Evidence map›Paper›PMID 41890159›Full record

ArticleFrontiers in veterinary science2026

The adoption paradox for veterinary professionals in China: high use of artificial intelligence despite low familiarity.

Shumin Li, Xiaoyun Lai

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 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.

Shumin LiCollege of Veterinary Medicine, Jilin University, Jilin, China.
Xiaoyun LaiWest East Small Animal Veterinary Conference, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The global integration of artificial intelligence (AI) into veterinary medicine is advancing, yet its adoption in major markets like China remains uncharacterized. This study aimed to provide the first exploratory analysis of AI perception and adoption among veterinary professionals in China. Methods: A cross-sectional survey was administered to 455 veterinary professionals in China from May to July 2025. Data on AI familiarity, adoption rates, application priorities, and perceived drivers and barriers were analyzed using descriptive statistics and thematic analysis. Results: We identified a distinct adoption paradox: 71.0% of respondents incorporated AI into their workflow, yet 44.6% of these active users reported low familiarity with the technology. Adoption was primarily practitioner-driven and focused on core clinical tasks, including AI-assisted disease diagnosis (50.1%) and prescription calculation (44.8%). The primary barrier to use was concern about AI reliability and accuracy (54.3%). A strong consensus (93.8%) emerged supporting regulatory oversight of AI by veterinary authorities. Discussion: The adoption paradox is driven by a practitioner-led, "inside-out" integration model where AI is used to augment clinical capabilities, countered by an "interpretability gap" that limits trust and familiarity. This contrasts with the more administrative, "outside-in" pattern seen in North America. The findings underscore a need for specialized veterinary AI tools, enhanced training focused on critical appraisal, and robust regulatory frameworks to safely harness AI's potential in one of the world's largest veterinary markets.

Indexed as

artificial intelligenceChinaclinical decision makingsurveytechnology adoptionveterinary medicine

Identifiers

PMID41890159
PMCPMC13012951

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.