AI tech trends in 2026

Editor’s note: The authors are affiliated with Instinct Science and ScribbleVet.

Artificial intelligence (AI) is moving fast, with new capabilities landing seemingly every month. For veterinary practices, this technology is full of opportunity: tools that can lighten the day-to-day load, enhance and smooth the client experience, and give teams more time to spend with family.

Here are 3 ways we see AI benefiting veterinary medicine over the next few months, and what we'd have our eye on if we were running your practice tomorrow morning.

Anyone can become a developer

We know how intimidating this sounds, but the tools now exist for people who have never written a line of code to build working software just by describing what they want in plain language. The results are useful and they’re only getting better by the month. Someone you know is probably building an app right now to solve a niche problem you’ve never encountered.

In the software world, this shift has been dramatic. Coding agents (AI that writes and runs code on your behalf instead of just answering a question) went from novelty to daily habit for most engineers in roughly a year. Veterinary medicine is a step behind, but the gap is closing faster than most people in our industry realize.

That documentation headache you've complained about for years, the report your veterinary practice information management system (PIMS) has never quite given you, the workflow that's too specific to how your clinic runs for any vendor to build…You are far closer to fixing those issues yourself than you think, without having to hire an engineer. You can use AI platforms like Claude or ChatGPT to write the appropriate code to solve that problem.

This is not a hypothetical. We already do this. You probably could too.

There's one prerequisite for building your own workflow: open application programming interfaces (APIs). Open APIs are structured endpoints allowing third-party tools (like ScribbleVet) to read and write patient data, appointments, and records without manual export/import. If your software won't let other tools connect to your data, you can't build anything on top of it.

It’s worth asking every vendor you work with if their software supports open APIs. If they become guarded or vague when you ask, that should tell you something.

AI agents are going to do the prep work

There's a difference between a tool that does a task when you ask and an assistant that knows your preferences, understands your workflows, and gets ahead of you without being told. The benefit of an AI agent over a simple AI-powered tool is that the agent has agency. It can anticipate. It pulls from multiple places, connects the dots, and hands you the result before you've had the chance to even ask. Imagine that each patient's relevant history is neatly summarized before you walk into the room, your schedule is organized, and all your callbacks are categorized and flagged. Now, imagine you also had an extra pair of hands, because the administrative tasks being handled leave your technicians free to focus on their patients.

We don't have veterinary-specific agents running the whole pre-appointment workflow on their own…yet. The underlying technology exists, though, and the veterinary versions are on the way. Still, examples of powerful AI tooling already exist: Document Summary in Instinct EMR, for instance, turns the records on a patient's chart into a structured summary, with every finding linked back to its source. ScribbleVet’s Dialer lets you make calls from inside the app, meaning that as soon as you hang up, your conversation is documented and your patient’s treatment plan is updated.

The practices that get comfortable with this now, even just by using today's tools and learning how they actually behave, are going to have a dramatically easier time when the next ones land. Familiarity compounds. We recommend that veterinary teams start experimenting now.

Where your clinical content comes from is about to matter much more

This one is personal for both of us. It worries us that many veterinary professionals are already using general-purpose AI to answer clinical questions. It is vitally important to know where the public AI models derive their information before you trust them with your patients’ safety. An answer to a drug dosage question stitched together from an unknown mix of websites, Reddit posts by non-veterinarians, and outdated handouts is fundamentally different from an answer drawn from a peer-reviewed source written, reviewed, and maintained by veterinary professionals. The two should not be treated as interchangeable.

We're watching exactly this play out in human medicine right now. Physicians are moving toward AI grounded in verified clinical literature rather than open web search because they learned the hard way that easily accessible is not the same as accurate.

For example, clinical decision support tools within Instinct software and ScribbleVet draw upon trusted content in Plumb’s and Standards of Care rather than hallucination-prone tools. So here's the test we'd apply to any AI tool you're weighing for clinical use: Where does the information come from (like peer-reviewed articles, trusted reference materials, and veterinary-specific studies)? How easily can you verify it? If you can't easily answer the first question, the second one probably doesn’t matter.

Where to start

If you're a practice leader trying to figure out where AI fits in your practice today, pick one problem to solve and focus on that, even if it takes a little longer to set up at first. That is where AI is best, at least for now. Focus on one problem at a time, build confidence in the tools, and understand how they work. Let that confidence open the door to everything that comes next.

The surprising thing we’ve noticed is that the practices that get the most out of AI usually aren’t the most tech-forward. The practices that are really crushing it right now are the ones that picked a single real problem, solved it, and kept going.

Pick your problem. We're excited to see what you build.

Caleb Frankel, VMD, is founder and CEO of Instinct Science. An internship-trained emergency veterinarian, he also serves as a board member, advisor, and author and speaker on the intersection of technology and veterinary medicine. Instinct’s mission is to improve the experience of modern veterinary teams through better technology. The company develops practice management software, an AI scribing platform, clinical decision support tools, and educational resource.

Rohan Relan is founder and CEO of ScribbleVet, an AI scribe tool used by veterinarians and recently acquired by Instinct Science. He is a seasoned entrepreneur with an engineering background from UC Berkeley, driven by a passion for cutting-edge technology.