AI Resilience Report forVeterinarians

Good news first: AI in veterinary medicine is mostly being used to help vets, not replace them. Right now, the biggest impact is on the paperwork side of the job. Roughly 4 in 10 veterinary professionals are already using AI regularly, and they see it as a tool that can help them organize information, draft records, flag potential abnormalities, or reduce time spent on repetitive tasks — not as a substitute for veterinarians.

AI "scribes" are the fastest-growing example: the University of California-Davis School of Veterinary Medicine adopted the ScribbleVet digital scribe, which records exams and drafts SOAP notes so veterinarians can finish medical records in minutes rather than hours, while still keeping hands-on medical decisions with the clinician. In diagnostics, radiology tools can pre-read X-rays, but AI flags findings quickly and at a lower cost yet requires veterinarians to verify the output, with radiology platforms drawing skepticism over false positives and inconsistent reads. A pilot study in JAVMA even found that six commercial veterinary radiology AI services frequently missed diagnoses on canine abdominal X-rays ^[1], meaning hands-on tasks like surgery, euthanasia, and grief counseling stay firmly human.

Adoption is speeding up because the tools are cheap, easy to try, and target the exact pain points vets complain about: admin work and burnout. While surveys indicate growing adoption, they also highlighted common concerns including data security and reliability, transparency, and professional accountability, and investment across diagnostic imaging, practice management software, and clinical documentation is accelerating ^[2]. But adoption will stay careful in clinical areas.

Reference committee members cited scheduling and inventory management as lower-risk uses, while emphasizing that higher-stakes tasks such as medical records transcription or triage support require human oversight, with the degree of oversight matching the risk level. Ethics also matter: delegates warned against AI being used to create "virtual veterinarians" and stressed protecting the veterinarian's responsibility for clinical judgment ^[3]. International research shows the same pattern — a Frontiers study of 455 Chinese veterinary professionals ^[4] found high AI use despite low familiarity, suggesting adoption is running ahead of training.

For students today, that means the safest bet is learning the human skills — surgery, empathy, communication — that AI still can't touch.