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Employee Taking Charge in AI-Driven HRM - A Social Exchange Perspective
Conference paper   Peer reviewed

Employee Taking Charge in AI-Driven HRM - A Social Exchange Perspective

Rahman Khan, Kashif Ullah Khan, Athar Hameed Butt Dr., Jeoung Yul Lee, Ghulam Murtaza and Muhammad Zeeshan
Academy of Management Annual Meeting Proceedings
Academy of Management (AOM) Annual Meeting, 86th (Philadelphia, United States, 31/07/2026–04/08/2026)
01/07/2026

Abstract

AI-driven HRM Psychological ownership Taking charge at work Organizational transparency Artificial Intelligence or Cybernetics Human Resources
Drawing on the social exchange perspective (Blau, 1964), we propose that AI-driven HR practices reduce psychological ownership, which, in turn, lowers the tendency to take charge. However, organizations that remain transparent in their processes are less likely to reduce employees' psychological ownership, thereby overcoming the challenge of low taking charge at work. This research employs a mixed-methods approach, utilizing three studies with vignette experiments and time-lagged surveys to test the hypothesized model. The findings of a vignette study (Study 1) conducted with 142 employees in China confirmed that individuals in a high AI-driven HRM condition are significantly less likely to take charge than those in a low AI-driven HRM condition. Additionally, results from the 2x2 vignette-based study (Study 2), which included 190 employees, showed a significant interaction between organizational transparency and AI-driven HRM in predicting psychological ownership. Specifically, individuals in the high AI-driven HRM-high organizational transparency condition had significantly higher psychological ownership than those in the high AI-driven HRM-low organizational transparency condition. Our two-wave survey of 377 Chinese employees (Study 3) confirmed that AI-driven HRM is negatively related to employee taking charge at work. Furthermore, employee psychological ownership towards organizations significantly mediates the relationship between AI-driven HRM and taking charge at work. Also, it was found that organizational transparency significantly buffers the negative impact of AI-driven HRM on psychological ownership, which, in turn, leads to higher levels of taking charge at work.

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