Opportunity and threat: how employees’ perceptions of artificial intelligence influence job crafting

Huanran Wang et al.

Baltic Journal of Management2025https://doi.org/10.1108/bjm-09-2024-0525article
AJG 1ABDC B
Weight
0.48

Abstract

Purpose Artificial Intelligence (AI) application imposes a complicated and uncertain situation for employees to comprehend and react. Existing research has examined employees’ positive and negative perceptions of AI and their reactions separately. Little is known about how the two opposing perceptions of AI could coexist and interact to shape employees’ behavioral reactions. Drawing on the categorization theory, our research aims to examine how employees’ opportunity and threat perceptions of AI interact to influence job crafting and boundary conditions for this interaction. Design/methodology/approach We conducted a two-wave study of 250 employees in China who had experienced AI transformation in their organizations. SPSS and Hayes PROCESS were used to test the hypotheses. Findings The positive effect of employees’ opportunity perceptions of AI on job crafting was attenuated by their threat perceptions. This attenuating effect was stronger for younger employees. Originality/value Our research extends categorization theory and the literature on AI perceptions by demonstrating the interaction effect of employees’ opposing perceptions of AI on job crafting and identifying age as a boundary condition for this interaction.

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https://doi.org/https://doi.org/10.1108/bjm-09-2024-0525

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@article{huanran2025,
  title        = {{Opportunity and threat: how employees’ perceptions of artificial intelligence influence job crafting}},
  author       = {Huanran Wang et al.},
  journal      = {Baltic Journal of Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/bjm-09-2024-0525},
}

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Evidence weight

0.48

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.63 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.