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Human or AI? Identity Salience Enhances Historically Marginalized (But Not Privileged) Consumers’ Choice of Algorithmic Service Providers

  • Yeseul Kim
  • , Dipayan Biswas
  • , Courtney Szocs
  • , Khalia Jenkins
  • University of South Florida
  • Pennsylvania State University
  • American University, Washington

Research output: Contribution to journalArticlepeer-review

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Abstract

When their identity is salient, consumers from historically marginalized and privileged groups are differentially influenced when it comes to choosing algorithmic service providers (e.g., AI-enabled tellers, chatbots, robots, and digital kiosks). Under identity salience, as it would be in a service context where the service providers are all from historically privileged groups, consumers from historically marginalized groups (e.g., Black people) become concerned about identity-based social judgment. Underrepresentation of historically marginalized groups in white-collar professions (e.g., financial services), regulatory pressures to abandon diversity hiring initiatives, and a tight labor market, make it increasingly difficult for companies to ensure diversity among frontline employees. How can managers provide consumers from historically marginalized groups the services they seek in non-diverse settings while balancing other constraints and reducing identity-based social judgment concerns? The results of a series of field studies and controlled experiments suggest that algorithmic service providers can provide a means to serve historically marginalized consumers in non-diverse service settings. The effect attenuates in service contexts where historically marginalized consumers are less concerned about identity-based social judgment. Interestingly, identity salience does not influence historically privileged consumers’ choice of algorithmic service providers.
Original languageEnglish
Number of pages21
JournalJournal of Marketing
Early online date8 Apr 2026
DOIs
Publication statusE-pub ahead of print - 8 Apr 2026

Data Availability Statement

The data that support the findings of this article are available from the authors.

Acknowledgements

The authors thank the JM review team for their helpful suggestions. The authors are also thankful to Steve Carnegie, Morgan Bryant, Edith Davidson, Andrea Dixon, Barbara Duffek, Latuesday Guy, Charles Richardson, Joe Ricks, Kenyatta Rosier, Abhijit Roy, and Julian Saint Clair for their help with this research and especially with the field studies.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research received funding from an ACR/Sheth Foundation Dissertation Award, an AMS Mary Kay Dissertation Award, and an ACR-TCR grant.

Keywords

  • algorithm-based service providers
  • human and AI frontline employees
  • historically marginalized groups
  • minority consumers
  • identity salience

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