AI in Veterinary Medicine: 18 Categories of Veterinary AI Tools
- Sep 3
- 7 min read
Introduction
If you’re here, you’ve likely heard about artificial intelligence tools in vet practice - but what does that actually mean for frontline veterinary teams?
Learning about AI in veterinary medicine can feel overwhelming. However, as I have built my Vet AI Tool Database & Search Engine, I’ve realized this growing list of hundreds of products can be classified into several main categories, which is a lot easier to wrap your brain around!
This guide explains the primary categories of AI in veterinary medicine that you can currently find in vet clinics, research, production medicine, and perhaps in your own home. Some categories may be broken down into additional subcategories to help you further understand the tool. Each category matches the filters in the Vet AI Tool Search Engine and is listed here in the same alphabetical order.
How did I select these categories?
These categories evolved as I built the Vet AI Tool Database; but more importantly, they reflect underlying AI model types. For example, AI scribes rely on large language models (LLMs), while wearables combine sensor data with computer vision or pattern-recognition AI. These are fundamentally different models.
That distinction is blurring, though. Many platforms now integrate multiple AI types. AI scribes, for instance, are beginning to incorporate extraction models for analyzing medical records, sometimes combining both text-based and visual AI. This growing overlap makes it even more important to understand the categories clearly.
Main Categories of AI in Vet Med
⬇️ Jump to a section:
2. ChatBots
6. Imaging
10. Medical Records
11. Motion Analysis
16. Research
18. Wearables
1. Breeding & Genetics
What is it?
AI tools here analyze reproductive and genetic data to boost breeding success and reduce inherited disease risk.
Subcategories:
Birthing Sensors
Breeding Timeline Management
Embryo, Sperm, Egg, Chick Sorting
Genetic Analysis to Guide Breeding
Common Features:
Fertility/heat detection
Embryo/sperm/egg sorting
Breeding timeline apps
Genomic risk tools
2. ChatBots
What is it?
Conversational AI models designed for client engagement, education, triage, and handling routine queries.
Subcategories:
Client Education
Decision Trees (NLU)
Common Features:
Voice/call bots for booking and refills
After-hours triage Q&A
Appointment and chat routing
3. Client Communication & Automation
What is it?
AI-driven messaging platforms that streamline outreach, follow-ups, and client interactions.
Subcategories:
AI Reception & Scheduling
Common Features:
AI reception services
SMS/email reminders
Multilingual messaging
Telemedicine integrations
Survey summaries
4. Decision Support
What is it?
AI engines that interpret clinical data and suggest next steps for diagnosis, triage, or treatment planning.
Subcategories:
Clinical Reasoning & Summary Generation
Diagnosis & Treatment Assistance (Integrated)
Diagnosis Generation
Diagnostic Test Interpretation
Photo/Image Analysis
Triage & Urgency Assessment
Common Features:
Triage scoring
Drug-interaction checks
Diagnostic photo recognition
Treatment planning tools
5. Developer & Integration Tools
What is it?
APIs and SDKs that allow vendors and clinics to embed AI capabilities into their existing platforms.
Subcategories:
(None Currently)
Common Features:
Data pipelines
Model hosting
Practice management system (PIMS) plug-ins
Interoperability bridges
6. Imaging
What is it?
AI systems that read, annotate, and analyze diagnostic imaging across multiple modalities.
Subcategories:
Infrared (Inflammation)
MRI
Multiple Features
Radiography
Ultrasound
Common Features:
Auto-detection in radiographs
Ultrasound guidance
MRI/CT interpretation helpers
Lesion measurement
7. Laboratory & Pathology
What is it?
Computer vision tools that assist in lab diagnostics by interpreting slides, strips, and microscopic data.
Subcategories:
Microscope (Multiuse)
Urinalysis
Common Features:
Cytology slide analysis
Urinalysis image scoring
Parasite detection
Disease trend prediction
8. Livestock & Farm Management
What is it?
Large-scale AI systems designed for animal welfare, productivity, and efficiency in production medicine.
Subcategories:
Audio Sensors
Imaging
Motion Sensors
Multiple Features
Nutrition Optimization
Smart Feeders
Visual Trackers
Wearables
Common Features:
Cough detection sensors
Lameness detection
Smart feeders
Nutrition optimization
Wearable monitoring
9. Medical Equipment
What is it?
Hardware devices embedded with AI that interpret physiological signals directly at the point of care.
Does not include wearables, which are categorized separately.
Subcategories:
Stethoscopes & Attachments
Common Features:
Digital stethoscopes
Ultrasound probes with AI
ECG capture and analysis
10. Medical Records
What is it?
AI-enhanced EMR tools that reduce documentation time, improve data quality, and support compliance.
Subcategories:
AI Information Access & Admin Automation
AI Scribe
Discharge Generation
History Summary
Multimodal Medical Documentation
Platforms with AI Features
Common Features:
AI Dictation
Ambient AI
History and discharge summaries
Safety/compliance checks
Trend boards
11. Motion Analysis
What is it?
AI-assisted gait and movement analysis systems that detect lameness and track rehab progress.
Subcategories:
Lameness
Common Features:
Equine inertial sensors
Treadmill analysis
Video-based rehab monitoring
12. Nutrition & Feeding
What is it?
AI-driven platforms for tracking food intake, monitoring adherence, and optimizing feeding plans.
Subcategories:
(None Currently)
Common Features:
Smart feeders
Weight and activity trend tracking
Livestock feed optimization
13. Patient Monitoring
What is it?
