Algorithmic Management. Theoretical Perspectives and Implications for Organizational Development

Abstract

Algorithmic management leverages data-driven algorithms and artificial intelligence to automate managerial functions traditionally executed by human managers. This paper provides a comprehensive overview of algorithmic management, exploring its definitions and emergence in gig economy platforms and traditional workplaces. It delves into key sociological and organizational theories—including Weber's bureaucracy, Critical Management Studies (CMS), and technological rationality—to frame the discussion. The impact of algorithmic management on employee autonomy, digital surveillance, and forms of worker resistance is examined, alongside its role in shaping organizational structures, enhancing efficiency, and driving innovation. Ethical implications, particularly concerning fairness, transparency, and bias, are critically analyzed. While algorithmic management offers potential benefits such as improved efficiency and decision-making, it also raises significant concerns about worker autonomy, power imbalances, and ethical considerations. The paper underscores the need for a nuanced understanding and responsible implementation of algorithmic management to harness its advantages while mitigating its drawbacks.