Frank LaSota on AI and Automation Signal a Turning Point for Healthcare IT

Hello, and welcome to the latest edition of the Textron AI Leadership Series. I'm your host, Mike Ra. Today we're with Frank Ada, who's ccio, OCTO, for Zider TruCare.

And we're having a chat about the impact tech and AI in general is gonna have on maybe, hopefully improving the state of healthcare. Frank, welcome to show. Thanks.

Really appreciate being here, Mike. Uh, look, we looking forward to our discussion. I feel like something is fundamentally changing here in the healthcare sector because for years when it came to tech, healthcare was a laggard.

I mean, outside of maybe some fancy new machine that would save someone's life, you know, the whole backend of healthcare was always something of, uh, you know, a lot of legacy technology that was hard to support. And now when I look around, especially in the age of ai, I almost feel like they're at the forefront of this because, well, maybe they have the data and maybe they've had instruction enough to make use of all this stuff. But what's your current assessment of the state of healthcare and it Yeah, it, it's definitely evolving from an AI perspective and, um, zider TruCare, um, we focus, um, on the, the clinical, um, aspect of, uh, healthcare with care management, uh, utilization management, a lot of population health.

An easy example of that is when you go to the doctor, go to the doctor, you need a procedure, you need to get a prior authorization approval. Our utilization management software handles that. Same with on, uh, kind of like a, a a case management side when you're on a care plan, um, working with physicians, uh, and, and nurses to, to, to review that, to, to give you the outcome that you need.

And, um, you know, we also develop agent AI products that are embedded in these ecosystems that are changing the way business process within large, uh, payers. Insurance companies work, definitely a ton of data. Um, but it's connecting that ecosystem, redefining business processes.

And going back to your original question, there's been a lot of great technology deployed over many years, um, with less than optimal outcomes. And what we do through our, our products that have been around for about 20 years, we have 44 million lives, um, supporting our customers on our platform is to reshape, um, and connect that ecosystem and redefine those, um, business process that deliver outcomes, uh, in, in, in the world that is evolving given the cost pressures, um, all of the regulatory mandates from, um, entities like CMS, et cetera. To your point about cost, there's a lot of conversation about that, uh, all up and down the line from Congress all the way down to the local dinner table probably, or diner.

Um, what impact can it have on those costs? Because some of them are kinda baked into the system, but it's not clear how many of them are actually directly relatable to the fact that the data itself is problematic to manage. Mm-hmm.

Y yeah, and, and great question. And, um, that's the, the, the business we're in of solving with, um, you know, our, our, our product suite. And we look at the cost of, of care is going up, the cost to administer, um, workloads are going up, data is spread across these large enterprise ecosystems.

In some case, disconnected very or very hard to connect a lot of one-off solutions. And the healthcare costs rising population is not, um, getting any healthier. And what we're able to do is go in and we sell our, our product in terms of piloting.

We show, um, hey, how we can, uh, re-engineer these processes, um, with our agent ai, take human out of the loop, and also improve outcomes. Um, and, you know, we're looking at it from, Hey, we can give you a, a 20% performance improvement with operational optimization increase. Um, you know, the, the, the outcome that you are delivering to, um, your, your customers, the, the folks that you insure and really, um, e extract that cost from the business at, at a lower price point.

And that's what you have to do because there's been excellent technology implemented for the past 15 to 20 years in these companies. And the outcomes aren't changing. The costs keep increasing, and you have to really get in there, um, connecting the ecosystem through agent ai, taking risk from these payers, insurance companies, turning that into opportunity, um, not only from better care delivery, lower prices on plans, um, but also technology outcomes.

So what is the appetite for agentic ai? And I asked the question because on the one hand, there is a lot of data to navigate and it is part of the problem, but, um, there are also trust issues with agentic ai and I have to put the right controls in place and I mm-hmm. Have the right context to get there an outcome.

Mm-hmm. And healthcare doesn't like probabilistic solutions. They want it to be right a hundred percent of the time.

Yeah. Mm-hmm. Mm-hmm.

Yeah, and that's a, a, a great question. Um, and, you know, some of the challenges and opportunities we have in front of us, if you look back at the beginning of 2025, nobody was talking about AgTech ai. And now there's products and companies that solely focus on it.