Remote or contactless systems that track vital signs, anesthesia depth, and recovery progress.
Does not include wearables, which are categorized separately.
Subcategories:
Anesthesia Monitoring
Litter Box Sensors
Remote Anesthesia Recovery
Vitals Monitoring
Common Features:
Smart litter box sensors
ICU dashboards
Anesthesia depth prediction
Recovery trackers
14. Practice Management
What is it?
AI tools that enhance business intelligence, operations, and staff efficiency.
Subcategories:
Training and Education
Common Features:
AI scheduling
Financial dashboards
Inventory prediction
Workforce planning
15. Precision Medicine
What is it?
AI applications that personalize treatment through genomics, biomarkers, and predictive risk scoring.
Subcategories:
Oncology
Other Predictive Tools
Common Features:
Liquid biopsy monitoring
Pharmacogenomic matching
16. Research
What is it?
Advanced AI systems for experimental research, drug discovery, and cross-species data mining.
Subcategories:
Cross-Species Drug Discovery
Smart Enclosures
Common Features:
"Omics" data synthesis
Literature mining
Trial optimization
Knowledge graph building
17. Treatment & Patient Care
What is it?
AI tools that assess pain, support therapy planning, and guide rehabilitation.
Subcategories:
(None Currently)
Common Features:
Vision-based pain scoring
Remote rehab tracking
AI-guided therapy prompts
18. Wearables
What is it?
Animal-mounted sensors that continuously track health, activity, and risk behaviors.
Subcategories:
Cardiac Monitors
Movement Assessment
Smart Collars/Halters
Other
Common Features:
Smart collars and halters
Cardiac monitoring
Abnormal behavior alerts
Herd-scale integrations
Veterinary AI: From Trend to Standard Practice
Broader Trends
AI is no longer a niche research interest - it is fully integrated into the front lines of veterinary medicine. There are many well-validated AI models available that are revolutionizing our field through increased efficiency, improved outcomes and access to care, and improved business functions.
It’s not a matter of “if” but “when”
Even for AI-adverse practitioners, AI is here to stay. In fact, in human medicine, the prevailing belief is that hospitals that wait to adopt AI will never be able to catch up with their competitors: the demand for AI-enabled improvements in efficiency, health outcomes, and workforce lifestyles is foreseen to work against those who wait.
In human medicine, the prevailing belief is that hospitals that wait to adopt AI will never be able to catch up with their competitors.
Similarly, vet practices that wait until AI is “perfect” risk falling behind on client service expectations, staff efficiency, and competitive positioning. Early adopters aren’t just gaining tools: they’re gaining profits, time, staff retention, and client goodwill.
Client Expectations
Clients expect a lot from us, and AI is soon going to become non-negotiable as more vet clinics overtly use AI technology in their patients’ healthcare.
In human medicine, studies are beginning to emerge, and people don’t dislike it. While it depends significantly on the field of medicine, multiple studies have shown that over half of respondents feel AI will improve healthcare, while only single-digit percentages felt otherwise.
Importantly, patients perceive improved access to healthcare as a benefit, which is notable since the veterinary field often deals with significant financial restrictions due to a lack of insurance.
As owners experience AI in their own healthcare, they will become increasingly used to it as a natural part of medical care. For instance, when I first began using AI scribes, several owners noted that their physicians were now doing the same. I found this to be an interesting response that positions us at the front lines of innovation in the eyes of these owners. Notably, I never had a single owner decline to be recorded by the AI scribe, which was unexpected.
Due to AI’s cost efficiency, we are in a unique time frame where we can keep up with similar advances in human healthcare, and clients are taking note.
Look at the Bigger Picture
While I love AI, I love strategy more. I passionately believe you shouldn’t be using AI just to say you are using AI. It should be an integral part of your overall strategy.
Believe it or not, AI isn’t the answer to everything! There are some things that it just is not good at, where traditional tools are better (ex: Excel Spreadsheets for data analysis).
You should be determining where AI will actually help you before you jump on board.
Believe it or not, AI isn’t the answer to everything! There are some things that it just is not good at, where traditional tools are better
Where are your pain points, and where do (good) AI tools exist that might solve those? I am a believer in mapping out your workflows as a way to better identify your most important bottlenecks, and I also believe this is a wonderful method to determine where an AI tool can and cannot serve you.
More reading on business strategy & continuous improvement:
Learn about AI in Veterinary Medicine
You don’t have to be an AI expert to know what tools you need and how to evaluate them, but you do need to know where to find the information you need. I also am a big believer in reading the fine print, as a lot of the clues live in those contracts you’re signing, like data usage, privacy measures, and storage timelines. (Just a warning - you should be able to opt out of your data being used for training.)
Understanding these categories above is a huge step in the right direction, but if I had to recommend one other article right now, it would be this one to help you understand how to evaluate tools.
If you want to learn more about how to evaluate AI safety & efficacy, though, here are some more blogs:
Now what?
Identify your clinic’s pain points (and consider process mapping).
Match them to the relevant AI category above.
Search for that category in my Vet AI Tool Search Engine.
Compare tools by pertinent features, certifications, and regulatory compliance.
Then contact vendors and ask for a trial!
Final Thoughts
Veterinary AI can feel overwhelming at first, but creating an organized understanding of the available options will go a long way toward your overall goals. Once you identify a category of interest, I encourage you to learn more about it to understand how to compare the tools effectively.
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