The Algorithmic Manager Paradox: Deconstructing the Chief AI Orchestrator’s Role in Modern HRM

Muhammad Alkirom Wildan

HRM; Algorithmic Management; Chief AI Orchestrator; Sociotechnical Systems.

The paper explores the critical transition of Human Resource Management from a traditional support function to the role of Chief AI Orchestrator, analyzing the Algorithmic Manager paradox, in which technical efficiency often triggers a decline in organizational trust and employee agency. Utilizing a critical literature review and qualitative meta-analysis of shifts observed in 2025–2026, the study evaluates how Black Box decision-making and surveillance-based metrics create algorithmic alienation and a transparency vacuum that undermines psychological contracts. The findings indicate that while predictive modeling may reduce turnover costs, active time tracking frequently fails to capture high-value cognitive output, leading to misaligned appraisals and a growing digital divide. Despite limitations to early 2026 tech adopters, the research offers significant practical implications, advising organizations to implement Human-in-the-loop (HITL) protocols and pivot HR toward ethical auditing to protect corporate culture. Ultimately, this review identifies a 2026 inflection point at which HR’s value proposition shifts from administrative to ethical orchestration, offering a novel framework for governing the tension between data-driven productivity and human-centric leadership.

Ali, A., Cichoń, D., & Abbas, A. (2026). AI-driven HRM digitization in effect: Mechanisms, conditions, and employee outcomes. Journal of Innovation and Knowledge, 13. https://doi.org/10.1016/ j.jik. 2025. 100919.
Ali, Adnan, Yang, Q., Ali, Afzaal, Ali, Z., & Noman, M. (2025). How and when AI-driven capabilities foster organizational sustainability: A moderated mediation analysis of digital literacy and green HRM. International Journal of Information Management, 85. https:// doi.org/10.1016/j.ijinfomgt.2025.102956
Barba, G., Corallo, A., Lazoi, M., & Lezzi, M. (2025). Large language models for competence-based HRM: A case study in the aerospace industry. Journal of Innovation and Knowledge, 10(5). https://doi.org/10.1016/j.jik.2025.100780
Bayo-Moriones, A., Erro-Garcés, A., & Lera-López, F. (2025). The role of technology, calculative and collaborative HRM and social trust in driving human resource analytics in European firms. Personnel Review. https://doi.org/10.1108/PR-06-2024-0561
da Silva, L. B. P., Pontes, J., Mosconi, E., Treinta, F. T., Yoshino, R. T., & de Resende, L. M. M. (2026). The future of HRM for intelligent manufacturing systems in the context of industry 5.0. Computers and Industrial Engineering, 211. https://doi.org/10.1016/j.cie.2025.111587
Do, H., Chu, L. X., & Shipton, H. (2025). How and when AI-driven HRM promotes employee resilience and adaptive performance: A self-determination theory. Journal of Business Research, 192. https:// doi.org/10.1016/j.jbusres.2025.115279
Gryncewicz, W., Zygala, R., & Pilch, A. (2023). AI in HRM: case study analysis. Preliminary research. Procedia Computer Science, 225, 2351–2360. https://doi.org/10.1016/j.procs.2023.10.226
Malik, A., Budhwar, P., & Kazmi, B. A. (2023). Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework. Human Resource Management Review, 33(1). https://doi.org/10.1016/ j.hrmr. 2022.100940
Pan, Y., & Froese, F. J. (2023). An interdisciplinary review of AI and HRM: Challenges and future directions. Human Resource Management Review, 33(1). https://doi.org/10.1016/j.hrmr.2022.100924
Prikshat, V., Islam, M., Patel, P., Malik, A., Budhwar, P., & Gupta, S. (2023). AI-Augmented HRM: Literature review and a proposed multilevel framework for future research. Technological Forecasting and Social Change, 193. https://doi.org/10.1016/j.techfore .2023. 122645
Prikshat, V., Malik, A., & Budhwar, P. (2023). AI-augmented HRM: Antecedents, assimilation and multilevel consequences. Human Resource Management Review, 33(1). https://doi.org /10.1016/ j. hrmr.2021.100860
Prikshat, V., Patel, P., Varma, A., & Ishizaka, A. (2022). A multi-stakeholder ethical framework for AI-augmented HRM. International Journal of Manpower, 43(1), 226–250. https://doi.org/10.1108/IJM-03-2021-0118
Rabenu, E., & Baruch, Y. (2025). Cyborging HRM theory: from evolution to revolution – the challenges and trajectories of AI for the future role of HRM. Personnel Review, 54(1), 174–198. https://doi.org/10.1108/PR-02-2024-0111
Shahid, S., Kaur, K., Mohyuddin, S. M., Prikshat, V., & Patel, P. (2025). Revolutionizing HRM: a review of human-robot collaboration in HRM functions and the imperative of change readiness. Business Process Management Journal, 31(7), 2892–2928. https://doi.org /10.1108/BPMJ-12-2023-0951
Shin, H. H., Choi, S., & Kim, H. (2025). Artificial Intelligence (AI) in Human Resource Management (HRM): A driver of organizational dehumanization and negative employee reactions. International Journal of Hospitality Management, 131. https://doi.org/10.1016/ j.ijhm.2025.104230.
Sohani, S. S., Pandey, J., Varma, A., & Ray, P. (2025). Is it necessary? A framework for assessing the utility of A.I. in HRM practices. Acta Psychologica, 254. https://doi.org/10.1016/j.actpsy.2025.104816
Sony, M. M. A. A. M., Amin, M. Bin, Ashraf, A., Islam, K. M. A., Debnath, N. C., & Debnath, G. C. (2025). Bias in AI-driven HRM systems: Investigating discrimination risks embedded in AI recruitment tools and HR analytics. Social Sciences and Humanities Open, 12. https://doi.org/10.1016/j.ssaho.2025.102082
Trautwein, Y., Zechiel, F., Coussement, K., Meire, M., & Büttgen, M. (2025). Opening the ‘black box’ of HRM algorithmic biases – How hiring practices induce discrimination on freelancing platforms. Journal of Business Research, 192. https://doi.org/ 10.1016/j.jbusres.2025.115298
Zhanseitov, A., Akybayeva, G., Mambetova, S., Kazbekov, T., & Berdimurat, N. (2025). The impact of artificial intelligence on the labour market and HRM. Procedia Computer Science, 272, 489–495. https://doi.org/10.1016/j.procs.2025.10.236
Zhou, Y., Wang, L., & Chen, W. (2023). The dark side of AI-enabled HRM on employees based on AI algorithmic features. Journal of Organizational Change Management, 36(7), 1222–1241. https://doi.org/10.1108/JOCM-10-2022-0308