AI in veterinary care is advancing, but clinicians still carry the risk

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Artificial intelligence is moving deeper into healthcare and veterinary medicine, but the clearest message from recent reviews is that it’s still a support tool, not a substitute for clinical judgment. A recent narrative review in healthcare found AI performs well in narrow, controlled settings such as imaging, laboratory diagnostics, rehabilitation, and conversational support, while emphasizing unresolved concerns around generalizability, bias, ethics, and real-world validation. In companion animal medicine, a separate systematic review found AI applications expanding beyond diagnostics into behavior, welfare, and monitoring, but described the field as fragmented and not yet well integrated into routine practice. Meanwhile, veterinary workflow vendors are pushing broader operational use cases, from note-taking to client communication and scheduling, and regulators are beginning to spell out where responsibility still sits: with the veterinarian. (pmc.ncbi.nlm.nih.gov)

Why it matters: For veterinary professionals, the takeaway is practical. AI may help reduce documentation burden, speed image review, summarize records, and support triage or client communications, but it doesn’t remove the need to verify outputs, document reasoning, protect client data, and maintain the standard of care. The American Association of Veterinary State Boards said in its March 2025 white paper that practice acts regulate how tools are used, not the tools themselves, and that veterinarians remain responsible for diagnoses, record accuracy, informed consent in higher-risk uses, and avoiding unlicensed practice concerns when chatbots or autonomous systems drift into medical advice. (aavsb.org)

What to watch: Expect more pressure for validation standards, transparency around training data and limitations, and clearer state-level guidance as AI tools move from administrative support into clinical workflows. (aavsb.org)