Models, Infrastructure, and Enterprise Readiness for Agentic AI - with Alex Tyrrell of Wolters Kluwer

**Daniel Faggella** (0:12)
Welcome everyone to the Emerge AI in Business Podcast. Today's guest is Alex Tyrrell, SVP and CTO of Health at Wolters Kluwer. Wolters Kluwer is a global provider of information solutions, software and services across healthcare, tax and accounting, financial and corporate compliance, legal and regulatory, corporate performance and ESG. Alex joins Emerge's Matthew DeMello on today's episode to outline how agentic AI changes operational realities in healthcare by shifting from systems that create outputs to systems that execute tasks across interconnected workflows. He explains how adoption now hinges less on model performance and more on infrastructure readiness, domain-adapted reasoning and safe integration into regulated environments. Just a quick note for our audience, that the views expressed by Alex Tyrrell on today's program do not reflect that of Wolters Kluwer or its leadership. In this episode, we cover agentic AI in healthcare. To go deeper on AI topics and learn how to evaluate AI vendors by assessing leadership expertise and why funding benchmarks can signal product maturity and stability, download our free PDF report, Five Ways to Select the Right AI Vendor at emerj.com/aiv1.
That's emerj.com/aiv and the number one. Now, the conversation with Alex.

**Matthew DeMello** (1:44)
Alex, welcome back to the program. It's a pleasure having you.

**Alex Tyrrell** (1:47)
Matthew, great to be back.

**Matthew DeMello** (1:49)
Absolutely, we're talking about models, infrastructure, enterprise readiness for agentic AI on today's show. Generative AI capabilities have accelerated. We're hearing from many enterprise leaders across the healthcare space that they've discovered that model performance alone is not the limiting factor. Instead, adoption is increasingly constrained by infrastructure readiness, domain expertise, and then that ability to safely integrate AI into complex regulated workflows at scale.
We know that agentic AI sort of was kind of the word of 2025, especially for the lay public. Maybe for insiders, really more the word of 2025 might have been infrastructure, because you got to build the back end before you build what's really going to touch the patient, the customer. How are you seeing agentic AI adoption differ from early generative AI use cases we saw a few years ago?

**Alex Tyrrell** (2:42)
Yeah, that's a great question. So I think, you know, when I have conversations with senior leaders, and I try to actually, you know, absolutely bullseye this very concept, I say create versus do. Create versus do. LLMs create things. They create emails. They create a poem, if you like, a recipe. They can create images. They can create music. They can create sound. It's very transactional experience. And the LLM itself cannot influence the outside world. They cannot send an email for you specifically, right? That gets you to agentic, right? Agents do things. They act, plan, reason, execute. They do have the ability to interact with the outside world.
They could potentially park your car, things like that. And so the LLM is still at the core of the agent, but additional technology includes remounts that have been provided around it, so it has more ability to interact with the real world. I think that's a pretty good definition of the difference.
What's really so fun? Any sticks may be a whole new year, but so far I got away with that.

**Matthew DeMello** (3:47)
No, I've maybe differentiated on another big step level change we see from agentic AI is the ability to jump between domains and programs. I can have an agent go buy me concert tickets, but it's going to have to know where I live, it's going to need my credit card information, it's going to need to go to Google and tell me, know that I'm going to have to get there, it's going to need to jump to Ticketmaster, open its own web page. So and we haven't really seen systems, especially that the public uses, really jump those domains quite yet. So that's another gigantic step with agentic. Go ahead.

**Alex Tyrrell** (4:22)
Yeah. So I think what we focus on in the professional setting, and by the way, at Wolters Kluwer, we've been focused on this for a very long time. And that is the idea that it's really about the jobs to be done, right? I mean, we were a print heritage and textbooks, and by the way, we're a 189 year old company, and there were no computers back then. As we made that journey and the evolution from print to digital, to online, to cloud, to SaaS, to what we call expert solutions, we have been continuously focused on, what is the day in the life of a customer? What happens after you read a journal article, or you look up something in the tax code?
What's the next step in that workflow? That's really where we focus on jobs to be done. The fact that we've been doing this for well over a decade, when Agenta came on the scene, it was almost like, aha, what a catalyst. What an accelerator to this strategy where we take domain expertise, our subject matter experts. We combine it with best in class, in verified trusted information, and then we layer in technology. That is going to drive outcomes. That is owning an outcome potentially end-to-end, and with Agenta, it could be very profound. In the healthcare setting, one of the most obvious places that we talk quite a bit about is the whole EHR workflow.