Artificial intelligence is already used in veterinary practice, mainly to read images such as radiographs, to flag abnormal patterns in laboratory results, and to transcribe consultations and draft clinical notes. Used well it saves time and can catch things a tired human might miss at the end of a long day. What it does not do is take responsibility.
The veterinary surgeon remains accountable for every clinical decision, which means AI functions as a tool that supports judgement rather than a replacement for it, and the profession is still working out how these tools should be validated before they are trusted.
Interviewers have started asking about this, and they ask applicants your age partly because they assume you will have used AI yourself. That makes it a slightly unusual topic: you may have more direct experience of the technology than of veterinary medicine, and the risk is answering as a technology enthusiast rather than as a future clinician.
It will not come up in every interview, and it is the topic on this list that changes fastest. Prepare the principles rather than the products, because a specific tool you name may be superseded by the time you interview. Our guide to the veterinary hot topics for your vet school interview covers the wider set, and our common vet school interview questions guide covers the themes behind them.
How is AI actually used in veterinary practice?
The most established use is image interpretation. Software trained on large numbers of radiographs can highlight areas of concern and offer a report, which is genuinely useful in a first opinion practice at eleven at night with no radiologist available. Similar tools assist with cytology and with pattern recognition in blood results, flagging combinations that suggest a particular disease process.
The fastest growing use is administrative rather than diagnostic. Ambient scribe tools listen to a consultation and draft the clinical record, which matters more than it sounds: record keeping is a substantial part of a vet's day and a common reason for working late. Practices also use AI for triage messaging, appointment scheduling and drafting client communications.
It is worth separating those two categories in your head, because the risks are quite different. A poor administrative tool wastes time. A poor diagnostic tool can harm an animal.
What are the risks of using AI in veterinary medicine?
The first risk is accuracy, and specifically the confident wrong answer. These systems produce outputs that read as authoritative whether or not they are correct, and a plausible mistake is more dangerous than an obvious one because it is less likely to be challenged. Systems also perform differently on cases unlike their training data, which in veterinary medicine is a live concern given the range of species, breeds and equipment involved.
The second is responsibility. If a vet follows an AI suggestion and the animal is harmed, the vet is accountable. That is not a loophole to complain about, it is the point: professional responsibility cannot be delegated to a tool. It does raise a fair question about how a vet can be responsible for a system whose reasoning they cannot inspect.
The third is deskilling. If new graduates lean on AI for image interpretation before they have developed their own, the skill may never fully develop, and it is exactly the skill needed to notice when the AI is wrong. Add data protection questions about client information and recorded consultations, and the case for caution is substantial without being a case for refusal.
Of these, accountability is the one interviewers press on hardest, so make sure you can say clearly where responsibility sits before you walk in.
| Where AI helps | Where it needs care |
|---|---|
| Flagging abnormalities on radiographs out of hours | Confident wrong answers that read as authoritative |
| Drafting clinical notes so vets finish on time | Client data and consent around recorded consultations |
| Spotting patterns across large volumes of lab data | Performance drops on cases unlike the training data |
| Consistency, since software does not get tired | Accountability still sits entirely with the veterinary surgeon |
| Triage and routine client communication | New graduates may not build the skill to spot errors |
| Access to expertise in practices without specialists | Validation standards are still being established |
Could AI ever replace a vet?
This is the version of the question most applicants get, and the honest answer is more interesting than a simple no. Parts of the job are genuinely automatable, and pattern recognition on images is exactly the kind of task where software can perform very well. Pretending otherwise sounds defensive.
But a great deal of veterinary work is not pattern recognition. It is physical examination, which requires hands on an animal that cannot describe its symptoms. It is history taking from an owner who may not know what is relevant, or who may be embarrassed about something important. It is procedural skill in surgery. It is telling a family that their dog is dying and helping them decide what to do, then carrying it out with kindness.
And it is taking responsibility for a decision made with incomplete information, which is a professional act rather than a computational one.
So the more accurate framing is that AI will change what vets spend their time on rather than remove the need for vets. If it takes over some record keeping and offers a second opinion on an image, it may give a vet more time for the parts of the job that only a person can do. That is a better answer than either doom or dismissal.
