A Critical Review of Artificial Intelligence in People Management

Book chapter


Chang, K., Cheng, K. and Sandland, S. 2024. A Critical Review of Artificial Intelligence in People Management. in: Adisa, T. A. (ed.) HRM 5.0: Unpacking the Digitalisation of Human Resource Management Palgrave Macmillan. pp. 35-56
AuthorsChang, K., Cheng, K. and Sandland, S.
EditorsAdisa, T. A.
Abstract

Artificial Intelligence (AI) seems omnipotent and ubiquitous in the workplace, but managers and employees have mixed views about its merits in practice. In this chapter, the opportunities and constraints of AI-driven management policy and practices are critically discussed, through an in-depth review of both conceptual research and empirical study, drawing on three theoretical perspectives (i.e., job replacement, psychological contract, and demands-resources theories). Following the theories-informed analyses, four meaningful discoveries are revealed. These are: (i) a manager’s experiences, attitude, and understanding of AI are highly influential, which in turn may affect the design and implementation of AI-driven management policies; (ii) the utility of AI-driven management policies does not necessarily guarantee productivity and should not be treated as an elixir to fix poor employee performance; (iii) managers are liable to learn AI and understand its characteristics prior to the implementation of AI-driven management policies; where applicable, a dry-run or pilot practice should be arranged in advance; and (iv) managers should remain cautious of AI’s influence in their managerial practices, as AI has the potential to become a job-demand or job-resource, affecting their employees either psychologically or behaviorally. In conclusion, the current chapter aims to offer new unique insights to AI-driven management literature, hence advancing knowledge in the field of AI policymaking and managerial practices. Limitations and suggestions for future studies are also discussed.

Book titleHRM 5.0: Unpacking the Digitalisation of Human Resource Management
Page range35-56
Year2024
PublisherPalgrave Macmillan
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Publication dates
Online17 Jul 2024
Publication process dates
Deposited08 Aug 2024
Edition1
ISBN9783031589126
9783031589119
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-58912-6_3
Copyright holder© 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG
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