The Tool Desk
Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Veterinary AI can help a clinic review images, spot patterns, organize records, or handle repetitive documentation. It does not examine your pet, interpret every finding in context, or take responsibility for a diagnosis and treatment plan. In an interview published September 27, 2026, Michael Q. Bailey, DVM, DACVR—the 2025–2026 AVMA president and a board-certified veterinary radiologist—describes AI as support for veterinary teams, not a substitute for them. Whether a tool helps a particular patient depends on what it does, the quality of its data, and a veterinarian’s judgment.
What AI can help a veterinary team do
Bailey describes AI as an aid for tasks that can support clinical work. Its output is something a veterinary professional evaluates, not a decision that stands on its own.
Review images and surface patterns
In radiology and other diagnostic modalities, Bailey says AI can flag areas of concern for a veterinarian to assess. It may also help with routine image work, such as putting radiographs in order, or serve as another set of eyes. Analysis of subtle changes over time may help a clinician notice progression earlier, but the interview does not establish a general accuracy rate or guarantee that every tool improves outcomes.
Support prediction and research
An AVMA statement from July 21, 2025, discussed examples including forecasting chronic disease, matching dogs with lymphoma to medications, and analyzing images for tumors and fractures. These are examples of applications the AVMA has discussed; they do not establish that a particular product is available, validated for your pet, or appropriate for an individual treatment decision.
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Reduce repetitive administrative work
AI scribes and voice-to-text systems may reduce the time teams spend on documentation, Bailey says, potentially leaving more room for client communication and clinical care. The AVMA statement also identifies automated recordkeeping, streamlined training, and analysis of client feedback as possible uses. The AVMA’s professional education material cautions that applications vary: some may deliver value, while others fall short, so readiness and effectiveness need evaluation.
What AI cannot do for your pet
An AI tool can process information it receives; it cannot collect everything a veterinarian can learn during an examination. Bailey points to hands-on assessment and even a patient’s smell as information that a remote or computational tool may not capture. An image flag or device reading therefore needs to be interpreted alongside the animal’s history, examination, and other findings.
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Bailey puts responsibility with the veterinarian and the veterinary team under that veterinarian’s supervision: they make care decisions and treatment plans in consultation with the client. AI may inform that process, but it does not own the diagnosis or replace discussion of choices with you.
Wearables can add data, but data are not a diagnosis
Pet wearables may record activity, sleep, behaviors such as shaking or scratching, food consumption, ECGs, or other vital parameters. Features differ by device; a reading is useful only if its limitations and context are understood.
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Bailey says that if veterinarians rely on a wearable for diagnostic purposes, it needs evaluation for accuracy and reliability in the species for which it is intended. The interview does not identify a validated collar model or compare consumer devices. If you bring tracker data to an appointment, ask your veterinarian what the device actually measures and whether those measurements are useful for your pet.
Why AI can get things wrong
Bailey says performance depends on both training data and the information entered into a system. He identifies inconsistent labeling, biased datasets, and poor-quality inputs as potential sources of inaccurate outputs. Veterinary tools also have to contend with differences among species and substantial variation in canine anatomy. The interview supplies no broadly applicable numerical error rate, so a single accuracy figure should not be assumed to describe veterinary AI as a whole.
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Remote veterinary care has limits, too
Bailey uses telehealth as an umbrella term for remote health information, education, guidance, or care. The categories he names include teleadvice, teletriage, telemedicine, telemonitoring, teleconsulting, and telesupervision. They are not interchangeable: some involve general guidance, while telemedicine involves diagnosing or treating a patient.
Bailey describes telemedicine as requiring an existing veterinarian-client-patient relationship (VCPR), generally established through an in-person examination or a visit to the animal’s premises. He describes an exception for a life-threatening emergency or severe animal suffering until a VCPR can be established. He also says AVMA policy generally does not allow a VCPR to be established solely electronically in most states. State laws and rules vary, so these interview comments are not jurisdiction-specific legal advice; check current requirements where you live and consult official policy for legal questions.
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How to think about AI at your pet’s clinic
- Ask what the tool is used for. Image organization, note-taking, and decision support are different jobs, with different implications for your pet’s care.
- Ask how its output is checked. A veterinarian should interpret AI findings in the context of an examination and the rest of the clinical record.
- For wearables, ask whether they suit your animal. Find out what the device records and whether its accuracy and reliability have been evaluated for the intended species and diagnostic use.
- Keep the conversation with your veterinary team. Ask how a result affects the options being considered, and what additional examination or testing may be needed.
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