From SOAPs to School Emails: How Vet Moms Are Using AI (and How They’re Not!)

If you spend any amount of time online right now, it probably feels like artificial intelligence is everywhere.

Every conference has an AI lecture. Every software company suddenly has an AI feature. Every LinkedIn post is either promising that AI will change the world or warning that it will ruin it.

And honestly, I understand why veterinary professionals feel skeptical.

Veterinary medicine already asks us to move fast, process massive amounts of information, communicate clearly, lead teams, document thoroughly, and somehow still be emotionally available to clients and patients all day long. The last thing most vet moms want is another complicated thing to learn.

But the reality is this: AI is already quietly becoming part of daily life, both inside and outside the clinic. And I think one of the biggest mistakes we can make is assuming you have to become a “tech person” to benefit from it.

You just need to understand the basics well enough to decide where these tools genuinely reduce friction and where they create more.

Because not all AI tools are helpful; some absolutely make your life harder.

And veterinarian oversight still matters. A lot.

First, let’s simplify the terminology

The AI world loves jargon, so let’s make this less intimidating.

Artificial Intelligence (AI)

Artificial intelligence is the broad umbrella term. It basically refers to computer systems performing tasks that normally require human intelligence.

That can include recognizing speech, summarizing information, generating text, identifying patterns, or helping make predictions.

Not all AI is futuristic robots. Honestly, most of it is just software trying to automate or simplify repetitive cognitive tasks.

Machine Learning

Machine learning is a subset of AI where systems learn patterns from large amounts of data.

Instead of having someone manually program every single rule, the system improves by learning from examples over time.

Think pattern recognition, not actual “thinking”. If it looks like a duck, walks like a duck, and quacks like a duck, AI is going to call it a duck because that is the pattern it recognizes. 

But Siri, Alexa, Google, and Meta did not go to veterinary school. AI systems are trained to predict likely answers based on data and patterns, not to independently reason through a complex medical case the way a veterinarian does or why one ‘duck’ might actually be a swan in disguise.

That is why these tools can support us, but they should never replace clinical judgment. 

Large Language Models (LLMs)

LLMs are what tools like OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini are built on.

These models are trained on enormous amounts of text and are designed to predict and generate language that sounds human. They do not “know” things the way a person does. They generate responses based on patterns learned during training and the context they are given.

That means they can:

• draft emails
• summarize meetings
• rewrite complicated information
• organize thoughts
• create outlines
• brainstorm ideas
• help structure communication

What they are not:

• a veterinarian
• a replacement for medical judgment
• always accurate
• a guaranteed source of truth

They can absolutely sound confident, engaging, and even sympathetic - all while being very incorrect.

That is why veterinarian oversight matters so much.

AI inside the veterinary clinic

AI-supported tools are fast-growing areas in veterinary technology right now - particularly in documentation, diagnostics, imaging, and workflow support.  

Some of these tools are genuinely exciting. Some are overhyped. Some create more work than they solve.

The key is learning how to evaluate them critically.

AI Transcription and Documentation Tools

This is probably the biggest area veterinary teams are exploring right now.

Examples include:

• Shepherd Veterinary Software’s TranscribeAI
• ScribbleVet
• Scribe Veterinary Software
• CoVet

The goal is simple: reduce documentation burden and help veterinarians spend less time typing charts at night.

But here is my biggest advice: Do not just ask whether it “works.”

Ask whether it actually creates less friction.

Because if you spend just as much time copying, pasting, fixing formatting, correcting medical inaccuracies, or rewriting awkward wording, then the software may actually be adding work instead of removing it.

The best systems are medically intelligent enough to:

• structure information cleanly
• understand veterinary terminology
• summarize appropriately
• create readable medical documentation
• reduce editing time

If the output reads like a raw transcript of every spoken word, you may not actually be saving time overall.

And no matter how good the software becomes, the veterinarian still has to review the final medical record.

Always.

AI Clinical Assistant Tools

There is also a growing category of veterinary-specific AI assistants.

Examples include:

• OpenVet
• Sofie Veterinary AI
• PRIM Veterinary AI
• Shepherd’s DiagnoseAI

These tools are designed to help veterinarians access medical information more efficiently.

Many pull from reputable veterinary references such as:

• Plumb’s Veterinary Drugs
• American Veterinary Medical Association publications (JAVMA)
• Fossum’s Small Animal Surgery
• Other peer-reviewed veterinary literature

That is an important distinction.

General public AI systems may not prioritize veterinary-specific evidence or current standards of care. Worse, general-purpose AI may surface inaccurate advice drawn from non-veterinary or poorly validated sources. (Think about your crazy aunt’s conspiracy theory blog that includes why her cat should eat vegetarian only…) 

Veterinary-focused systems are often designed around more medically relevant source material. That said, trust but verify. AI can support clinical thinking. It should not replace it.

