanism through which AI-assisted HR decision-making and employee adaptability translate into employee relations outcomes, rather than as one variable operating alongside them.The paper adopts a systematic narrative review methodology, critically analysing peer-reviewed literature published predominantly between 2019 and 2026 across human resource management, organizational psychology, and information systems journals. The review finds consistent evidence that the transparency, explainability, and perceived fairness of AI-driven decisions determine whether AI adoption strengthens or erodes the psychological contract, and that adaptability functions as a precondition for, rather than a substitute for, trust formation. Where these conditions are absent, AI adoption is associated with technostress, perceived breach of the psychological contract, and declining engagement, even where the underlying technology performs efficiently. The paper concludes that organizations pursuing AI-enabled HR transformation without deliberately building employee trust risk converting efficiency gains into relational deficits. Theoretical contributions, practical implications for HR governance, and an agenda for future empirical validation of the proposed model are discussed.
},
      keywords = {Artificial Intelligence, Human Resource Management, AI-Assisted Decision-Making, Employee Trust; Psychological Contract, Employee Engagement, Workplace Trust, Technology Adoption, Employment Relations},
      month = {July},
      doi = {https://doi.org/10.64388/IREV10I1-1719434}
  }