From PegaWorld: enGen's Richard Rutkowski on moving agentic AI from theoretical to practical

Summary

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Podcast Summary: The Agile Brand with Greg Kihlström®

Episode: From PegaWorld: enGen's Richard Rutkowski on Moving Agentic AI from Theoretical to Practical

Date: June 23, 2026
Guests: Greg Kihlström (Host), Rick Rutkowski (Director of Product and Technology, enGen)

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Episode Overview

This episode focuses on the transformation of agentic AI (autonomous, action-taking artificial intelligence) from a conceptual framework to an operational reality in enterprise healthcare. Greg Kihlström and Rick Rutkowski discuss what it takes for organizations—particularly in the highly regulated, complex healthcare sector—to transition from predictable, human-in-the-loop AI to agentic AI that orchestrates and automates on its own. They explore the strategic, technical, and cultural shifts required, hurdles faced, and the practical steps to adoption, with examples from enGen’s work in improving clinical operations.

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Key Discussion Points & Insights

1. What is Agentic AI and Why Move Towards It?

• Definition & Strategic Shift
  • “With AI, you're taking information and analytics that a human will then step in, interpret and act upon. With agentic AI, you're…replacing that human…when you're making that determination or decision.” (Rick Rutkowski, 03:43)
• Drivers & Healthcare Pressures
  • Aging populations, clinician burnout, increased regulation, and escalating costs are pushing health plans to seek scalable solutions.
  • Fragmented, disconnected traditional care management systems can’t scale to meet these pressures.
  • “If you want to scale, you can't go with traditional care management...you have to move to something that's a little bit more orchestrated or interoperable, that utilizes data…” (Rick Rutkowski, 04:53)

2. Organizational Buy-In for Agentic AI

• Navigating Regulation and Building Trust
  • Healthcare’s privacy and security needs dictate careful governance: dashboards, auditing, traceability for every agent/AI system deployed.
  • Starting with “use cases that are there today” and scaling up from proven pilots is essential.
• Gaining Stakeholder Support
  • Operational teams need to see real value—the approach: start small, prove value, pilot in workflow, grow adoption from there.
• Quote:
  • “You have to have a full picture of each and every agent that you put out there…You need your operations team and you need something that's going to bring them value.” (Rick Rutkowski, 05:18)

3. Practical Implementation: Architecture & Technology

• Platform Approach Using PEGA
  • Building a “chassis” that enables AI agents to work across ecosystems and data sources.
  • Data-Driven Responses: Example of a hospital discharge event triggering coordinated agent action (case creation, care scheduling, patient nudges).
  • Data Integration: Structured, unstructured, real-time monitoring data; all must be unified and accessible.
    • “That chassis is what makes it possible, right, for agents to work across the entire ecosystem…” (Rick Rutkowski, 06:50)
• Human-in-the-Loop Remains Critical
  • Automation reduces clinician burden and lets them focus on clinical expertise.
  • Most systems maintain human review for trust and safety, especially for mission-critical decisions.
  • “Generating summaries still requires clinical acumen to review it…So human in the loop is a good way to gain their trust.” (Rick Rutkowski, 08:44)

4. Impact and Measurement of Agentic AI

• Success Metrics
  • Focus on enabling “more care, faster” by freeing clinicians.
  • Traditional outcome measures (fewer ER revisits, cost savings) supplemented by qualitative KPIs (clinician satisfaction, engagement).
  • Many results currently in pilot/proof-of-concept phase, but positive anecdotal feedback fuels expansion.
  • “When you can do more and gain more engagement, it's proven over the years that you're going to have better outcomes.” (Rick Rutkowski, 10:57)
• Utilization Management Case
  • Parallel processing: Agentic AI runs in tandem with human reviewers until trust/performance thresholds are met, then automation increases.
  • “You can shift it left, if you will, from…parallel processing to putting it right in front of the medical director…to saying, you know what, we're just going to let that go because…we approve it in 95% of these situations and the agent knows that type of thing.” (Rick Rutkowski, 12:48)

5. Future Vision & Best Practices for Adopting Agentic AI

• Platform Scalability & Flexibility
  • Modular, unified architectures support adaptation to evolving regulations, changing populations, and new tech advances.
  • “If you're staying put in traditional systems…you're going to be left behind…” (Rick Rutkowski, 14:29)
• Risk-Aware, Stepwise Adoption
  • “It's not go all in...but taking those initial wins and building on them and learning.” (Greg Kihlström, 14:57)
  • Responsible, gradual rollout as opposed to instant full automation.

