- Documentation steals 30-40% of a veterinarian's working hours - roughly 10 minutes per consult, over 3 hours a day at 20 consults.
- 62% of vets say administrative work interferes with clinical care often or almost always, in a field where 87% of staff report medium-to-high burnout.
- AI scribes generate SOAP notes from voice recordings in real time - the clearest win, giving those hours back.
- AI drafts the notes and assists on imaging; the diagnosis, the treatment, and the care of the animal stay with the vet.
Veterinary medicine has a documentation problem that's quietly driving people out of the profession. The direct answer: AI's clearest value for veterinarians is scribing - generating clinical notes from the visit so vets reclaim the hours currently lost to documentation - which directly addresses the administrative burden and burnout straining the field, while every diagnosis and treatment decision stays with the veterinarian.
The problem AI actually solves
The numbers are stark. Vets spend roughly 10 minutes per consult on clinical notes; at 20 consults a day, that's over 3 hours of documentation - time that comes out of lunch breaks, family evenings, or just gets skipped. All told, documentation steals 30-40% of a veterinarian's working hours. And it's not a minor annoyance: 62% of vets say administrative work interferes with clinical care often or almost always, in a profession where 87% of staff report medium-to-very-high burnout. Documentation isn't just eating time - it's a genuine factor in people leaving veterinary medicine.
The scribe: the clearest win
This is where AI lands most cleanly. AI scribes (like CoVet) generate SOAP notes from voice recordings in real time - the vet has the consult, talks naturally, and the structured note is drafted by the time the appointment ends, ready for review and sign-off. That converts the after-hours 'notes backlog' into a quick review, giving back a large share of those 3+ daily hours. For a burned-out profession, that's not a productivity nicety - it's a retention tool.
Diagnostic AI is a secondary, more cautious use - radiograph interpretation, dermatological analysis, and blood-panel review as a second read - and triage tools help owners assess urgency before deciding to come in. But scribing is the win with the fastest, least-risky payback.
Where the line holds
As in all clinical work, the boundary is firm. AI drafts documentation and offers a second read on imaging; it does not diagnose the animal, decide treatment, or replace veterinary judgment. Every AI-drafted note requires the vet's review and sign-off, because the vet is accountable for its accuracy and for the care. (Vets are appropriately cautious - 54% cite reliability as the top barrier.) The right frame is AI for the paperwork and the second opinion, the veterinarian for the medicine. Used that way, AI gives an overstretched vet their evenings back without touching the care - which is exactly why it's being adopted.
What this means for veterinary practices
The clearest, safest place to start is scribing - and building AI into your specific practice workflow is a matter of clinical and operational judgment, not code. That's the MakerSquare premise. Our use cases show what building administrative tools around a real clinical workflow looks like, with the vet in charge of care.
Nobody became a vet to spend a third of the day writing notes. That's the part worth handing off.
MakerSquare is a 2-week in-person AI builder program in Austin, TX for professionals who want to build AI into the paperwork side of their work while keeping the care human. See what two weeks of hands-on building looks like.