Robots as Managers? Organizational Justice, Power Asymmetries, and the Future of AI Supervision

Abstract

This commentary critically expands on Wolf and Stock-Homburg’s (2025) study of employee acceptance of robotic managers, which relies on Expectation-Disconfirmation Theory and the Technology Acceptance Model. We argue that acceptance is not purely rational or individual but shaped by power dynamics, workplace culture, and ethical concerns. Drawing from organizational behavior and AI ethics, we show that compliance often replaces genuine trust, particularly in high power-distance contexts. Algorithmic opacity, bias, and technostress can undermine well-being and fuel resistance. By embedding AI acceptance within broader social and organizational frameworks, this paper challenges the assumptions of existing models and proposes new research directions. It offers practical guidance for implementing robotic management systems in ethical, inclusive, and psychologically sustainable ways.