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Memorable Quotes & Moments

• On Defining Agentic AI:
  • “You're kind of replacing that human…The driving need to shift...is really scale.” (Rick Rutkowski, 03:43)
• On Proving Value:
  • “You have to have a full picture of each and every agent…You need your operations team and you need something that's going to bring them value.” (Rick Rutkowski, 05:18)
• On Human-AI Collaboration:
  • “It’s less about replacing the individual, more about supplementing their ability to do what they do best…free them up to actually work with the member.” (Rick Rutkowski, 08:44)
• On Staying Agile:
  • “When you think you have it figured out, you should keep looking because there's always something else and there's always something new…” (Rick Rutkowski, 16:13)

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Timestamps for Key Segments

• [03:43] – Agentic AI: What It Is and Why It Matters
• [05:18] – Building Stakeholder Buy-In and Responsible Governance
• [06:50] – Architecting for Agentic AI: Data, Chassis, and Integration
• [08:44] – The Critical Role of Human-in-the-Loop for Trust and Adoption
• [10:57] – How to Measure Success: Clinical Outcomes and Value Proof Points
• [12:48] – Utilization Management: Practical Path from Parallel to Automated
• [14:29] – Future-Proofing and the Risks of Standing Still
• [16:13] – How Rick Stays Agile and Continuously Adapts

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Tone & Language

The tone is pragmatic, insightful, and candid—as befits a conversation between senior industry practitioners wrestling with real-world change. The discussion balances optimism about AI’s potential with clear-eyed recognition of healthcare’s unique challenges and the necessity of human oversight.

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Useful for

Anyone in enterprise healthcare, technology, operations, or digital transformation—especially those seeking actionable insights on implementing AI responsibly, architecting scalable solutions, and driving cultural change among clinical and operational stakeholders. Also highly relevant for those assessing the shift from predictive to autonomous, agentic technology in regulated industries.

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Transcript

[A]

Hi, I'm Greg Hillstrom, host of the Agile Brand, and here's a question for you. Most leaders think about AI as a tool to analyze data and assist with tasks. But what happens when your AI becomes an autonomous agent, not just providing insights, but actively orchestrating complex processes on its own?

[B]

Today we're here at Pegaworld 2026 at

[A]

the MGM grand in Las Vegas and we're going to talk about moving AI from a theoretical concept to to a practical value driving reality. Specifically, we're going to explore the transition from predictive AI to agentic AI and what that means for orchestrating complex customer journeys, the architectural and data foundations required to successfully deploy autonomous AI agents at an enterprise scale, and how this approach enables a new level of proactive personalized engagement that improves outcomes and drives business value.

[B]

Welcome to season eight of the Agile Brand Podcast. This season we're going all in on Expert Mode, MarTech AI and Customer Experience, talking with the people and platforms behind the brands you know and love. Again, I'm your host Greg Kilstrom and I help Fortune 1000 companies make sense of MarTech AI and marketing ops. Hit, subscribe or follow to make sure you always get the latest episodes and leave us a rating so others can find us as well. PEGA provides the leading AI powered platform for enterprise transformation. The world's most influential organizations trust pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences, and modernizing legacy systems. Since 1983, Pega's scalable flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Learn [e-mail]

[A]

to help me discuss this topic, I'd like to welcome Rick Rutkowski, Director of Product and Technology at Engine. Rick, welcome to the show.

[C]

Hey, Greg, thanks for having me today.

[A]

Yeah, yeah. Looking forward to talking about this. And great to be here at pegaworld. Before we dive in, why don't you give a little background on yourself and your role at engineering?

