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Empathetic creativity as a ‘shield’: A dual-path study of the impact of artificial intelligence usage on employee work outcomes

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  • Jiao, Yuchen
  • Huang, Yuling
  • Wen, Tong
  • OuYang, Mengyan

Abstract

Currently, artificial intelligence is being rapidly deployed in frontline services, collaborating with employees in an increasing number of tasks. While this brings many benefits, it is also encroaching on the “skill toolbox†of frontline employees, subjecting them to mounting technological pressure. As a result, identifying key skills that are compatible with intelligent machines and helping employees cope with the challenges posed by AI, has become a focal point in academic research. However, the specific skills and mechanisms through which employees can adapt to this transformation remain unclear. This study combines the transactional model of stress and complementarity theory to explore the role of empathetic creativity as a key skill in this process. Through a two-wave survey and a semi-structured interview, the study finds that when employees have high empathetic creativity, the use of AI enhances their positive affective work prospection, thereby increasing their work effort. However, when employees have low empathetic creativity, AI may induce negative affective work prospection, leading to time theft behavior at work. This study highlights the important role of empathetic creativity in helping service industry employees cope with the challenges of AI, providing valuable practical insights for companies in shaping competitive advantages and employee training.

Suggested Citation

  • Jiao, Yuchen & Huang, Yuling & Wen, Tong & OuYang, Mengyan, 2025. "Empathetic creativity as a ‘shield’: A dual-path study of the impact of artificial intelligence usage on employee work outcomes," Journal of Retailing and Consumer Services, Elsevier, vol. 85(C).
    • Handle: RePEc:eee:joreco:v:85:y:2025:i:c:s0969698925000803
    DOI: 10.1016/j.jretconser.2025.104301
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    References listed on IDEAS

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    1. Loureiro, Sandra Maria Correia & Guerreiro, João & Tussyadiah, Iis, 2021. "Artificial intelligence in business: State of the art and future research agenda," Journal of Business Research, Elsevier, vol. 129(C), pages 911-926.
    2. Anat Perry, 2023. "AI will never convey the essence of human empathy," Nature Human Behaviour, Nature, vol. 7(11), pages 1808-1809, November.
    3. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    4. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    5. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    6. Huang, Yingying & Gursoy, Dogan, 2024. "How does AI technology integration affect employees’ proactive service behaviors? A transactional theory of stress perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    7. Cheng, Bao & Lin, Hongxia & Kong, Yurou, 2023. "Challenge or hindrance? How and when organizational artificial intelligence adoption influences employee job crafting," Journal of Business Research, Elsevier, vol. 164(C).
    8. Argyro Avgoustaki & Almudena Cañibano, 2020. "Motivational Drivers of Extensive Work Effort: Are Long Hours Always Detrimental to Well‐being?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 59(3), pages 355-398, July.
    9. Darıcı, Sefer & Riaz, Muhammad & Demir, Gülay & Gencer, Zekiye Tamer & Pamucar, Dragan, 2024. "How will I break AI? Post-Luddism in the AI age: Fuzzy MCDM synergy," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    10. Argyro Avgoustaki & Hans T. W. Frankort, 2019. "Implications of Work Effort and Discretion for Employee Well-Being and Career-Related Outcomes: An Integrative Assessment," ILR Review, Cornell University, ILR School, vol. 72(3), pages 636-661, May.
    11. Mohr, Lois A. & Bitner, Mary Jo, 1995. "The role of employee effort in satisfaction with service transactions," Journal of Business Research, Elsevier, vol. 32(3), pages 239-252, March.
    12. Biyun Hu & Crystal M. Harold & Dayoung Kim, 2023. "Stealing Time on the Company’s Dime: Examining the Indirect Effect of Laissez-Faire Leadership on Employee Time Theft," Journal of Business Ethics, Springer, vol. 183(2), pages 475-493, March.
    Full references (including those not matched with items on IDEAS)

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