TY - JOUR
T1 - The Rise of Algorithmic Management and Implications for Work and Organisations
AU - Zhang, Mingqiong Mike
AU - Cooke, Fang Lee
AU - Ahlstrom, David
AU - McNeil, Nicola
N1 - Publisher Copyright:
© 2025 The Author(s). New Technology, Work and Employment published by Brian Towers (BRITOW) and John Wiley & Sons Ltd.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - AI-driven workplace technology
KW - algorithmic management
KW - algorithmic management governance
KW - human resources
KW - managerial control
KW - responsible algorithmic management
KW - social relationship
UR - https://www.scopus.com/pages/publications/105007524741
U2 - 10.1111/ntwe.12343
DO - 10.1111/ntwe.12343
M3 - Review article
AN - SCOPUS:105007524741
SN - 0268-1072
JO - New Technology, Work and Employment
JF - New Technology, Work and Employment
ER -