In this interview from Appian World 2026, Jeff Renon, director of information systems at Global Excel Management, joins Gregg Aldana, vice president of solutions consulting at Appian, to talk with theCUBE's Dave Vellante and co-host Alison Kosik about how process-centric AI is transforming claims management and operational efficiency in global healthcare administration. Renon describes Global Excel Management's core mandate — accelerating the speed at which claims are adjudicated and information reaches customers across its network of 2,500 employees operating in nine countries. Aldana explains how Appian distinguishes itself by embedding AI directly into process workflows rather than layering it on from the outside, enabling organizations to move from experimentation to production at a pace that generates measurable returns almost immediately.
The conversation also explores how the regulated nature of healthcare demands that AI operate within auditable, inspectable frameworks rather than as a black box. Aldana details how every AI agent deployed on Appian must follow defined, governable steps — a critical requirement in environments subject to healthcare compliance rules. The discussion then shifts to a broader competitive argument: rather than using AI to cut headcount, the most aggressive companies are deploying it to double output with the same teams. Renon and Aldana also highlight how adaptability speed — the ability to integrate a new LLM or capability as soon as it emerges — is becoming as important a benchmark metric for CFOs as raw cost savings. From reducing behavioral health claim onboarding from six months to six days to warning that AI will produce market winners and losers faster than any previous technology wave, the discussion makes a compelling case for why process-first AI adoption is the defining competitive differentiator of this era.
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Jeff Renon, Global Excel Management & Gregg Aldana, Appian
Dave Vellante & Alison Kosik sit down with Jeff Renon, Director, Information System, Global Excel Management & Gregg Aldana, VP, Head of Global Solutions Consulting, Appian, at Appian World 2026 at the JW Marriott Orlando, Grande Lakes in Orlando, FL.
Jeff Renon, Global Excel Management & Gregg Aldana, Appian
In this interview from Appian World 2026, Jeff Renon, director of information systems at Global Excel Management, joins Gregg Aldana, vice president of solutions consulting at Appian, to talk with theCUBE's Dave Vellante and co-host Alison Kosik about how process-centric AI is transforming claims management and operational efficiency in global healthcare administration. Renon describes Global Excel Management's core mandate — accelerating the speed at which claims are adjudicated and information reaches customers across its network of 2,500 employees operatin...Read more
Jeff Renon
Director - Information SystemsGlobal Excel Management
Jeff Renon, Global Excel Management & Gregg Aldana, Appian
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>> Welcome back to Appian World 26. We're streaming live here in Orlando. I'm Alison Kosik joined alongside by Dave Vellante. We're about to talk about scaling AI-driven efficiency in global healthcare operations.>> Yeah, we're deep into day two. We had some great customer stories and looking forward to this one.>> Yeah, let's bring him in right now. We've got Gregg Aldana. He's the vice president head of Global Solutions Consulting with Appian. Welcome to The Cube again.>> Thanks for having us, Alison.>> And we've got Jeff Renon, Director Information Systems with Global Excel Management. Welcome to The Cube as well.>> Thank you very much.>> So Jeff, I'm going to start with you. I'm curious what the core problem was that you set out to solve, and how did your approach evolve as you introduced more automation, more AI?>> Good question. So basically, at a very high level, we wanted to be able to track or be able to get information to our customers and to our employees faster. And to be able to ultimately pay-claim faster is really our ultimate challenge or goal.>> And where did your partnership with Appian step in for that?>> Yeah. So, during the whole process, we started, basically took a step back of looking at our whole process and saying, "How do we want to solve that problem?" And we wanted to know how do we get our data faster, better. So we kind of took a step back and said, "How do we get data from our customers first? And then how do we get that information into our employees' hands faster?" So basically, we built our front end tools through Appian, through portal, so that we can ingest the data better and faster, and expose that to our employees better.>> And Gregg, this was right up Appian's alley, right?