Evidence map›Paper›PMID 42205962›Full record

ArticleFrontiers in psychology2026

The impact of generative artificial intelligence (GenAI) usage patterns on employee creativity.

Qiang Li, Shuangshuang Li

Abstract read
In one paragraph

Article in Frontiers in psychology, 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
0cells of the map it votes in
0citing papers in PubMed
–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

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

2 authors.

Qiang LiSchool of Business Administration, Lanzhou University of Finance and Economics, Lanzhou, China.
Shuangshuang LiSchool of Business Administration, Lanzhou University of Finance and Economics, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Generative AI (GenAI) is transforming the way employees innovate, yet existing research has mainly focused on its adoption contexts and usage frequency. Methods: Based on a three-wave lagged survey design with 381 valid matched employees from knowledge-intensive firms in China, this exploratory empirical study develops and tests a model grounded in the exploration-exploitation framework, with knowledge integration capability as the core mediator and task complexity as the moderator. Results: Results show that: (1) Exploitative GenAI use is more strongly positively associated with incremental creativity than radical creativity; (2) Exploratory GenAI use is more strongly positively associated with radical creativity than incremental creativity; (3) Employees' knowledge integration capability plays a critical complementary mediating role in the above relationships; (4) Task complexity positively moderates the relationships between GenAI usage patterns and knowledge integration capability. Discussion: This study improves the theoretical precision of understanding human-AI co-creativity and provides evidence-based guidance for organizational GenAI strategies.

Indexed as

employee creativitygenerative artificial intelligence (GenAI)knowledge integration capabilityself-determination theorytask complexity

Identifiers

PMID42205962
PMCPMC13202233

What OpenQuestion holds

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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.