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2026

United Kingdom · June 2026

AI Provider Information Framework for Veterinary Practice

Veterinary AI Transparency Alliance (led by RCVS and Digital Practice)

Draft framework, out for consultation

Professional associationUnited Kingdom

Sets out what AI providers should disclose to veterinary practices so tools can be adopted proportionately. Scrutiny is banded to risk: the more a tool influences records, reasoning, triage, diagnosis or treatment, the more disclosure and oversight it warrants. Requires a qualified human in charge who is competent to challenge the output, treats failure modes as being as important as best-case performance, and expects practices to explain AI use to clients and know where data goes.

United Kingdom · April 2026

Using artificial intelligence (AI) in practice — advice for the profession

Royal College of Veterinary Surgeons (RCVS)

Regulator advice

Professional associationUnited Kingdom

Applies the existing Code of Professional Conduct to AI rather than writing separate AI rules. Veterinary surgeons and registered veterinary nurses remain professionally responsible for clinical decisions, clinical decision making may not be wholly delegated to a tool, and a human must stay in the loop. Flags erosion of clinical skills through overreliance, bias and hallucination, and client confidentiality under the Data Protection Act 2018 and UK GDPR.

United Kingdom · February 11, 2026

Joint statement on the use of artificial intelligence in health and care professional education

RCVS with GCC, GOC, GOsC, GPhC and HCPC

Joint regulator statement

Professional associationUnited Kingdom

Six UK health and care regulators state a common position on generative AI in professional education and training, so that education providers running programs approved by more than one regulator are not subject to conflicting expectations. Issued through the education inter-regulatory group.

United States · January 21, 2026 (JVIM 40:1)

The influence, promise, and potential perils of artificial intelligence in veterinary medicine: a call for improved awareness and literacy

American College of Veterinary Internal Medicine (ACVIM) AI Task Force

Specialty college task force report, peer reviewed

Specialty collegeUnited States

Argues that AI literacy and rigorous validation must precede adoption if diagnostic and workflow gains are not to come at the cost of animal care and professional autonomy. Introduces a 12-item ACVIM AI Validation Factor checklist for appraising a tool, and calls for ethical frameworks, transparency and critical oversight.

Canada · January 2026

Use of Artificial Intelligence in Veterinary Medicine — Professional Standard

Alberta Veterinary Medical Association (ABVMA)

Enforceable professional standard

Professional associationCanada

A binding standard rather than advisory guidance. Members remain responsible and accountable for conduct when AI is used, must apply critical thinking to AI output including scribe applications, must never rely solely on AI for diagnosis or treatment, and must review AI-generated medical records for veracity, accuracy and completeness. Requires transparency with clients and consent where appropriate.

2025

United Kingdom · December 2025

BVA Policy Position on Artificial Intelligence in the Veterinary Profession

British Veterinary Association (BVA)

Association policy position

Professional associationUnited Kingdom

Eight general principles spanning clinical practice, education, research, epidemiology, government and practice management, framed around AI as a tool that supports rather than replaces the vet-led team. Includes a risk pyramid separating minimal, moderate, high and unacceptable functions, calls for veterinary involvement in AI design and validation, and recommends every veterinary workplace hold a written AI use policy.

United States + Europe · March 19, 2025 (JAVMA, June 2025)

ACVR and ECVDI position statement on artificial intelligence

American College of Veterinary Radiology (ACVR) and European College of Veterinary Diagnostic Imaging (ECVDI)

Specialty college position statement, peer reviewed

Specialty collegeUnited StatesEurope

Calls for good machine learning practice, transparency, error reporting, clinical expert involvement throughout development, secure patient data handling and post-implementation monitoring, with a veterinarian — preferably a board-certified radiologist or radiation oncologist — kept in the loop. States that no commercially available veterinary imaging AI product then met the required standards for transparency, validation or safety, and calls for unbiased third-party evaluation.

United States · March 2025

Regulatory Considerations of the Use of Artificial Intelligence in Veterinary Medicine

American Association of Veterinary State Boards (AAVSB)

White paper with position statement

Professional associationUnited States

Written for state licensing boards. Covers definitions, current regulatory frameworks, unlicensed practice, standards of practice, medical recordkeeping, data storage and confidentiality, and informed consent. Identifies fabricated output, training-data bias, automation bias and the absence of premarket approval for veterinary AI tools as the principal regulatory risks.

