ArticleFrontiers in veterinary science2026
A systematic audit of transparency and validation disclosure in commercial veterinary artificial intelligence.
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.
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1 author.
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Abstract
Objective: To systematically identify the commercial market for clinical artificial intelligence (AI) products in veterinary medicine and audit their public documentation for transparency using a standardized, evidence-based instrument. Methods: A cross-sectional systematic audit of commercial AI tools was completed via a multi-channel search. Inclusion criteria required commercially available products with explicit AI claims and clinical functionality; administrative and direct-to-consumer tools were excluded. Publicly available documentation was archived and evaluated using a 25-point framework adapted from FDA and GMLP guidelines to assess data provenance, validation, safety, and usability. Results: Seventy-one AI products, available in the North American market were included, comprising Generative and Ambient ( Conclusions: The commercial veterinary AI market operates with systemic opacity. This audit reveals a significant "Transparency Gap"-a divergence where the sophisticated clinical capabilities marketed to veterinarians far exceed the publicly available evidence required to validate them. A significant gap exists between maturing imaging applications and unvalidated generative tools. The universal failure to report training demographics renders independent assessment of algorithmic bias impossible. Clinical relevance: Veterinarians currently bear the legal and ethical burden of validating AI tools without access to necessary performance data. The implementation of standardized transparency frameworks is urgently required to support evidence-based product selection and prevent patient harm from unvalidated technologies.
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