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The workplace has experienced extensive digital transformation, in part due to artificial intelligence's commercial availability. Though still an emerging technology, emotional artificial intelligence (EAI) is increasingly incorporated into enterprise systems to augment and automate organizational decisions and to monitor and manage workers. EAI use is often celebrated for its potential to improve workers' wellbeing and performance as well as address organizational problems such as bias and safety. Workers subject to EAI in the workplace are data subjects whose data make EAI possible and who are most impacted by it. However, we lack empirical knowledge about data subjects' perspectives on EAI, including in the workplace. To this end, using a relational ethics lens, we qualitatively analyzed 395 U.S. adults' open-ended survey (partly representative) responses regarding the perceived benefits and risks they associate with being subjected to EAI in the workplace. While participants acknowledged potential benefits of being subject to EAI (e.g., employers using EAI to aid their wellbeing, enhance their work environment, reduce bias), a myriad of potential risks overshadowed perceptions of potential benefits. Participants expressed concerns regarding the potential for EAI use to harm their wellbeing, work environment and employment status, and create and amplify bias and stigma against them, especially the most marginalized (e.g., along dimensions of race, gender, mental health status, disability). Distrustful of EAI and its potential risks, participants anticipated conforming to (e.g., partaking in emotional labor) or refusing (e.g., quitting a job) EAI implementation in practice. We argue that EAI may magnify, rather than alleviate, existing challenges data subjects face in the workplace and suggest that some EAI-inflicted harms would persist even if concerns of EAI's accuracy and bias are addressed.
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This content will become publicly available on July 1, 2026
Artificial Intelligence at Work: An Integrative Perspective on the Impact of AI on Workplace Inequality
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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- Award ID(s):
- 2239538
- PAR ID:
- 10634009
- Publisher / Repository:
- Academy of Management Annals
- Date Published:
- Journal Name:
- Academy of Management Annals
- Volume:
- 19
- Issue:
- 2
- ISSN:
- 1941-6520
- Page Range / eLocation ID:
- 693 to 735
- Subject(s) / Keyword(s):
- artificial intelligence workplace automation augmentation organizations economy large language models
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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