United States · 2025

What Do Veterinary Professionals Need to Know about Artificial Intelligence in 2025?

Veterinary Innovation Council and NAVC

Guidance document

Professional associationUnited States

A task force report covering the two applications then reaching general practice: radiology AI and AI scribing tools. Separates marketing claims from demonstrated scope, sets out how to evaluate a tool and what to ask a provider, and addresses automation bias, overinterpretation and compliance considerations.

New Zealand · 2025

AI use in veterinary services and regulation

New Zealand Veterinary Association (NZVA), Animal Welfare Network Aotearoa

Briefing paper

Professional associationNew Zealand

Reviews benefits, risks, applicable New Zealand law, and how the Veterinary Council of New Zealand's existing standards apply to AI use. Gives particular weight to data privacy and data sovereignty where client and patient data is processed offshore, and to algorithmic bias.

2024

Canada · December 2024

Use of Medical Devices Enabled by Artificial Intelligence in the Practice of Veterinary Medicine

College of Veterinarians of Ontario (CVO)

Guidance document

Professional associationCanada

A companion guide to the College's 2024 position statement, giving veterinarians a framework for weighing risk against mitigation when selecting AI-enabled medical devices. Notes that no single agreed set of definitions yet exists across jurisdictions, and restates that the licensed practitioner remains accountable for the choice.

United States · November 11, 2024

Policy Statement: Use of AI in Vet Med

Georgia Veterinary Medical Association (GVMA)

Association policy statement

Professional associationUnited States

Positions the veterinarian as the authority for diagnoses, treatment protocols and recommendations, with AI as support that does not replace professional judgement, spectrum-of-care advising or empathy. Requires compliance with data protection and privacy law, informed client consent explaining the tool's benefits and limitations, and protection of records from public exposure or access by large foundation models.

United States · July 2024

CVMA Policy on the Use of Artificial Intelligence in Veterinary Medicine

California Veterinary Medical Association (CVMA)

Association policy

Professional associationUnited States

Supports applying the FDA regulatory approach already used in human medicine, names the veterinarian as the decision-making authority, and states that no current technology replaces professional judgement and clinical expertise. Calls for standards from regulatory bodies, informed client consent, and confidentiality of client and patient data.

United Kingdom · August 19, 2024 (roundtable held May 20, 2024)

RCVS AI Roundtable Report

Royal College of Veterinary Surgeons (RCVS)

Roundtable report

Professional associationUnited Kingdom

Report of a roundtable of more than 100 participants from veterinary associations, educational institutions, technology companies, other professional regulators and the public sector, convened to set the RCVS direction of travel on regulating AI across clinical practice, research and education. The starting point for the RCVS guidance and Transparency Alliance work that followed.

Canada · March 2024

Embracing Innovation and the Digital Age in Veterinary Medicine

College of Veterinarians of Ontario (CVO)

Position statement

Professional associationCanada

Frames software as a medical device as the most challenging class of digital innovation and holds that every licensed veterinarian is accountable for their practice choices in a largely unregulated market. Asks veterinarians to weigh transparency of potential bias, explainability of outputs, robust prelaunch testing, and data privacy and security, while treating regulation as an avenue for safe forward movement rather than a barrier.

2023

Canada · October 12, 2023

Artificial Intelligence in Veterinary Medicine

Canadian Veterinary Medical Association (CVMA)

Position statement

Professional associationCanada

Warns that claimed benefits of veterinary AI tools may not be supported by sound evidence and that, absent structured regulatory oversight in Canada, commercial diagnostic systems can reach market with little supporting evidence — leaving practitioners exposed to liability for errors. Notes that platforms built on human systems may not translate to animals, and directs readers to their provincial or territorial regulator for binding standards.

2020

Europe · Adopted September 28, 2020

Report on the Impact of Digital Technologies and Artificial Intelligence in Veterinary Education and Practice

European Coordination Committee on Veterinary Training (ECCVT) — FVE, EAEVE and EBVS

Expert working group report

Professional associationEurope

The earliest of these documents. An expert working group delivered a SWOT analysis of digital technologies and AI in veterinary education and practice, together with recommendations on the Day One Competences graduates need for responsible use, competences that the technology can itself enhance, communication trends, undergraduate and postgraduate teaching methods, and linked quality assurance.