Evidence map›Paper›PMID 41792237›Full record

ArticleScientific reports2026

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

Zenglin Wu, Hong Gan, Luxin Zhang, Wan Mohd Hirwani Wan Hussain, Sawal Hamid Md Ali

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zenglin WuBusiness School, Nanfang College, Guangzhou, 510970, Guangdong Province, China.
Hong GanBusiness School, Nanfang College, Guangzhou, 510970, Guangdong Province, China.
Luxin ZhangGraduate School of Business, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia. ukm.edu.academic@gmail.com.ORCID http://orcid.org/0009-0009-9932-7698
Wan Mohd Hirwani Wan HussainGraduate School of Business, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia.
Sawal Hamid Md AliDepartment of Electrical, Electronics and System Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia.

Funding

Guangdong Provincial Department of Education GDJG2405
6 · The paper itself

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.

Indexed as

Artificial IntelligenceCooperative BehaviorCross-Sectional StudiesFemaleHumansMaleSelf Efficacyemployee-AI collaborationhuman-AI interactionself-efficacy in using AIsustainable careersustainable innovation outcomes

Identifiers

PMID41792237
PMCPMC13096237

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.