AI in Allied Health: The Potential Is Still Underestimated

Adoption of AI in allied health is happening. The real question is how fast and how carefully, practices move. I've spent close to two decades building software for health clinics and I'd put AI in the same category as the internet and cloud computing arriving in this industry: a major shift in what practice management software can do, building on everything that came before it.

Where adoption is heading - Practices are moving through it in stages. The first use cases target the biggest admin burdens: transcription, note writing, the tasks that eat into evenings and weekends. The next wave is insight, tools that surface what's actually happening in a practice rather than just recording it. After that comes agentic AI, software that can take action on its own, manage workflows and handle more complex tasks with less hands-on guidance from a practitioner.

Earlier this year, we surveyed around 700 allied health practitioners worldwide for our State of AI in Allied Health report and the results back up how much room is still ahead here: among practitioners who use AI daily, 71 percent cut their documentation time by a quarter or more and that's with practices only scratching the surface of what's possible.

What this means for practitioners - What all of this adds up to is more headspace for the people doing the work. Less paperwork, more time with patients and over time, a healthier, more sustainable workforce in a profession stretched by regulation and rising expectations. The practices I talk to that made these changes early are seeing practitioners leave on time, stay mentally clear on the drive home and show up to sessions more present because they aren't tracking eight other things at once.

Building trust alongside speed - Healthcare calls for a particular pace with AI: fast and also deliberate, with security and compliance built in from the start. The real challenge right now is helping practices tell a properly secure, compliant platform from one that simply looks the part. Barriers to entry have dropped fast, which is great for innovation, but it also means practices need a clear way to evaluate who's actually built for healthcare. Speed and rigor, together, are what this space needs.

AI can't replace what they do. We agree completely. Clinical judgment and connection belong with the practitioner.

AI's role is to support human connection in a session: letting a practitioner stay present instead of taking notes, while the read on a patient's tone and body language stays entirely human. In the open-ended responses of our survey, practitioners said the same thing again and again in their own words: AI can't replace what they do. We agree completely. Clinical judgment and connection belong with the practitioner and we build with that in mind. What AI does well is help create a more present practitioner and a more present practitioner is simply a better one.

What's still ahead - The opportunity that gets underestimated most is how much friction can still come out of a practice's day. Bookings, payments, compliance, notes, all of it keeps getting smoother from here, to the point where a practitioner walking into their clinic five years from now will spend noticeably less time in front of a screen and noticeably more time with the people in front of them. Practices that build around that shift stand to become more profitable, more sustainable and more enjoyable to run, for the practitioner and for the patient walking through the door.

We're still at the start of this. A year from now, we'll likely be talking about features nobody's building yet as if they were obvious all along. The practices that do well will be the ones that adopt AI deliberately, hold onto the parts of the work that were never meant to be automated and use the rest to build something more sustainable than what came before.