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How artificial intelligence shapes job anxiety: the mediating role of AI stress

Lingzhi Brian Fang et al.

Internet Research2026https://doi.org/10.1108/intr-09-2024-1462article
AJG 3ABDC A
Weight
0.50

Abstract

Purpose The aim of this study is to address the research gap in understanding the role of AI in the workplace, particularly by investigating how AI fosters job anxiety. By introducing the transactional theory of stress and coping (TTSC), this study engages with the conventional theory of stress and anxiety to determine the dual role of AI features in both exacerbating and alleviating job anxiety. Design/methodology/approach A large-scale survey was conducted, and 675 valid responses were collected. Structural equation modeling (SEM) was employed to analyze the entire theoretical model. A bootstrapping analysis was applied to assess the serial mediating role of AI stress in linking AI features to job anxiety. Findings The results revealed that AI explainability significantly enhances job anxiety. Conversely, algorithm transparency emerges as a mitigating factor, reducing job anxiety. These findings underscore the dual impact of AI, which acts as both a stressor and a potential alleviator depending on its design characteristics. Research implications This study highlights that algorithmic transparency can effectively mitigate AI-induced stress and job anxiety, underscoring the need for firms and managers to implement AI cautiously while strengthening governance merchanisms and prioritizing employee well-being and skill development. AI developers and policymakers should advance human-centered transparency and regulatory safeguards to reduce workplace anxiety and protect employees in AI-enabled environments. Originality/value This study pioneers a focus on the complex effects of AI in the workplace, diverging from conventional research that predominantly emphasizes the supportive role of AI. By integrating the TTSC, this study theoretically advances the understanding of AI stress mechanisms and empirically demonstrates the paradoxical effects of AI features. The dual-role framework offers novel insights for both academics and practitioners in addressing AI-related workplace challenges.

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https://doi.org/https://doi.org/10.1108/intr-09-2024-1462

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@article{lingzhi2026,
  title        = {{How artificial intelligence shapes job anxiety: the mediating role of AI stress}},
  author       = {Lingzhi Brian Fang et al.},
  journal      = {Internet Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/intr-09-2024-1462},
}

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Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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.