>> Oh, it was right in our wheelhouse. And I think one of the unique things about Appian is that how quickly you can go from experimentation or a proof of concept into production. And a lot of that has to do with not just using AI, but the platform is very cohesive. And where a lot of platforms will piece together in both AI and from the outside, with Appian, we're betting it right in the middle. So, let us help Regeneron get there a lot faster.>> Jeff, can you tell us more about global excel management? You're based in Canada, you're an international administrator.>> Yes.>> Third party administrator. Tell us more about your business.>> Yeah. Basically, we're based out of Canada. We're a global provider of medical assistance, claims assistance, and also cost containment. Our headquarters is in Quebec, but we have offices in nine different countries. Globally, we have 2,500 employees servicing members, our client members in 90 different countries.>> Okay. So it's about cost efficiency.>> 100%.>> You're helping your clients manage risk.>> Correct.>> Service claims.>> Yes.>> Okay. So what are the real drivers in your business today? What's driving the decision-making around where you put your resources?>> The biggest one is speed. Nowadays, everyone wants everything now. They want their claim paid yesterday.>> It's the millennials.>> Everything is a now.>> How can we not respond?>> We're a very impatient culture.>> For sure. And that's kind of where we want to go. Ultimately, like I said, how do we pay our claims are faster. And that's really where we've been kind of looking at our whole process and saying, what are our challenges? We knew we had challenges. We knew we had things that we need to fix, but obviously at the end of the day, we had to focus on something and that's kind of how we want to look forward for that.>> And Alison, I presume as well, I mean, when you're adjudicating claims, you don't want to go back and forth, back and forth. I mean, that's costly. You want to get it right the first time. Explain it. If the customer has to take a haircut, you explain why. If not, if you're rejecting it, you want to explain why. Maybe there's an escalation process, but you want to make that as efficient as possible.>> And streamline, exactly.>> Absolutely. And really give them enough information. So what happens is we don't want them to be reaching out to us. We want to give that information as quickly for them so that they're not calling us every other day asking them, "Where's my claim?" And that type of thing. So we want to make sure that we alleviate that issue.>> So, in the early days of generative AI, and Gregg, I wonder if you could chime in this as well.>> Sure.>> We saw a lot of people, because it was so experimental, stealing from other budgets to fund their AI. And then it's become more obvious where the value is, but I wonder if you could sort of take us through the journey post the AI heard around the world.>> Sure. Yeah.>> How you guys have worked together? What's some of the successes that you've had? And how you guys have succeeded together?>> I tell you, the partnership with Appian and GM has really been phenomenal. And it's kind of a blueprint that we're seeing over and over again. The technology can solve some of these problems so quickly that it's actually generating the return on investment that pays for a lot of these projects. So that need for speed, that translates into real dollars. When we can adjudicate a claim, or you can actually address a customer's concern that much quicker, that's more revenue. These things are actually paying for itself. And so there's a willingness, well, what else can we do? And so we're seeing these projects go from idea into production faster than we would've ever imagined before. So it's really been a great partnership, but what we're also seeing is that it's not just enough, like the traditional ROI, like time savings, cost savings, those are great drivers, but expectations are changing. Jeff talked about people are getting impatient, they want things faster. And with ChatGPT, things have not slowed down. How quickly a company can adapt to those changes is now becoming some of the benchmark metrics here. How quickly when a new system comes out or a new LLM or a new finding, can we actually implement that change? That is just as important to a CFO than just the raw cost dollar savings.>> Why is process so important in healthcare environments, and process also including cybersecurity as well?>> Well, I mean, it's a regulated environment. And there are specific rules that have to be followed. And I think one of the things that was a great match between Appian and GM here was the fact that anything that you do on Appian can be audited by a third party. And you're not just using AI in isolation, or AI is a black box where we don't know what it's doing. It's AI being given a set of very defined regulated processes that can be inspected, so that if we roll out an AI agent, there are very specific steps that it has to follow. There are government rules, there are healthcare rules. So that's why it's very critical that you're very strategic about where we place AI inside these healthcare processes.