[C]

Sure. I'm the Clinical Product Director at engin. We are a wholly owned subsidiary of Highmark Health, which is the third largest Blue Cross Blue Shield plant in the country. My background is about 28 years in healthcare. The last 10 have been in the clinical space. And I have to say this is an explosion, I think, in an area that I've never seen before in the 28 years. It's just clinical is just where it's at if you want to make a difference.

[D]

Yeah, yeah.

[A]

So I know you touched briefly, but let's talk a little bit more about Engine and, you know, what's the company's core mission and the types of organizations that you primarily serve?

[C]

Yeah, Engine's a health tech company. We support other health plans on their journey to improving the way they manage care, deliver care, things like that. We focus on the underpinnings of that, the platform, the systems, the capability. But for me, my focus is predominantly predictable, that I help them with their clinical journeys.

[D]

Got it, got it.

[A]

So, yeah, let's dive in here and certainly we're going to talk about a few things, but I want to start with really the strategic approach here and this strategic shift to agentic AI. Certainly lots of people talking about it, but in extracting value from it, a lot of organizations are running into challenges and certainly there's a lot of headlines about things like that. From your perspective at Engine, how do you define agentic and what's the fundamental strategic shift required for an organization to move towards it?

[C]

Yes, with AI, you're taking information and analytics that a human will then step in, interpret and act upon. With agentic AI, you're kind of replacing that human. Not that a human's not in the loop, but you're replacing that human when you're making that determination or decision. The driving need to shift though, to move to an agentic world, I think is really scale. And it sounds a little odd, but if I talk about a few of the, I'll say storms that are out there in the health care world, you've got aging populations with chronic illness on the rise. We've got clinician burnout to levels we haven't seen before. So there's a work shortage. Regulatory policy. With CMS ratcheting down, sla's means more, more faster. And again, clinicians are burning out. Right. And rising costs and those other items. But if you want to scale, you can't go with traditional care management, which is fragmented, disconnected. So you have to move to something that's a little bit more orchestrated or interoperable, that utilizes data, it's modular, can connect to other systems, other vendors, other data sources. And then you gotta layer AI and add intelligence on top of that to be effective.

[D]

Yeah, yeah.

[A]

And you know, healthcare being a highly regulated and complex industry to boot, you know, what are the strategic considerations and stakeholder buy in necessary to make the case for doing something like the agent? You know, again, AI, it can sound intimidating or things like that in such an environment.

[C]

Yeah, especially in healthcare. Right. So regulations, we have to be extremely Thoughtful with how we advance, with all the privacy concerns that are out there and security concerns. But we've established governance that includes measures, clear measures, dashboards, results auditing, traceability. You have to have a full picture of each and every agent that you put out there. Or even if you're thinking about AI, you have to understand the data. Then you got to align the buy in. You need your operations team and you need something that's going to bring them value. And I like to, I tend to start with, or have started with, use cases that are there today that you can maybe scale.

[D]

Right.

[C]

Right in the workflow. Again, they're part of fully testing and piloting. And then, you know, I think the desire from their side is those pressures I talked about, they don't really have a choice, but you do have to kind of get on board. I think that's the way to go.

[D]

Yeah, yeah.

[A]

So now I want to talk a little bit more about how we take that strategy and implement it. So one of your colleagues had a session describing building the architectural chassis of the operations on PEGA to leverage this agentic AI. Can you break down what that means from a tactical perspective? What are the core components? Things like data integration, process automation, or other things that need to be in place for something like this to work?

