"The rise of algorithmic management (AM) is helping to transform work and employment relationships, creating new challenges and opportunities alike. AM leverages machine-learning algorithms to help automate managerial functions. This raises key questions about its impact on work, organisations, and the broader society. This paper synthesises existing research on AM and categorizes scholarly insights into five theoretical perspectives: AM as a surveillance and control system, as a neutral tool, as an agentic boss, as a socio-technical process, and AM as a contradictory unity. While AM enhances coordination and efficiency, it also raises concerns such as pervasive surveillance, bias, dehumanization and worker alienation. We highlight the tensions between control and autonomy, transparency and opacity, and efficiency and fairness, illustrating the paradoxical nature of AM. This paper proposes a future research agenda, calling for ethical governance and responsible design of algorithmic systems to reap the benefits of AM while managing potential risks and mitigating harms."

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