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Driving sustainable innovation outcomes through employee AI collaboration with the mediating role of sustainable career capacities
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  • Published: 06 March 2026

Driving sustainable innovation outcomes through employee AI collaboration with the mediating role of sustainable career capacities

  • Zenglin Wu1,
  • Hong Gan1,
  • Luxin Zhang  ORCID: orcid.org/0009-0009-9932-76982,
  • Wan Mohd Hirwani Wan Hussain1 &
  • …
  • Sawal Hamid Md Ali3 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Business and management
  • Information systems and information technology
  • Science, technology and society

Abstract

Amid digital transformation, artificial intelligence (AI) integration into organizational work has reshaped employee-technology interactions and career trajectories. Despite growing interest in Employee-AI Collaboration (EAC), there is little research examining its impact on both sustainable career development and innovation outcomes. Drawing on Conservation of Resources (COR) theory and Social Cognitive Theory (SCT), this study examines how EAC influences Sustainable Innovation Outcomes (SIO) via Sustainable Career (SC) capacities and the moderating effect of Self-Efficacy in Using AI (SEUA). Using a cross-sectional survey of 294 employees, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test our hypotheses. Results show that EAC significantly enhances all the four SC dimensions: Resourceful, Flexible, Renewable, and Integrative capacities. These dimensions mediate the relationship between EAC and SIO, while EAC also exerts direct effects. Alternative model analysis suggests a mutually reinforcing relationship between SC and SIO. Notably, SEUA negatively moderates the relationship between EAC and the Integrative dimension, suggesting a counterintuitive attribution mechanism. These findings reveal how EAC drives innovation through both direct technological enhancement and indirect career capacity development pathways. This research extends technology empowerment theory into career development contexts, providing evidence-based recommendations for organizations to optimize AI integration strategies and career development policies.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Funding

Research on the Effectiveness Evaluation of the “Job–Course–Competition–Certification” Talent Cultivation Model: A Case Study of the Big Data Management and Application Major (GDJG2405) Guangdong Provincial Education Reform Project.

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Authors and Affiliations

  1. Business School, Nanfang College, Guangzhou, 510970, Guangdong Province, China

    Zenglin Wu, Hong Gan & Wan Mohd Hirwani Wan Hussain

  2. Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia

    Luxin Zhang

  3. Department of Electrical, Electronics and System Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia

    Sawal Hamid Md Ali

Authors
  1. Zenglin Wu
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  2. Hong Gan
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  3. Luxin Zhang
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  4. Wan Mohd Hirwani Wan Hussain
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Contributions

ZLW— Conceptualization, Methodology, Data Curation, Formal Analysis, and Writing—Original Draft.LXZ —Supervision, Conceptualization, Validation, Investigation, and Writing—Review & Editing.HG — Data Curation, Resources, and Writing—Review & Editing.WMHWH—Methodology, Data Curation, and ConceptualizationSHMA—Validation and Data Curation.All authors have read and agreed to the published version of the manuscript.

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Correspondence to Luxin Zhang.

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Wu, Z., Gan, H., Zhang, L. et al. Driving sustainable innovation outcomes through employee AI collaboration with the mediating role of sustainable career capacities. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41586-0

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  • Received: 11 December 2025

  • Accepted: 20 February 2026

  • Published: 06 March 2026

  • DOI: https://doi.org/10.1038/s41598-026-41586-0

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Keywords

  • employee-AI collaboration
  • sustainable career
  • sustainable innovation outcomes
  • self-efficacy in using AI
  • human-AI interaction
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