arbiter
JournalsAccount

Starting with trust: unraveling the impact of AI trust on employee digital performance

Zilong Li & Yanhua Zhou

Baltic Journal of Management2025https://doi.org/10.1108/bjm-03-2025-0177article
AJG 1ABDC B
Weight
0.46

Abstract

Purpose This study aims to investigate the relationship between AI trust (AIT) and employee digital performance (EDP), with employee–AI collaboration (EAC) as a mediator. Additionally, the study examines how digital self-efficacy (DSE) moderates this process. Design/methodology/approach This study conducted a multi-wave questionnaire survey among 210 employees in China. Statistical analyses were conducted using AMOS 24 and the PROCESS macro in SPSS 27. Findings AIT has a positive relationship with EAC; EAC mediates the relationships between AIT and digital-enabled task performance (DETP) as well as between AIT and digital-enabled innovation performance (DEIP); DSE positively moderates the relationship between AIT and EAC, while also positively moderating the mediating role of EAC in the relationships between AIT and both dimensions of EDP. Originality/value Utilizing self-determination theory, this study constructs a moderated mediation model between AIT and EDP, revealing that EAC serves as a critical mechanism facilitating the transition from trust to performance enhancement. Additionally, the study identifies the significant boundary role played by employees’ DSE.

4 citations

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1108/bjm-03-2025-0177

Or copy a formatted citation

@article{zilong2025,
  title        = {{Starting with trust: unraveling the impact of AI trust on employee digital performance}},
  author       = {Zilong Li & Yanhua Zhou},
  journal      = {Baltic Journal of Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/bjm-03-2025-0177},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Starting with trust: unraveling the impact of AI trust on employee digital performance

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.46

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

F · citation impact0.37 × 0.4 = 0.15
M · momentum0.60 × 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.