I think of these tools as assistants, not decision-makers.

AI and Radiograph Interpretation

Radiology is another rapidly growing area of veterinary AI.

Tools like Antech Imaging Services’ RapidRead, Radimal, and other AI-supported imaging platforms are being used to help identify potential abnormalities on radiographs more quickly.

These systems can sometimes help:

• Prioritize urgent cases
• flag possible findings
• improve workflow efficiency
• provide another layer of review
• support hospitals that may not have immediate access to boarded radiologists

And, truth be told, there are situations where having another set of “eyes” can be incredibly helpful during a busy day.

But this is also an area where limitations matter tremendously.

AI radiology interpretation tools are not perfect at all. In fact, a recent study published in JAVMA came to this conclusion: 

“Diagnostic performance varied between the 6 AI platforms tested and was overall low to moderate for this small sample. Even the best-performing algorithm had notable limitations, and none appeared suitable for clinical use in their current form.”

Positioning quality, unusual presentations, species differences, artifacts, and subtle findings can all affect accuracy. They should support clinical interpretation, not replace it.

The TL:DR: 

A normal AI read does not override your clinical concern. An abnormal AI suggestion still requires veterinarian interpretation, context, and confirmation.

Just because software flags something does not automatically make it clinically meaningful.

General LLMs for veterinary leadership and communication

This is where I personally use AI the most.

Not for medicine; for communication and operational friction.

I use tools like ChatGPT, Claude, and Gemini constantly for things like:

• drafting difficult client communication
• translating medical language into client-friendly explanations
• creating SOPs and onboarding documents
• summarizing long meetings
• organizing ideas for presentations
• helping structure leadership conversations
• brainstorming workflows
• outlining educational content

Sometimes the hardest part of leadership is simply figuring out how to start the conversation.

AI can help reduce that blank-page or writer’s block feeling.

And for overwhelmed vet moms juggling medicine, leadership, parenting, schedules, and life logistics simultaneously, reducing mental load matters.

AI at home: Small ways vet moms are already using it

This is the part people do not talk about enough: AI is not only a tool for work. Sometimes, it is just a practical life assistant. 

Here are some ways AI can be helpful in our lives outside of the clinic or hospital:

Vacation Planning

Instead of opening 37 browser tabs, you can ask an LLM to:

• build a family-friendly itinerary
• compare destinations
• organize travel schedules
• suggest restaurants
• create packing lists
• estimate driving times
• help stay within a budget

Calendar and Schedule Planning

In my recent spring calendar article, I discussed how many of us become overscheduled before we even realize it.

AI can actually help identify patterns in your schedule and help prioritize:

• where your time is going
• what could be delegated
• where bottlenecks exist
• which tasks are repeatedly draining energy

Sometimes having an outside framework helps you see your week more clearly.

Communication Help

Need to draft:

• a difficult email?
• a school response?
• a committee update?
• a volunteer communication?
• a birthday itinerary?
• a professional bio?

AI can help organize your thoughts quickly. This doesn’t mean you’re incapable of writing it yourself. Sometimes your brain is simply tired and struggles switching from “Dr. speak” to “Mom speak.”

Everyday Voice AI

Even small tools matter.

With things like Meta Smart Glasses, Siri, or other voice assistants, you can offload tiny mental tasks throughout the day.

Things like:

• “Remind me to call the orthodontist when I get home.”
• “Add milk to my grocery list.”
• “What’s a good creamed spinach recipe?”
• “What time does soccer start Saturday?”
• “Draft a text reminding the team about tomorrow’s meeting.”

Tiny reductions in cognitive load add up.

Especially for vet moms carrying both clinic responsibilities and household management simultaneously.

The ethical concerns are real

I also want to acknowledge something important: Some people are deeply uncomfortable with AI. And some of those concerns are valid.

Real conversations are happening around:

• data privacy
• documentation accuracy
• overreliance on automation
• bias in training data
• environmental impact
• intellectual property
• erosion of critical thinking

Those discussions matter.

And in veterinary medicine specifically, we have to be especially careful anytime technology intersects with patient care and medical records.

My recommendation is not blind adoption. It is a thoughtful adoption.

Use AI where it genuinely reduces friction, improves communication, supports workflow efficiency, or helps reclaim time. But keep humans firmly in the decision-making role, especially veterinarians.

Because no algorithm can replace clinical judgment, emotional intelligence, ethical reasoning, or the relationship between veterinary teams and the families we care for.

At least not the parts that matter most.

I do not think most vet moms are looking for robots to take over our lives anyway. Although if AI wants to take over meal planning, dishes, litter boxes, and scheduling orthodontist appointments, I think many of us would at least hear it out.