Example vet school interview questions on AI
Below are the versions worth preparing. Notice how many are really about responsibility rather than about technology.
| Question you might be asked | What the interviewer is testing |
|---|---|
| Could AI ever replace vets? | Whether you understand what the job actually involves |
| Would you trust an AI diagnosis? | Appropriate scepticism without reflexive rejection |
| Who is responsible if the AI is wrong? | Grasp of professional accountability |
| How might AI change veterinary training? | Thinking about deskilling and how skills are built |
| Should AI be used to draft clinical records? | Separating administrative use from clinical use |
| How would you check whether an AI tool is reliable? | Instinct for validation and evidence |
| Do you use AI in your own studies? | Honesty, and how you think about using tools well |
How to answer a vet school interview question on AI
Most often it is simply: do you think AI will replace vets?
I would build the answer in this order. "I do not think it will replace vets, but I think it will change the job quite a lot, and I would not want to be dismissive about it because some of it is genuinely impressive. Reading radiographs is pattern recognition, and software can be very good at that, so I would expect AI to be a real help in a practice at night with no specialist available."
"What I do not think it can do is the rest of the consultation. It cannot palpate an abdomen or feel that something is not right. It cannot take a history from an owner who does not know which detail matters. It cannot do the surgery, and it cannot sit with a family while they decide whether to put their dog to sleep. Those are the parts of the job I would find hardest and also the parts I most want to do."
"The other thing is responsibility. If I followed an AI suggestion and the animal came to harm, that would still be my decision and my accountability, and I do not think you can pass that to a tool. So I would want to understand how a system had been validated before relying on it, and I would want to keep developing my own skills at reading images rather than outsourcing them early, because that is what would let me notice when the AI was wrong."
Conceding the true part first is what makes the rest persuasive, far more than defending the profession reflexively would. It gives concrete clinical examples of what cannot be automated rather than asserting that human touch matters. It lands on accountability, which is the professional core of the question. And the point about maintaining your own skill in order to catch errors is exactly the kind of second order thinking that separates a good answer from a very good one.
Four things weaken this answer. Technology enthusiasm without clinical grounding sounds like someone who wants to work in software. Blanket dismissal sounds incurious and slightly defensive. Claiming detailed knowledge of specific products is risky, because the interviewer may know more than you and the market changes fast. And forgetting the accountability point misses what the question is actually about.
How to prepare AI for your vet school interview
Prepare principles rather than products. Know the two broad categories of use, diagnostic and administrative, and why their risks differ. Be ready to name three things a vet does that are not automatable, and make them concrete. Have a position on responsibility, because that is where most versions of this question end up.
Be honest if you are asked whether you use AI yourself. Most applicants do, and an interviewer is far more interested in how thoughtfully you use it than in whether you abstain. Saying that you use it to test your understanding but check it against a proper source is a perfectly good answer.
This topic pairs naturally with veterinary telemedicine and remote prescribing, since both ask where technology helps and where clinical judgement must stay human, and with why vets leave the profession, because administrative burden is one of the pressures AI might genuinely relieve. If you would like to rehearse these answers with feedback from a vet, interview preparation runs through The Vet Offer Programme.
Common questions
How is AI used in veterinary practice?+
The main clinical use is image interpretation, where software highlights possible abnormalities on radiographs, along with pattern recognition in laboratory results. The fastest growing use is administrative: ambient tools that transcribe consultations and draft clinical records, plus triage messaging and client communication. The veterinary surgeon remains responsible for all clinical decisions.
Could AI replace vets?+
It is very unlikely to replace vets, though it will change the job. Pattern recognition tasks such as reading images can be automated well. Physical examination, taking a history from an owner, surgical skill, difficult conversations about euthanasia, and taking professional responsibility for decisions made under uncertainty are not tasks software can perform.
Who is responsible if an AI diagnosis is wrong?+
The veterinary surgeon. Professional accountability for clinical decisions cannot be delegated to a tool, so a vet who acts on an AI suggestion remains responsible for the outcome. This is why the profession emphasises understanding how a system was validated, and why AI is treated as decision support rather than as a decision maker.
What are the risks of AI in veterinary medicine?+
The main risks are confident wrong answers that read as authoritative, reduced performance on cases unlike the training data, deskilling if new graduates rely on AI before developing their own judgement, unclear validation standards, and data protection questions around client information and recorded consultations.
Do vet schools ask about AI at interview?+
Increasingly, yes, though not universally. It is usually framed as whether AI could replace vets or whether you would trust an AI diagnosis. Interviewers want measured engagement rather than enthusiasm or dismissal, and they are particularly interested in whether you understand that responsibility stays with the vet.