Evidence map›Paper›PMID 40893848›Full record

ArticleFrontiers in psychology2025

When digital-AI transformation sparks adaptation: job crafting and AI knowledge in job insecurity contexts.

Chengcheng Sha, Tianlong Chai

Abstract read
In one paragraph

Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

2 authors.

Chengcheng ShaDepartment of Economics and Trade, Guangxi Eco-Engineering Vocational & Technical College, Liuzhou, China.
Tianlong ChaiSchool of Civil Engineering and Architecture, Guangxi University of Science and Technology, Liuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: As AI technology continues to rise, numerous studies have explored its impact on employee behavior. However, little is known about employees' responses to the integration of AI in the digital transformation process. Drawing on Conservation of Resources Theory, this study aims to examine the impact of digital-AI transformation on employees' job crafting behaviors, focusing on the mediating role of job insecurity and the moderating effect of AI knowledge. Methods: A two-wave survey was conducted among 400 employees actively using AI tools in digitally transforming organizations, resulting in 370 valid responses. Data were analyzed using SPSS 22.0 and the PROCESS macro (version 3.3) to test the proposed hypotheses. Results: The results indicate that digital-AI transformation has a significant positive effect on employees' job crafting ( Discussion: This study extends the application of Conservation of Resources Theory by emphasizing the potentially positive role of job insecurity under specific contextual conditions, while also offering a critical reflection on the ethical implications of using job insecurity as a motivational tool. It is suggested that organizations should leverage employees' AI knowledge to enhance job crafting, rather than relying on stress as a driver. Future research is encouraged to explore additional antecedents of job crafting.

Indexed as

AI knowledgeconservation of resources theorydigital-AI transformationjob craftingjob insecurity

Identifiers

PMID40893848
PMCPMC12390811

What OpenQuestion holds

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LicenceCC BY
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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.