The Healthcare AI Playbook: What it actually takes to build trustworthy AI for care

Hosted by Amanda Ducach, CEO, and Morgan Rose, chief science officer, EmaEQ

Healthcare companies have spent the last two years hearing the same advice: get AI into your product. Few have been told what that actually takes.

Most default to the fastest option. Plug in a general-purpose model, wrap it in a chat window, and call the box checked. It looks like progress on a roadmap slide. It rarely holds up once a real patient is on the other end of it.

We’ve spent years building AI specifically for healthcare, and the lesson that keeps repeating itself is simple: accuracy is not the same thing as trust, and trust isn’t something you bolt on after launch. It has to be part of how the system is built from the first line of code, not a feature added once regulators or users start asking questions.

That distinction is the whole reason clinical accuracy gets treated as a checkbox instead of a discipline. A model can sound confident and still be wrong in ways that matter enormously in a health context.

Knowing the difference, and building for it deliberately, is what separates AI that’s genuinely safe for care from AI that’s simply fast to ship.

On July 20th, we’re hosting a live conversation about exactly this: what companies should be paying attention to before they choose an AI to build with, what clinical accuracy really requires, and the pillars we hold every AI system to before it gets anywhere near a patient’s care.

The Healthcare AI Playbook Webinar: July 20th, 1:30-2pm EST, live on LinkedIn.

Register here: https://www.linkedin.com/events/7482643171823509504?viewAsMember=true

If your team is building anywhere near healthcare, or evaluating what’s already in your product, this is the conversation we think the industry needs right now.