The practice of veterinary medicine in the United States is seeing changes with the use of new artificial intelligence (AI) technologies, especially in diagnostic imaging. Veterinary clinics and hospitals are treating more animals, so they need faster and more accurate diagnoses. AI gives tools that help veterinary workers by improving how images are read, making workflows easier, and helping animals get better care. For clinic owners, managers, and IT staff, knowing how AI affects veterinary imaging is important to choosing the right tools that meet both medical and operational needs.
Diagnostic imaging is very important in veterinary medicine. It helps check health problems in pets like dogs and cats. Usually, reading X-rays, ultrasounds, and CT scans takes a lot of skill and time from special veterinary doctors called radiologists. There are not enough radiologists, which can cause delays in diagnosis and treatment. AI is helping by giving veterinary teams fast and accurate image analysis.
One example is Vetology, a company based in San Diego, California, that offers AI-powered Virtual Radiologist Reports in the U.S. and other countries. Vetology’s AI provides imaging reports with about 90% accuracy within minutes. This helps veterinarians get quick support. The system works with dogs and cats and has tools for abdominal conditions like enlarged liver and blocked intestines. In 2025, Vetology added 14 new classifiers for dog abdomen diagnoses, showing how AI is improving veterinary image reading.
Veterinarians at places like UC Davis have also helped improve diagnostic imaging by making AI models that find diseases accurately. They created AI that detects Addison’s disease in dogs with over 99% accuracy using blood work from more than 1,000 dogs. This AI checks chemical markers that were once hard to understand. Another AI model finds leptospirosis with 100% accuracy after testing over 400 dog blood samples. These AI tools help find diseases early, which is very important for treatment.
AI imaging helps give vets more confidence by acting like a second opinion, using expert veterinary knowledge. SignalPET is a company that uses AI and deep machine learning to detect diseases early through tools like SignalSTAT and SignalRAY. These AI systems help vets find small problems that might be missed when cases are busy or complicated. This extra help reduces mistakes, especially in emergencies where careful decisions are needed.
Technologies like Magnetic Resonance Imaging (MRI), 3D imaging, fluoroscopy, and positron emission tomography (PET) are used more and more in big veterinary hospitals and universities in the U.S. UC Davis Veterinary Medicine, a leading center, uses a special PET scanner made for horses. This scanner only needs light sedation and helps check injuries in racehorses. It is better at finding injuries and predicting recoveries than older bone scans.
Also, 3D imaging with CT scan data lets orthopedic surgeons make custom 3D-printed titanium implants for dog hip replacements. This method fits implants better and helps them last longer while lowering surgery problems. These advances depend on detailed images from high-tech machines, and AI helps analyze complex body parts quickly.
Another area is interventional radiology, which uses real-time imaging like fluoroscopy to guide small surgeries. This includes blocking tumors and giving targeted chemotherapy for cancer. These less invasive treatments help animals recover faster. UC Davis uses these imaging-guided treatments to improve results and lower risks compared to old surgery methods.
AI is not only used in clinics but also helps teach veterinary students. Vetology works with Massasoit Community College in Massachusetts to give veterinary tech students access to their AI imaging software. This lets students get practical experience with AI while learning how to take and read X-rays.
Students say the quick feedback from AI helps them know what makes a good X-ray and boosts their confidence before they start clinical work. This teaching helps new vet techs and doctors learn to use AI tools in their jobs, which is good for animal care and work efficiency.
AI helps not just with diagnoses but also by making workflows easier in veterinary offices. Doing routine tasks automatically saves staff time and makes operations more efficient.
Chatbots and virtual assistants powered by AI help manage client communication. They can schedule appointments, answer common pet care questions, and give updates after surgery. This let the staff spend more time on patient care and less on office work.
AI also helps with record keeping by using voice-to-text during visits. Systems like Scribenote and HappyDoc let vets and techs speak notes, which AI turns into detailed reports quickly. This cuts down paperwork, lowers errors, and speeds up billing and follow-ups.
In veterinary cancer care, AI platforms like FidoCure study genetic data to customize treatments based on the tumor’s genes. AI can quickly process lots of information to help doctors decide the best therapy. ImpriMed’s AI uses live cancer cells to predict the best drugs, making treatment more personal and possibly saving more lives.
Wearable devices like PetPace’s smart collar track animals’ health in real time. These collars collect data like vital signs and behavior patterns. They alert veterinary staff to early signs of sickness or pain. This helps staff act faster and lowers the manual work of checking animal health all the time.
Using AI in imaging and workflow is becoming a key part of better veterinary care. For clinic managers and owners, getting AI diagnostic reports quickly helps the clinic treat animals sooner and see more patients. Shorter waiting times make pet owners happier and improve animal health.
AI tools also help lower costs by speeding up diagnosis, cutting repeat scans, and supporting focused treatments. This can make veterinary businesses earn more and use resources better. AI supports human expertise rather than replacing it. Vetology’s CEO, Dr. Seth Wallack, points out that AI helps vets feel more sure of their decisions without taking over clinical judgment.
Veterinary workers feel less stress and doubt when using AI. Accurate AI systems, reviewed by certified radiologists and vets, give them confidence and help teaching. This leads to more accurate diagnoses, fewer legal issues, and better reputations for clinics.
Partnerships like the one between Vetology and VetIT to expand AI in the UK and Europe show how similar efforts can grow in the U.S. These collaborations help vet teams get support, training, and smooth AI use in their clinics.
As AI systems improve, more detailed and species-specific tools will come. These will cover more areas like brain disorders, heart disease, and infections. Combining AI with new tech like 3D printing, robotic surgery, and telehealth will make vet diagnostics and care better.
More AI use is expected to help clinics improve based on user feedback and medical tests, making sure AI stays useful and correct. Clinic managers and IT staff should watch these changes to plan for AI growth that fits their clinics.
Using AI in imaging and workflows helps U.S. veterinary clinics handle more patients better, give higher quality care, and meet the needs of tech-aware clients. These clinical and business benefits make AI an important tool for the future of veterinary medicine.
Scribenote is an AI-powered clinical documentation system that processes veterinary conversations in real-time to generate comprehensive medical records, improving documentation accuracy while reducing administrative burdens.
Vetology uses advanced AI diagnostic systems to rapidly analyze veterinary imaging data, providing detailed clinical reports within minutes while ensuring high accuracy through human-AI collaboration.
Digitail is an integrated AI practice management ecosystem that automates workflows, from medical records to client communication, allowing seamless operation and real-time data synchronization across all modules.
GoldieVet transforms audio recordings into detailed medical records using AI-powered transcription, enabling veterinary teams to accurately document various clinical scenarios while ensuring data security.
HappyDoc provides real-time transcription and customizable workflows that automatically convert clinical conversations into medical documentation, allowing vets to focus more on patient care and reducing burnout.
FidoCure analyzes complex genomic data to create personalized cancer treatments for dogs, utilizing next-generation sequencing and a vast database to improve therapeutic strategies.
ImpriMed uses AI to process live cancer cells to predict optimal treatment paths for pets, offering personalized medicine through rapid drug response testing and comprehensive diagnostics.
PetPace employs a smart collar to track real-time pet biometrics, detecting changes in wellness patterns through continuous monitoring of vital signs and behaviors to enable early intervention.
Petriage simplifies pet health assessments through an AI-driven engine that delivers rapid care guidance with 97% accuracy, connecting pet owners to licensed veterinary professionals.
ScribbleVet automatically processes clinical conversations into polished medical records using natural speech processing, ensuring accurate documentation while facilitating client communication with medical explanations.
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