>> Back in the day, when the IT department was lucky enough to implement something that saved the company money, because they had an idea, or maybe they're talking to the business, and it was successful, the next year your budget still got cut by 5%, do more with less. What Craig was just saying is essentially some of these AI projects are paying for themselves. Is there a gain sharing? Are you able to reinvest that?>> Oh, absolutely. That's one of the things that we are trying to do, is look at the data efficiency, where else can we take that money, and focus it on other projects that, in turn is gosh, you're going to save money as well, right? So, for sure. But also like you're saying, it's always do more with less, right?>> Wait, I'm going to challenge that, Jeff, because a lot of customers are not saying do more with less, they're saying do more with more. And so a lot of companies aren't just saying, "Hey, I don't need as many people to do what I used to be able to do. I can do more." It's like, "Well, wait a second, with the same number of people, I can double my output now." And so that's where we're seeing a lot of competitive companies really take a different mindset, like bust out of the common way of just cutting.>> Because one of the things I've noticed, it's not a broad trend yet, but I've seen it more and more where the CFO is taking more of an operational role. I mean, Scarpelli kind of was like this, right?>> Yes. Our old firm from ServiceNow.>> And so they had a much more of a go to-market and a growth mindset.>> Yes.>> And so it was a good balance where the capital allocation, wow, if I can invest a dollar in technology and get back four, I'm going to invest $4 and get back 16.>> Well, I mean, we saw the journey of a lot of these tech companies over the last 10 years, and hyper growth is a term we all saw. Well, AI is making hyper growth available to a lot more industries now, not just the tech industry to grow, like you said, double every so many months. What are you seeing the impact of that?>> Really, it's kind of hard to say at this point. There's so much going on. The curve, the AI curve, again, one of the questions is like, where are you in your AI journey, right? That goalpost changes almost every day, right? From three years ago, if you saw us three years ago to we are now, pretty substantial growth to where we are. But if you look at what AI is three years ago to today, and then where we are today with AI, we're still on that up slope, because that goalpost of like AI is moving all the time, all the time.>> We're all used to S-curves. We learned about them in school, and we've sort of experienced them every new technology wave, whatever it was, cloud, internet, mobile, social, big data, PCs, it was kind of an S-curve. Erik Brynjolfsson, the economist, he was now at Stanford, he was at MIT when we first interviewed him on The Cube. I think that's probably a step-up maybe. I don't know. We're East Coast, so I like East Coast AI. Anyway.>> East Coast AI.>> There you go. I'm around with that.>> That's right.>> He has this concept of a J-curve, which is kind of a steeper up, which I don't know, it's kind of a weird question. Does it feel like a historical S-curve, or does it feel like more of a... Well, it seems like it's all over the place curve.>> It's almost like a straight... The way the industry is going, it's almost an exponential exponential curve, right? Not even a curve. It seems like there's no top at this point, right? It's just a straight lineup.>> What I'm finding is a lot of companies are... I don't think they have a handle on how quickly things are going to escalate, and how fast. And the companies, like Global Excellence here, they're responding very quickly or going to be much more competitive. I think you're going to see winners and losers a lot more quicker than you used to be able to see them. You will see companies disappear in months, and you'll see new companies emerge out of nowhere. It's just so fast nowadays. We've never seen anything like this.>> Jeff, what does success look like to you for your company in the next couple of years?>> That's a good question. Right now, I think our success point is making sure that obviously our clients are happy, right? And again, we get more business in there so that we can process more claims. Really at the end of the day, that's kind of what our goal is, is to be able to process claims faster, and make all our customers happy.>> And sorry, I apologize for not knowing that you might have said this before, you're a global organization?