How Veterinarians Are Using ChatGPT: Real-World Applications, Benefits, and Challenges

With the release of ChatGPT by OpenAI, veterinarians, veterinary educators, and researchers have begun exploring how large language models (LLMs) can be integrated into veterinary medicine. Generative AI (tools like ChatGPT) is showing promise in improving efficiency, communication, and education — but with caveats. Recent reviews and studies provide a useful picture of current usage, potential, and pitfalls.

Benefits

From the studies so far, some of the main advantages identified are:

1. Time-Saving / Efficiency
   Drafting documents, client instructions, educational materials, etc., can be much faster. This frees up veterinarian time for clinical decision-making. Frontiers+2PMC+2

2. Improved Communication
   Helps translate technical or medical language into terms clients can understand. Generate consistent messaging. PMC+1

3. Learning Support
   Students and educators report benefits for review, reinforcement of concepts, comparative anatomy, generating practice questions. intjmorphol.com+1

4. Idea Generation and Creativity
   For research proposals, marketing ideas, writing styles, etc. ChatGPT provides a springboard for creativity. Frontiers+1

Challenges, Risks, and Ethical Considerations

While promising, there are several things veterinarians are cautious about, according to the literature:

• Accuracy / Hallucinations
  ChatGPT sometimes generates plausible‐sounding but incorrect or misleading content. This is especially risky for diagnostics or medical advice. Users must verify all outputs. Frontiers+1

• Data Privacy / Confidentiality
  Using real patient data in prompts risks exposing private or sensitive information; there may be regulatory / legal issues, especially with client consent. Frontiers+1

• Authorship / Intellectual Property
  Who owns or is responsible for text generated by ChatGPT? How to appropriately credit or declare use of AI in scientific writing. Frontiers

• Bias, Generalization Limits
  ChatGPT reflects biases in its training data. Also, it may not reflect the latest evidence or region-specific norms. Breed, species, regional disease prevalence may vary; LLMs aren’t always up to date. Frontiers

• Regulatory / Liability Issues
  If a veterinarian relies on AI and something goes wrong, who is responsible? Are there guidelines/regulations for AI use in veterinary medicine? The literature suggests this area is underdeveloped. Frontiers

Best Practices & Guidelines for Use

From papers and expert thought leaders, here are suggested practices for using ChatGPT responsibly in veterinary medicine:

• Always verify content / cross-check multiple sources, especially medical advice.

• Use de-identified data whenever possible, especially in prompts.

• Establish clear internal protocols: when is AI used, who reviews the outputs, how to flag uncertainties.

• Use prompts carefully, with good context, species, breed, region, etc., to improve relevance.

• Train staff and students on what ChatGPT can and cannot do.

• Disclose use of AI in research / publications where relevant.

• Keep current with AI tools’ updates and limitations.

Case Study: “ChatGPT in Veterinary Medicine: a Practical Guidance…” (Chu et al.)

A very recent mini-review (“ChatGPT in veterinary medicine: a practical guidance of generative artificial intelligence in clinics, education, and research” by Candice P. Chu et al.) summarizes many of these points. Frontiers+1

Some highlights from that review:

• In a survey, ~84% of veterinary professionals and students were familiar with AI applications; ~70% reported using AI tools weekly or daily. Frontiers

• There's strong interest in using LLMs for daily clinic workflows, education, and research writing.

• But many are skeptical about reliability, accuracy, data security, and lack of formal training.

• The review offers concrete examples: using ChatGPT to generate SOAP notes, summarise patient histories, build exam prep content, etc. Frontiers

Outlook: Where Things Are Likely Heading

Based on current trends, here are areas where greater adoption and innovation are likely:

• More specialized veterinary LLMs or GPT models trained/fine-tuned on veterinary data to improve species accuracy.

• Integrated tools within practice management software: e.g., prompts built in for progress notes, reminders, client messaging, triage.

• Regulatory guidance: definitions, ethical guidelines, best practices for AI/LLM use in veterinary care.

• Better image / multimodal AI: e.g., using LLMs with vision (e.g. GPT-4’s vision capabilities) to assist with interpreting radiographs, pathology slides, wound images. The literature notes interest in this. Frontiers+1

• Educational platforms leveraging LLMs for simulation, case-based learning, or adaptive assessment.

Conclusion

Veterinarians are increasingly exploring and implementing ChatGPT and other generative AI tools. The main gains are in efficiency, communication, and education. But there are significant risks, especially with accuracy, ethics, and privacy. Responsible implementation, verification, and human oversight remain essential.