How are you staying on top of all of that and setting your priorities straight right now?

Yeah, absolutely.

First, healthcare is complex, so we work in a fairly complex industry.

We also are part of CVS Health, which creates its own balances across a large enterprise like ours.

But in Aetna, the goal is very simple.

We focus... on areas where technology can create better experiences for, first of all, our members, then our providers, but also our colleagues.

And we are out there to solve real business problems.

What you're doing right now that's turning that optimism into something that clinicians are using daily in their actual workflows?

How are you staying on top of all of that and setting your priorities straight right now?

Yeah, absolutely.

First, healthcare is complex, so we work in a fairly complex industry.

We also are part of CVS Health, which creates its own balances across a large enterprise like ours.

But in Aetna, the goal is very simple.

We focus... on areas where technology can create better experiences for, first of all, our members, then our providers, but also our colleagues.

And we are out there to solve real business problems.

What you're doing right now that's turning that optimism into something that clinicians are using daily in their actual workflows?

And I wonder, you know, how do you think about that and being a more proactive partner in a member's health journey?

Yeah.

You know, it goes back to, um, historically the healthcare experience hasn't been focused around the consumer.

And so now, if you shift the dynamic to, uh, member experience, consumer experience, removing the friction points, AI now enables you to take all that data that I talked about earlier.

Now we have all the clinical data, very rich data set.

We have a great trust and relationship with our members.

They're using our digital properties, and then we can now use AI to augment that and get them what we call a next, next best actions, right? It's, it's really around, um, sort of, sort of that preventative, uh, care that we can provide.

As you look ahead, let's say five years, what excites you in terms of the change that, uh, may continue to evolve, that impacts, um, members, that impacts the company, pay-- providers, et cetera? Y- Where do you see healthcare at the, the back half of this decade and the early part of the next one?

Mm-hmm

... that actually deliver better outcomes.

And so, you know, we have tons of an examples, um, where we're using AI, uh, to reduce that friction.

And like you mentioned in the beginning, a lot of that is around the administrative burden.

Um, we're the only industry that assigns healthcare to consumers, if you just think about that for a moment.

In no other industry do you, do you walk away from a visit and have homework.

So, um, you're right, there's a lot of, uh, there's a lot of use cases today that we have in production where we're using, you know, voice, maybe that's ambient listening.

So one of the key questions about AI is the issue of trust, right? How is this information being generated? What information is being left out? What information is deemed relevant by the AI algorithms, right? Is it hallucinating? So how do you approach the issue of trust? How often are you looking at these algorithms to make sure that there isn't model drift or, you know, things like that?