August 5, 2026

You can’t rush trust: Reflecting on a decade of AI innovation in healthcare

By Laurent Rotival, chief information officer, Cambia Health Solutions

Healthcare has an AI trust problem.

Poll after poll shows patients are skeptical of AI making decisions about their care. Providers worry about automation replacing clinical judgment. Regulators are scrambling to build guardrails around technology that’s moving faster than policy can follow. And the public – already frustrated with a healthcare system that feels impersonal, expensive and hard to navigate – isn’t always thrilled at the prospect of algorithms getting more involved.

I don’t think the answer to this problem is better marketing or a slicker product demo. It’s a track record that proves the technology can actually deliver.

A decade of learning what works (and what doesn’t)

Cambia has invested seriously in AI and data science for more than 10 years. We’ve put in the work to build a strong foundation — tackling governance questions proactively, building an AI Ethics Committee, developing responsible AI principles and making human oversight a non-negotiable feature of how we operate.

Today, Cambia runs multiple predictive models every day to do things like identify health plan members who are at risk, anticipate care needs and connect people with preventive support before a health issue becomes a crisis.

Reclaiming time for what matters

But the real test of the foundation we’ve built isn’t in the number of models we run. It’s in how those tools show up in the day-to-day work of serving our members.

Take care management. Assembling outreach lists, coordinating care, connecting members with resources — this is some of the most critical work we do, and it used to take hours of manual effort across multiple systems.

We’ve redesigned that process with AI. Tasks that took hours now take minutes. Employees using our AI assistant are seeing 10 – 20% gains on research and analysis. Yes, that’s efficiency, but what’s more important is what that reclaimed time means for those we serve. Our care management teams have more capacity to focus on what truly matters: the human-to-human conversations that help a member navigate their care.

The question that drives us forward

That focus on human connection is what guides our work. We start every AI initiative by asking: Does this make life better for the people we serve?

That question sounds simple, but it’s not. It requires us to define what “better” means for a member navigating a confusing benefits system, for a provider buried in administrative work, for an employee trying to do their job well in a complex organization. It requires us to measure outcomes, not just outputs. And it requires us to be honest when the answer is no (or not yet).

It’s also the question that keeps responsible AI from becoming a talking point. When you’re genuinely focused on whether a tool makes life better for real people, you build governance structures that reflect that commitment. You keep humans in the loop on decisions that matter. You deploy solutions that serve the mission: making healthcare simpler, more affordable and more human.

That’s the work we’ve been doing for more than a decade, and it’s our foundation for the next decade and beyond. The people we serve deserve an organization committed to getting this right year after year, not just chasing the next innovation cycle.

Trust in healthcare AI has to be earned over time. And we’re in it for the long game.