We read the public research on AI in veterinary practice — AAHA, AVMA, the BVA, the Merck–AVMA wellbeing study, and peer-reviewed journals — and pulled the figures that matter into one place. Every number on this page links to its original source.
Updated 8 June 2026 · a synthesis of public research, not a Vetch survey
Across the research, the pattern repeats: the people most positive about AI are the ones already using it. Peer-reviewed work finds familiarity is the strongest predictor of both optimism and adoption — and the AAHA read shows enthusiasm rising in lockstep with daily, hands-on use. The gap to close is experience, not interest.
“Vets want to stop doing something they don’t enjoy — like updating medical records by hand.”
In the largest North American read, 39.2% of veterinary professionals report using AI tools, and 69.5% of those users reach for it daily or weekly. In the UK, the BVA puts daily use at 1 in 5 vets (21%) — led by radiography (44%) and lab diagnostics (27%), with ambient scribes the fastest-growing category.
The clearest near-term win is record-keeping. Vendors report ambient AI scribes cutting documentation time by up to ~80% and recovering 1–2 hours per clinician per day. These are supplier figures, not independent trials — but they point at the same place association data does: writing notes is where the time goes.
Why does any of this matter? The Merck–AVMA Wellbeing Study of 10,000+ professionals finds roughly half of veterinarians report burnout. JAVMA research links that burnout to “burden transfer” — the administrative load that lands on the team. Less typing is not a convenience story; it is a retention story.
Industry guidance puts veterinary no-show rates in the 10–28% range, with forgetting cited as the leading cause. Vendors report automated, well-timed reminders cutting missed appointments by 30–50%. Treat the exact percentages as supplier estimates; the direction — automation reclaims booked revenue — is consistent across providers.
The barriers are specific, not vague fear. In the AAHA read, 70.3% name accuracy and reliability as their top concern, 53.9% flag data security and privacy, and 42.9% cite a lack of training and knowledge. Roughly 15.5% remain clearly opposed. Tools that earn trust here win; tools that hand-wave it stall.
The strongest predictor of optimism is hands-on use: peer-reviewed work finds familiarity with AI drives both enthusiasm and adoption. With the AI-in-animal-health market projected to grow sharply, the open question for 2026 is not whether vets adopt, but which workflows they trust AI to touch first.
Cite this page for the synthesis. When you quote a specific figure, please link the original source listed beside it — this report compiles others’ research, it doesn’t replace it.
Vetch. (2026). AI in veterinary practice 2026: A synthesis of public research. Vetch. https://vetch.vet/reports/ai-in-practice-2026
This page is updated as new research lands. If you spot a newer study or a figure we should correct, tell us the source and we’ll review it — credit included.
The research above is where the whole profession is heading. The demo shows how Vetch specifically gets there — less typing, fewer no-shows, calmer days. Thirty minutes, real practice data, founders on the call.
