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The nexus between technology and workplace inequality has been a long-standing topic of scholarly interest, now heightened by the rapid evolution of artificial intelligence (AI). Our review moves beyond dystopian or utopian views of AI by identifying four perspectives—normative, cognitive, structural, and relational—espoused by scholars examining the impact of AI on workplace inequality specifically, and the structure and organization of work more broadly. We discuss the respective strengths, limitations, and underlying assumptions of these perspectives and highlight how each perspective speaks to a particular facet of workplace inequality: either encoded, evaluative, wage, or relational inequality. Integrating these perspectives enables a deeper understanding of the mechanisms, processes, and trajectories through which AI influences workplace inequality, as well as the role that organizational managers, workers, and policymakers could play in the process. Toward this end, we introduce a framework on the “inequality cascades” of AI that traces how and when inequality emerges and amplifies cumulatively as AI systems progress through the phases of development, implementation, and use in organizations. In turn, we articulate a research agenda for management and organizational scholars to better understand AI and its multifaceted impact on workplace inequality, and we examine potential mechanisms to mitigate its adverse consequences.
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This content will become publicly available on July 4, 2026
Rethinking How We Theorize AI in Organization and Management: A Problematizing Review of Rationality and Anthropomorphism
Abstract Artificial intelligence (AI) has long held the promise of imitating, replacing, or even surpassing human intelligence. Now that the abilities of AI systems have started to approach this initial aspiration, organization and management scholars face a challenge in how to theorize this technology, which potentially changes the way we view technology: not as a tool, but as something that enters previously human‐only domains. To navigate this theorizing challenge, we adopt the problematizing review method by engaging in a selective and critical reading of the theoretical contributions regarding AI, in the most influential organization and management journals. We examine how the literature has grounded itself with AI as the root metaphor and what field assumptions about AI are shared – or contested – in the field. We uncover two core assumptions of rationality and anthropomorphism, around which fruitful debates are already emerging. We discuss these two assumptions and their organizational boundary conditions in the context of theorizing AI. Finally, we invite scholars to build distinctive organization and management theory scaffolding within the broader social science of AI.
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- Award ID(s):
- 2211943
- PAR ID:
- 10628112
- Publisher / Repository:
- Society for the Advancement of Management Studies and John Wiley & Sons Ltd.
- Date Published:
- Journal Name:
- Journal of Management Studies
- ISSN:
- 0022-2380
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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