[C]

Yeah, that's a good question. So that chassis is what makes it possible, right, for agents to work across the entire ecosystem, not even just in predictal. And this is embedded in the workflows, the AI summary, the decision making, et cetera. Agents can react to data events. I guess a good example would be and try and explain before I tell you why we did it, a discharge event. It's a data event that comes from edmr, letting you know that somebody was in the hospital for something urgent, potentially. Now they're being let out. What we like to do is several things. An agent can look at that find it, determine the criticality of it. I wasn't just in because I went because my arm hurt. I was in for maybe a cardiac event. Then it would update the authorization in one system. It would start a case for care and schedule it with a skilled case manager and another system and. And it would send a nudge to the member via digital means. Maybe it's a text, maybe it's their portal, their app, whatever it might be. That's all orchestrated through this architecture. So to get to that. Okay, to get to that, you have to hit several core capabilities. And what we did was we focused on diverse data. There's structured unstructured data, monitoring data claims. All your traditional datas are out there, but you have to bring them in, organize them, have them available to the entire ecosystem.

[A]

And, but I mean what you're describing, I mean not only are there a lot of moving pieces in there that are automated, but it's critical that they are right as well. I mean, I know I'm stating the obvious here, but we're talking healthcare, we're talking about these are pretty mission critical systems and the right data needs to go to the right place for the right person, so on and so forth. So getting that right is, you know, that seems like the key challenge, right?

[C]

Yeah, you're 100% right. And you know, the business operations are not going to buy in unless you actually prove this out. And we all hear some of the horror stories that are out there. Most of what I described has a human in the loop or on the loop depending upon what the situation may be. So generating summaries still requires clinical acumen to review it. But before when a clinician had to go look in three different systems to find data and try and bring it together, it's now presented with insights that they can confirm or deny and then that's all part of the process. Right. So human in the loop is a good way to gain their trust. It's also less about replacing, you know, there's always the worry about jobs. Right. It's less about replacing the individual, more about supplementing their ability to do what they do best, which is their clinical acumen and free them up to actually work with the member. So those are the types of things I think you have to get the business on board with.

[D]

Right.

[A]

But I think also on the flip side of that, there's so much that a human has to do, you know, in the pre automation part of that, there's so much that a human is responsible for that they have to get right. You know, so it's kind of, it's critical that the automation gets it right. But the human, the cognitive load on a human to get all of those things right and route it to the right place. It's, there's a, it seems to me like there's a huge opportunity for AI to kind of, to what you just said, get the human focused on the right thing, not just overburdened with all the things they have to put in the right buckets.

[C]

Basically the non clinical events are just burning out the clinicians and.

[D]

Right.

[C]

You know, you can just, you can't scale that way. Here's what it comes down to. And like I said, when you've got chronic illness on the rise and CMS ratcheting down SLAs, it's just not going to be possible.

[D]

Yeah, yeah.

[C]

So plans have to get on board.

[A]

So let's talk a little bit about how we measure success here. So with a system designed for earlier clinical detection and optimized prioritization, how do you measure success?

[C]

So success for us is focused on how we're enabling, I guess more care faster. Didn't say that. Well, the way we're freeing up the clinicians to do more, we're not necessarily positioned to run specific outcomes yet. We're doing a lot of piloting and proof of concepts. We do have ambient listening in production, so we are seeing some results there. I think in that front we actually do a bit of a traditional measure because when you can do more and gain more engagement, it's proven over the years that you're going to have better outcomes. Less ER visits or revisits, I should say, which allows you to save X amount of dollars because their outcomes are better. So you're helping member the health plan benefits by saving money. This type of engagement, even when I explained before with the ambient listening, is what's allowing us to scale that. So those numbers are going to go up. Outside of that, we haven't done a lot of measures yet, but we are seeing increased value. When you talk to the clinician about, wow, it is great that I have this summary and I can actually look at it and interpret it. Okay. Because not everything's agentic, but then some of the actions that come out of that could be automated in the future once you see the results are functioning well.

[A]

Well, and I would say, you know, those things that you just mentioned are they're proof points. Right. Of, you know, some, somebody listening to this that may be a little behind the curve on things but needs to get started, you know, are, are those the types of proof points where, you know, you can. It's anecdotal, but it's still powerful, right?

[C]

It is, it's very powerful. Especially if you're in a clinical space. I would say on the case management side's a good place to kind of wean into that a little bit or lean in there. You know, from a utilization management standpoint, doing it responsibly, I think is what's important. If you're out there thinking, how do I do this? Right.

