Algorithmic human resource management as a mode of algorithmic governance: transparency, fairness, and human agency in the digital workplace

The rapid digitalization of the workplace is reconfiguring the foundations of human resource management (HRM). This paper conceptualizes algorithmic HRM as a business process technology that transforms traditional people management practices through automation, predictive analytics, and workflow redesign. By comparing algorithmic and conventional HRM processes across six core domains—workforce planning, recruitment, training, performance management, compensation, and employee relations—the study demonstrates how algorithms shift HRM from intuition-driven decisions to data-based and adaptive systems. While these transformations offer efficiency gains, personalization, and new avenues for strategic value creation, they also raise critical concerns about transparency, fairness, privacy, and employee autonomy. The paper argues that algorithmic HRM represents both a technological and organizational frontier in the future of work, demanding hybrid governance approaches, ethical safeguards, and the cultivation of human capabilities that algorithms cannot replace. In doing so, it highlights implications for managers, workers, and policymakers navigating the challenges of an algorithmically mediated employment landscape.