Perceived Legitimacy of Organizational Disciplinary Decisions: Comparing Human, Human-AI, and AI Decision-Making

Background: The Industrial Revolution fundamentally altered the relationship between humans and machines. As tools evolved into systems that structured work, authority, and economic value, individuals increasingly became subject to technological forms of organization and control. Today, artificial intelligence may represent a similar shift - not in the production of goods, but in the production of decisions. While earlier machines transformed manual labor, AI systems increasingly participate in organizational judgment and disciplinary processes. In organizational contexts, AI is becoming integrated into human resource practices and decision-making, extending its role beyond operational support to influencing employment-related outcomes. Although such systems are often perceived as objective and efficient, they rely on historical data and statistical generalizations, which may raise concerns regarding fairness, accountability, and appropriate authority. At the same time, the increasing delegation of decision-making to AI systems may alter how individuals perceive organizational control and legitimacy. Despite the growing use of AI in workplace decision-making, limited research has examined how different forms of AI involvement influence perceived legitimacy in organizational disciplinary contexts. This study aims to address this gap by examining how decisions made by a human manager, a human manager supported by AI, or an autonomous AI system are perceived in terms of legitimacy Purpose of the study: This study examines how different forms of decision-maker involvement influence perceived legitimacy in organizational disciplinary decision-making. Specifically, it compares perceived legitimacy across three conditions: decisions made by a human manager, decisions supported by an AI system and confirmed by a human manager, and decisions made autonomously by an AI system. By employing an experimental vignette design that simulates a realistic workplace disciplinary situation, the study aims to capture participants’ subjective evaluations of legitimacy in response to identical outcomes that vary only in terms of decision-maker type. In doing so, the study isolates the role of human versus algorithmic authority in shaping perceptions of legitimacy. Furthermore, the study seeks to contribute to the emerging literature on AI in human resource management by examining whether the inclusion of human oversight mitigates potential legitimacy concerns associated with fully automated decision-making. By focusing on disciplinary decisions - where issues of authority, fairness, and accountability are particularly salient - the study provides insight into how employees may perceive and evaluate organizational control when it is exercised by human, hybrid, or AI-based systems. Broad research questions: What are individuals’ perceptions of the legitimacy of organizational disciplinary decisions when these decisions are made by a human manager, a human manager supported by AI, or an autonomous AI system?