[D]

Yeah.

[C]

When you make a utilization management determination today, it's always a clinician, it's always a Nurse and a medical director with agentic AI. You can now take all the clinical data you have, everything you know about that individual and the auth and compare it to the medical policy and render a decision. But it can be done in parallel to what the medical director's doing until you feel comfortable enough that yeah, they're aligned all the time or to a certain percentage that you say, yeah, the risk of it being wrong isn't really something we would worry about at that point. So you can shift it left, if you will, from that parallel processing to putting it right in front of the medical director who then human in the loop to saying, you know what, we're just going to let that go because it makes sense. We approve it in 95% of these situations and the agent knows that type of thing.

[A]

Yeah, yeah. And I mean in that shift left approach, it's not getting rid of the approval and, or the verification, it's just moving it left. Right? Yeah, yeah, definitely. So, you know, looking ahead a little bit at how does a platform based approach like the one that you've built with pega, what does that look like from a future innovation standpoint?

[C]

So I think it'll better support your flexibility in the future and your ability to scale. We talked about that. I think I've said the scale word several times today.

[A]

It's important.

[C]

Yeah, right. So understanding being able to orchestrate from a platform perspective the entire care journey as seamless as possible is important. So you're unifying the data, the workflow and the AI, that intelligence in there, right?

[D]

Yeah.

[C]

It's easier to evolve other capabilities over time, meet the changing needs, regulatory needs and just the needs of the population because I guess a chronic illness is on the rise. But if you're staying put in traditional systems and you're nervous about getting into this, I think you're going to be left behind and you're not probably doing a bit of a disservice to your members. I'm not saying you go full force into AI. AI can be a dangerous thing. But if you do it responsibly, it can be really effective.

[D]

Yeah, yeah.

[A]

I mean it sounds like starting with a measured approach and watching it and adopting slow, I mean that's what I've heard from other, several others here as well, is just, you know. Yeah, it's not, it's not go, go all in, but it's at, at, you know, at the beginning, let's say. But, you know, but taking those initial wins and building on them and learning.

[C]

Right, that's 100%. Right. And I again, I think we've seen, we've seen value, again, not necessarily quantifiable yet in our pilot stage for some of these, but we're seeing a lot of value and we're seeing clinician buy in, which is important.

[D]

Yeah, yeah. Love it.

[A]

Well, Rick, thanks so much for joining today. Two last questions as we wrap up here. First, you know, we're here at pegaworld in Las Vegas. What's been a highlight for you so far?

[C]

Alan's a great speaker as always, but I think just where AI is advanced, I mean, we've been talking about AI for the last few years and it just seems like it's finally really moving from theory to practice. The more people I interact with around here, I'm starting to find that out too. And it's across all industries, so I think that's important.

[D]

Yeah.

[A]

And last question for you. What do you do to stay agile in your role and how do you find a way to do it consistently?

[C]

To stay agile in my role, I try to stay flexible and open minded. I try to build good relationships with my peers and stakeholders and understand where the industry is going. And when you think you have it figured out, you should keep looking because there's always something else and there's always something new that's going to advance case management or utilization management for me specifically.

[D]

Yeah, love it.

[A]

Well, again, I'd like to thank Rick Rudkowski, Director of Product and Technology at Engine, for joining the show. You can learn more about Rick and Engine by following the links in the show.

[D]

Notes.

[B]

PEGA provides the leading AI powered platform for enterprise trust transformation. The world's most influential organizations trust pega's technology to reimagine how work gets done by automating workflows, personalizing customer experiences and modernizing legacy systems. Since 1983, Pega's scalable flexible architecture has fueled continuous innovation, helping clients accelerate their path to the autonomous enterprise. Learn more at PEGA through and thanks again for listening to the Agile Brand podcast. If you like the episode, hit subscribe and drop a rating so others can find the show too. And if you're interested in consulting, advisory work, or if you need a speaker for your next event, feel free to reach out. Just visit GregKillstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co. Op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.

[C]

The agile brand.