Yesterday I read an article that, um, the Salesforce CEO will take cloud out of his VO vocabulary and only speak in agentic interfaces. So this is, um, you know, where we're at, it evolves. But, you know, there are, um, core challenges to model hallucination bias.

And our approach when we come in, especially on the payer side, on the provider side of healthcare, there's been a little more uptake, um, a little bit more quickly, a little bit more in, in public sector too. Um, but, you know, we bring, um, a, a set of capabilities when we go to market and, um, we call it our recode philosophy with a model office. So we have PhD MDs that support and build our technology as well as your traditional engineers.

And we go in, we, we prove it out. Um, we're able to train models. We're able to bring, um, a diff different models in to, um, increase evidence-based outcomes and provide confidence scores with, um, how we deliver AI through workflows, reshape workflows.

And it's a, a, a, a barrier. Like sometimes it's a barrier, sometimes it's an opportunity, but you have to involve, um, you know, chief medical officers compliance, uh, folks when, when you're rolling this out to, to overcome those challenges. And it's also working with ecosystems that are API enabled where you have agents to agents doing the work, and an agent in the background might be going and pulling data solving problems and delivering them to you, where that has to be accurate, you know, on, on a customer side as well as within your product.

But I think as we train more, we look at eliminating bias, hallucinations and, and focus on refining our models. It'll have larger and larger uptake. 'cause it's very serious in terms of you have people's health and, and lives at risk and you can't have things, um, you know, deviate in that process.

So it's a, um, a like we look at it as a, a measured scale up where we could come in and we look at a line of business and a percentage of workflow and, and go from there. Um, but it's definitely new. It's where the market is going, is at right now, and will eventually, um, drive that, that change in innovation and trust.

Um, and, and supporting that from a a product perspective. We have the Zider Institute at Carnegie Mellon, where we work with them on, um, agen ai, um, challenges like this in the greater industry, um, governance, compliance, uh, efficacy from, you know, uh, the medical side of the house as well. Is this an opportunity to fix something?

And I'm asking the question because I seem to remember the time when, you know, electronic medical records were gonna cure what ails us. And we got in there and everybody seems to have these systems. And yet every time you go to a physician and you gotta move from one to the next to the next, especially if you're older, um, they still don't know, you know, what's in the record from one to the next to the other.

And, you know, it's that level of interoperability that we were trying to achieve never was, seems to have been realized in a way that resulted in a better patient experience. So is AI gonna finally deliver on that promise? Um, not by itself.

Um, we have, uh, a, a set focus on interoperability services, um, within our products, in, in services that, uh, we deliver because you can't just take all of this data that's in a disconnected, um, environment, multiple environments, mesh it together and, and bring it in. Um, it's a real philosophy, um, and it's real work to have interoperability in place. So when you bring the data in from these disparate systems into your tology, um, and you start really, um, implementing this, this type of software and, and work within the customer ecosystem, it has to be correct.

And it's not a, a, a AI is not a panacea for it. It, um, you have to work with your customers to really, um, en ensure that, um, you know, this i, this interoperability how you like your data, how it's updated, um, where it comes from is correct. We can accelerate that, um, pace.

We can provide better outcomes, but it's still something that needs to be worked at. And if you look at the landscape with what AI and agentic AI is, uh, doing to the marketplace, there are now net new startup companies popping up to focus on this interoperability challenge, uh, uh, because it's not just on the intake. It's like you said, when you move from one physician to another, uh, it, it spans EHRs, it spans clinical software companies like us, uh, claims core admin software companies, uh, CRM.

It's a, uh, a, a very large, uh, ecosystem that you have to get working correctly. But the opportunity is there to connect these in a agentic way where it can be very seamless, uh, very forward looking and less, i, I would say, siloed, um, to a particular vendor or even in some cases monolithic. But it's, you know, it's there every day solving for that challenge.

