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From despair to hope: the nonlinear impact of AI-induced job insecurity on employees’ innovative behavior

Huanyi Zhong et al.

Journal of Knowledge Management2026https://doi.org/10.1108/jkm-10-2025-1491article
AJG 2ABDC A
Weight
0.37

Abstract

Purpose This study aims to investigate the complex relationship between artificial intelligence (AI)-induced job insecurity and employee innovative behavior. It examines a potential U-shaped relationship between these variables, with knowledge hiding behavior as a mediator and trait resilience as a moderator. The research specifically explores whether trait resilience might amplify rather than mitigate the positive effect of AI-induced job insecurity on knowledge hiding behavior, revealing its potential dark side in organizational contexts. Design/methodology/approach A two-wave survey was conducted through the Credamo platform, collecting data from 485 Chinese office employees across multiple industries. The study used established scales to measure AI-induced job insecurity, knowledge hiding behavior, innovative behavior and trait resilience. Data analysis was performed using SPSS 27.0 and Amos 27.0, using hierarchical regression and bootstrap methods to test the hypothesized relationships. Findings Results confirmed a significant positive U-shaped relationship between AI-induced job insecurity and innovative behavior. Knowledge hiding behavior partially mediated this relationship. Notably, trait resilience positively moderated the connection between AI-induced job insecurity and knowledge hiding behavior. Employees with higher trait resilience demonstrated a stronger tendency to engage in knowledge hiding when experiencing AI-induced job insecurity, revealing an unexpected negative aspect of this typically positive trait. Originality/value This study breaks new ground by identifying a U-shaped relationship between AI-induced job insecurity and innovative behavior. It reveals the dark side of trait resilience, demonstrating its potential to strengthen counterproductive knowledge behaviors. These findings provide novel theoretical insights into employee adaptation to AI technologies and offer important practical implications for organizational management in the digital transformation era.

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https://doi.org/https://doi.org/10.1108/jkm-10-2025-1491

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@article{huanyi2026,
  title        = {{From despair to hope: the nonlinear impact of AI-induced job insecurity on employees’ innovative behavior}},
  author       = {Huanyi Zhong et al.},
  journal      = {Journal of Knowledge Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/jkm-10-2025-1491},
}

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From despair to hope: the nonlinear impact of AI-induced job insecurity on employees’ innovative behavior

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Evidence weight

0.37

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

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
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.