AI Resilience Report forVeterinary Assistants and Laboratory Animal Caretakers

If you're worried about AI taking over jobs caring for animals, here's some good news: in this field, AI is mostly being used to help people, not replace them. The hands-on parts of the job — feeding, bathing, restraining, comforting a scared puppy — still require human hands and human judgment. What AI is doing is taking over the boring paperwork. "AI scribes" listen during exams and write up medical notes automatically, so staff can spend more time with animals.

The University of California-Davis School of Veterinary Medicine recently adopted ScribbleVet, an AI-driven digital scribe designed to complete veterinary SOAP notes during a patient exam by recording the appointment and streamlining medical record-keeping. A 2024 AVMA-published survey of nearly 4,000 veterinary professionals ^[1] found that the top benefits were "improving efficiencies, streamlining administrative tasks," not replacing clinical care. On the laboratory side, researchers at Rutgers published in the Journal of the American Association for Laboratory Animal Science ^[2] using machine learning to predict cage-change timing for mice, and a 2025 paper in Disease Models & Mechanisms ^[3] describes home cage monitoring systems with cameras and sensors that can monitor animals 24/7 in a non-intrusive way over extended time periods, detecting early or subtle indicators of disease, experimental outcomes, or welfare concerns that brief daily observations might miss.

Adoption is moving quickly for paperwork tools but slowly for hands-on care. On the "fast" side, there's a huge worker shortage — Virginia Tech reports that the shortage of credentialed veterinary technicians who keep practices running has reached critical levels, and the U.S. Bureau of Labor Statistics projects 9% job growth from 2024 to 2034, much faster than the average for all occupations ^[4]. Clinics are leaning on AI to handle scheduling, transcription, and reminders so their human teams can focus on animals.

On the "slow" side, trust is still a big barrier: the AVMA-published survey found that key concerns included the reliability and accuracy of AI in diagnosis and treatment, alongside data security worries. The trade publication Vet Times notes that many vets remain cautious about accuracy and worried about what AI means for their roles, framing the shift as empowering staff rather than replacing them ^[5]. The bottom line for a young person eyeing this career: empathy, careful hands, and observational skills with living animals are exactly the things AI is worst at — and those are the skills employers will keep paying for.