>> Correct. Yes.>> Okay. And you service plenty of Canadian constituents, right?>> Correct. Yes. We have a large book of business in Canada.>> How would you describe the Canadian healthcare system? Thumbs up? People like it? People happy? Thumbs down?>> Oh, good question.>> Yeah, we hear all this debate in the US.>> Okay. I'm born and raised in Canada, and that's all I know. Is it great to walk into a hospital and not have to worry about a million-dollar bill? Great. But is it not good that you're sitting in a hospital waiting room for 11 hours? Not so good. They call it free, but is it really free? Time is not free, right?>> I like that honesty.>> That's kind of where I see it, where it's... You can walk into anywhere and get the service that you need. It might take six months to get it, but you'll get it.>> That's deflect from what we're talking about. Let me ask this. You guys are some of the smartest people about this. Do you see an AI fixed to this? Do you see a technological fix to that problem that you're just talking about?>> No, because at that point, unless you're going to see an AI, you're going to type in your problem and AI is going to spit out a prescription, to me, it's more about the resources available.>> Well, I was going to say, I have a little bit of a different take. I work with a lot of healthcare providers, and we even saw it today with the claim autism. I mean, they reduce the amount of onboarding time from six months to six days. And so I agree with you in terms of time is of the essence. I was traveling back from a conference in Australia a few months ago and I got an appendicitis on the flight back. And so I got rushed to a hospital in San Francisco, and I was literally in surgery within four hours. Now, I have private healthcare insurance, so maybe that might have escalated it, but time was of the essence. I was going to have something that would burst. I couldn't wait two days. So we're seeing a lot of the paperwork and a lot of the manual processes around getting access to healthcare being addressed rapidly with AI. I mean, if you look at an example like that, a claim autism, in behavioral medicine, there's really no standard way to document a diagnosis. It is the perfect use case for AI helping you, because you could have one diagnosis documented a hundred different ways, an AI agent can always deal with that in a very quickly way. People will spend weeks trying to sift through that.>> Well, and the reason I ask that loaded question is because the promise of AI is it's going to help with these really big, chewy problems: healthcare, climate, energy, on and on and on. And so I'd like to probe on, okay, what does that actually look like on a practical and day-by-day basis? How do we get from here to there? And companies like yours are actually doing the hard work. So, we appreciate that. And boy, that's not a good time to get appendicitis.>> The longest flight possible, Sydney to SFO, the 14-hour flight, I'm sure many of us have been on that, one hour into the flight, got the pain. And boy, oh boy, I got to the hospital very, very quickly. Thank you for that. But I really see AI addressing a lot of these problems and getting people access to healthcare. I mean, even if you look at their situation here, moving from just automating to now being a little more predictive?>> Oh, 100%. Oh, for sure. There's always a space for that. But when you're talking about the healthcare, 100% lower the question on that side of it. When you're talking about... To me, I don't have anything to compare it to. I see all the other, how the US healthcare is compared to what we have, it's like pros and cons on both.>> Is there a tiered system? Can you get access to more expensive healthcare?>> That's the one thing that they are trying to talk about. Can they privatize some of these things? I live in Windsor, so basically a border town from right across from Detroit.>> Michigan, yeah, yeah.>> So really at the end of the day, we have a lot of people that if they can't seek healthcare in Canada because they say they could get it, but say it's a six-month wait time, they go over and pay, they go over the border to pay.>> Yeah.>> Interesting. Wow.>> I heard about that.>> Because they feel their need is more.>> That's ironic. I have friends who did LASIK surgery in Canada because they thought it was better and cheaper.>> Oh, wow, really?>> So who knows? It goes both ways. Well, guys, thank you. This was fascinating.>> Great conversation. Thank you.>> This was great. I think we went in a lot of different areas.>> Absolutely.>> And that's how you find answers, right?>> Welcome to The Cube.>> Yeah. Thanks for being on The Cube. And you've been watching The Cube, the leader in high-tech enterprise analytics and live tech coverage. We'll be right back.