CLINICAL FOCUS MONTH:
AI LITERACY IN VETERINARY PRACTICE WITH COVET
This November, Elearning.Vet will shine a partner spotlight focus on CoVet.
AI is becoming part of everyday veterinary practice, but understanding how it works is essential to using it well. Why do large language models sometimes generate incorrect information? What are AI hallucinations, and how do they differ from other limitations? And what should veterinary professionals look for when reviewing AI-generated clinical content?
This Clinical Focus Month, CoVet explores these questions through practical examples and a closer look at AI-assisted documentation. We'll demonstrate how CoVet turns everyday clinical language into structured veterinary records, how clinicians can review and personalise the output, and where features such as differential diagnoses fit into the process. We'll also consider what growing AI adoption means for veterinary education, including AI literacy, clinical reasoning, and concerns about losing or never fully developing essential skills.
On-Demand Webinar
When AI Gets It Wrong: Understanding AI Hallucinations and Clinical Judgement in Veterinary Practice
Presented by Dr Adele Xavier BVSc FRCVS DipECEIM PhD
AI tools are increasingly used to support veterinary professionals with clinical documentation, communication, and information gathering. But how much can we trust the information they produce?
Large language models can generate convincing answers that are incomplete, inaccurate, or unsupported. Understanding why this happens is an important part of developing AI literacy and using these tools responsibly.
In this session, Dr Adele Williams Xavier explores how large language models work, what AI hallucinations are, and why errors can occur even when the output sounds credible.
Using practical veterinary examples, we'll look at the difference between hallucinations, missing information, and other limitations of AI-generated clinical content. We'll also examine how AI-assisted documentation can support everyday workflows, including the role of clinician review and the appropriate use of AI-generated differential diagnoses.
Finally, we'll consider the implications for veterinary education and professional development. As AI becomes more capable, how can veterinary professionals maintain the clinical reasoning skills needed to question, evaluate, and act on its output?
This session is designed for veterinary professionals interested in understanding AI and using it thoughtfully in clinical practice.
Enter your details to watch on-demand:
LEARNING OBJECTIVES:
By the end of this session, participants should be able to:
- Explain how large language models generate responses and why apparently convincing information may be incorrect
- Distinguish AI hallucinations from other limitations, including missing information, transcription errors, and unsupported clinical interpretations
- Identify practical steps for evaluating AI-generated clinical records, including checking factual accuracy, completeness, and consistency with the original consultation
- Describe the appropriate role of AI-generated differential diagnoses and explain why independent clinical reasoning remains essential
- Discuss the implications of AI adoption for veterinary education, clinical skills development, and responsible professional practice
Dr Adele Xavier BVSc FRCVS DipECEIM PhD
Dr Adele is an equine internal medicine specialist and veterinary AI expert. She has led the development of AI tools for the veterinary sector. She is a thought leader on responsible and ethical AI adoption, speaking and writing internationally about AI literacy for veterinary medicine.
She runs an AI consultancy for the veterinary profession, supporting vets and practices on their AI adoption journeys. She works part time with CoVet, a veterinary AI copilot designed to assist vets during consultations.
2026 End-of-Year Survey: AI in Veterinary Practice
Complete the survey to be in with a chance of winning £250!
How are veterinary professionals using AI in 2026, and what do they expect from it in the years ahead?
CoVet's 2026 End-of-Year Survey explores how AI is being adopted across veterinary practice, what professionals find most useful, and what concerns remain. From clinical documentation and decision-making to data privacy, professional judgement, and wellbeing, the survey examines how AI is affecting everyday veterinary work.
Whether you use AI daily, have tried it and stopped, or haven't used it at all, we'd like to hear your perspective. The findings will help build a clearer picture of where veterinary AI stands today and what the profession needs as we head into 2027.
Why Clinical Excellence Must Be Built Into Veterinary AI
What makes an AI tool suitable for veterinary practice? Clinical expertise plays an important role in how AI tools are developed, tested, and evaluated. This article explores why veterinary involvement matters, how clinical teams help identify errors and improve AI-generated documentation, and what veterinary professionals should look for when assessing AI tools.
It also examines why no AI system should be treated as infallible, and why reviewing AI-generated records remains an essential professional responsibility.
CoVet is the AI-powered assistant built by veterinary professionals who understand the realities of life in the clinic, designed to simplify operations and reduce administrative strain.
Backed by decades of hands-on experience, CoVet's in-house medical team informs every feature with real-world insight. Its context-aware platform adapts to the unique needs of general practice, specialty, and large-animal medicine, while providing enterprise-grade performance and privacy compliance for practices of every size, from solo DVMs to global veterinary groups.
By combining automation with intuitive design, CoVet empowers veterinary teams to enter each exam more prepared and leave confident that every step is complete, allowing them to spend more time caring for patients.
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