Do you think we might also, because we can get to the data better, see some actual medical breakthroughs as a result? And I'll ask the question in this regard, and I realize you're not a physician per se, but it's clear there are things like, uh, cancer clusters in specific regions, and there's should be some sort of common root cause it just has alluded us all these years, but, you know, is the answer to a lot of these questions somewhere in the data? Yeah, I, I think, uh, it, it is, it is rooted in data.

Um, it is, I think AI helps. Um, you know, we've published our, um, VP of AI innovation has published or co-published a, um, uh, uh, papers with Mayo Clinic regarding this. And, um, you know, this kind of how AI impacts, um, you know, the, the world, uh, in, in terms of, of solving these challenges.

And it, it's there, it's an accelerant. It's, um, you know, helping speed things along 'cause you want better outcomes from this. And whether it's medical devices to cancer research, to, um, you know, uh, utilization management and AI plays a big factor there.

And I think, uh, you know, we saw what, you know, cloud and, and hyperscalers have done in the past 10 to 15 years. We're just dipping our toe in the water, uh, on what a AI could bring, um, in, in terms of, of benefit to society in, in that regard. They're smarter people than, than than myself working on these challenges every day.

But I, I think it's definitely, um, you know, going to really accelerate how some of these, um, diseases get cured or variants of diseases as well. So it's tremendous opportunities, tremendous forward outlook. There are, of course, some healthcare organizations that are simply larger than others, and they have more money to spend.

But is there something you're seeing amongst them, regardless of size that says that they're more successful with IT and AI in general than others because it's something they do, or cultural issue, or, or is there something that, you know, a pattern that you see among those organizations that you just go, yeah, those folks get it. Mm-hmm. Yeah.

You know, that, that's a another excellent, uh, observation and question where, um, you find where people treat technology as an asset rather than a cost. Um, those organizations, no matter, um, how big or small, always have an advantage because they're always looking to do something with, um, an accelerator, right? It, it doesn't matter if it's AI or, you know, some type of different technology where it's embedded into the, the ecosystem.

It's delivered in conjunction with, um, type operational integration, um, joint decisioning and, you know, realistic strategies followed by very pragmatic execution. Um, those organizations really succeed, um, because a lot of what, you know, I've seen in, in, in my 25 years are, uh, you know, the organizations that have that, um, you know, really just move along, right? Um, they're able to adapt, upgrade when business throws kind of a curve ball in and they have to change, it's, uh, they're prepared to change.

It's when you look at it as purely a cost or, um, I need this for that, where the business isn't leveraged or, you know, strategy is, is not realistic, um, in terms of what you actually are encountering and delivering on a day-to-day basis. Those, those tend not to, to do really well. Um, So we're at the end of the year, you know, what is your, you know, outlook for the coming year, 2026, you know, what are you looking most forward to?

Um, just really, um, getting leaps and bounds into our agentic delivery quicker, faster. Um, 'cause we have the scale and really seeing how that evolves and where the, the, the market is going because, um, you know, we're looking and, and how we sell and go to market is completely different than a, a lot of other companies may be a year ago because we're able to write, um, software, uh, in a very much more prolific way with the tool, the AI tools that we incorporate into our engineering, our testing. Um, and you know, how we del and our delivery process and just continuing to build and optimize that, tackling new challenges, um, that are coming our way.

Um, we still have, um, you know, some legacy products that we have to, to, to, to pull forward. Um, but 2026, the outlook is, uh, uh, really good. And I, I think too, um, all these different startups in our space and, and what they're doing, um, lend a lot to us that we can, um, utilize to move and shape, um, what we're doing in our own space.

So, um, you know, the, uh, I, I think we're, we're kind of like on a three month iteration cycle. I think it's going to be that fast or quicker where we have to, uh, uh, adapt and adjust then, uh, you know, try to, um, keep our position, uh, within the market and not being, uh, caught from behind. Hey folks, I think we all realize at this point that AI will help from it and all kinds of other automation is having a profound impact on our lives and everything that goes along with that.

But in terms of benefiting society, well, I think in the healthcare space, we're about to see some amazingly profound things. Hey, Frank, thanks for being on the show. Well, thanks for having me, Mike.

Uh, really enjoyed it. All right, and thank you all for watching the latest episode of the Techstrong AI Leadership Inside Series. Find this episode and others on our website.

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