Healthcare AI Trust Starts in the Room

By Jon Hilton, SVP of AI Value Creation

At Optura, we design In the Round around a specific belief: that trust in healthcare AI is built through shared experience, not shared presentations.

Every element of the day stems from that premise. You don’t start with a keynote. You start with a laptop in front of you and a real problem from your own organization, and you work. The platform doesn’t prompt you; it works alongside a leader like an analyst and shows you what other organizations needed when you weren’t looking. By the time anyone sits down to talk, the room has worked through a challenge together. That changes what people are willing to say and communication opens up, along with a growing trust.

On April 30th in Nashville, that design got put to the test at a level we hadn’t quite seen before.

Senior executives from across healthcare — payers, providers, health tech leaders — spent the afternoon with the Optura platform. No script. Just real problems from real organizations, entered into the system, clustered into patterns, built into agent blueprints. What surfaced: 56 use cases. $200 billion in identified value. Six themes that cut across every organizational type in the room in ways nobody had mapped before they sat down.

That’s what trust-building looks like when it actually works.

There’s a version of healthcare AI leadership that consists almost entirely of sitting in briefings and approving budgets. A lot of executives operate that way. 

What happened during the working session is something I’ve now seen consistently across Optura, and it hasn’t stopped being striking: executives who actually build, who sit with the platform, enter their own problems, watch the output respond to their specific organization, come out of that working session approaching AI differently. The shift isn’t gradual. It’s visible.

The executives who engage most deeply with AI, who move it from strategy to operating model, are the ones who’ve personally interacted with it. Not because they need to become AI engineers, but because you cannot lead a transformation you’ve never experienced firsthand. Leaders lead by example. The afternoon was designed to create that experience in a compressed form. The fishbone diagram generates three more ideas for every one you enter. The blueprints come back with ROAI™ attached. By the time the working session ends, the question becomes: how do we move forward with AI.

That’s the shift we’re trying to create. Not in a deck. In practice.

The conversation that followed ran under Chatham House rules, so I’ll speak to the themes rather than the specifics. But the honesty of it was unusual, and I think it was unusual precisely because payer and provider leaders don’t often end up in the same room after doing real work together. The adversarial default that usually governs payer-provider interactions had softened, because the afternoon had already surfaced something neither side expected: their AI problems are largely the same problems.

Prior authorization came up, as it almost always does in this industry. Both sides named it the same way: a process where over 90% of cases are ultimately approved, and both sides have spent the past three years building increasingly sophisticated AI to fight each other over it. Bots calling bots. Tokens spent in conflict. The cost of healthcare administration keeps going up even as the underlying dispute rate stays the same.

The healthcare system is projected to reach $5.9 trillion this year. A quarter of that is administrative cost that delivers nothing to patients or members. That’s the opportunity. Not for one side or the other, but for the system. The infrastructure to get there isn’t primarily technical. It’s relational. It requires payers and providers to decide that the trillion and a half dollars sitting in the middle of them is a shared problem worth solving together, not an AI battlefield worth winning.

What I found remarkable is that by the end of the evening, executives were talking about APIs. Actual architecture. Not strategy. Implementation. That conversation didn’t happen because someone said the right things at a panel. It happened because the day had already created the conditions for it.

Getting in the room isn’t a soft idea. It’s the mechanism.

The panel conversation and the afternoon session were pointing at the same thing from two different angles. The working session proved it empirically: executives who touched the platform changed. The fireside chat named why it generalizes: people adopt AI when they trust that it was built for them, not deployed at them.

The phrase that stayed with me from the evening, said directly enough that I wrote it down: change done to people and change done with people produce categorically different outcomes. The first creates resistance. The second creates ownership. Most healthcare AI programs fail at this exact line, not because the technology doesn’t work, but because the rollout treated the front line as a target audience rather than a design partner.

The organizations getting real outcomes have figured this out. ICU-level monitoring in a medical-surgical environment, with measured mortality reductions. Ambient listening — experimental 18 months ago, now near-standard at health systems serious about keeping their clinicians. These outcomes are real. They’re also not surprising. They came from organizations that built with their front line, not at them.

And the ones that are measuring it, actually tracking ROAI™, defining what success looks like before deployment starts, failing fast on the use cases that don’t perform, are the ones that can stand up in front of their boards and answer the question everyone eventually gets asked: Is this working?

The answer can’t be a story. It has to be a number.

I want to say something directly about why the Optura team runs In the Round the way we do, because it’s not obvious from the outside.

Most healthcare AI events are structured for the speaker. Work the stage, deliver insights, take questions, go home. We built In the Round for the opposite: structured for the room. Every element, the working session, the platform work, the dinner, the fireside chat, is designed to create the conditions where trust can actually form. Between executives and the technology. Between organizations that are usually on opposite sides of a claim. Between leaders and the reality of what their own organizations need.

What happened on April 30th isn’t a case study we’re going to write up and put in a deck. It’s the ongoing proof of concept for what we believe at Optura: that the companies leading healthcare AI over the next five years won’t be the ones with the most technology. They’ll be the ones with the most trusted technology, built in collaboration, proved in practice, measured from day one.

You don’t get there through better keynotes. You get there by doing the work in the same room, with the same data, and letting what’s true surface on its own.

That’s what April 30th was. And we’re just getting started.

Request a demo to learn more about In the Round and what Optura’s platform surfaces when your executive team does the work together.