A Veterinary Innovation Council Guidance Document
Artificial intelligence (AI) in veterinary medicine promises faster documentation, enhanced clinical decision-making, and improved patient care. Tools that transcribe clinical records, integrate with electronic medical records, or interpret radiographs offer efficiency and new insights. Yet, current AI-driven solutions often fall short of their claims, pose questions about accuracy and privacy, and may not adhere to best practices. As these technologies evolve—expanding to advanced imaging modalities, predictive analytics, and deeper data integration—veterinarians must remain cautious. Carefully evaluating accuracy, cost, data security, and ethical implications is essential to ensure that AI complements, rather than compromises, professional judgment.
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Authors:
- Dr. Ryan Appleby, Assistant Professor, Diagnostic Imaging, Ontario Veterinary College, University of Guelph
- Nikhil Talgeri, Senior Director of Product Management at Covetrus
- Dr. Beth Venit, Chief Veterinary Officer at AAVSB
- Dr. Link Welborn, Chief Executive Officer at Veterinary Management Groups & Chief Veterinary Officer, Covetrus
- Dr. Eleanor Green, Founding Dean, Lyon College School of Veterinary Medicine
- Dr. Lauren Olavessen, Chief Veterinary Officer at Bitwerx
- Gary Peters, Cofounder at PupPilot
- Dr. Jessica Vogelsang, Chief Medical Officer, the American Animal Hospital Association