FinOps X 2026 | Ben Pippenger, Zylo

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Ben Pippenger

Co-Founder

Zylo

play_circle_outline Zylo Uses ML Trained on $90B of Spend to Discover Apps and Inventory SaaS, Normalizing Data, Tracking Contracts, Seats, Usage

play_circle_outline Shadow AI Surge: ChatGPT Is Top Employee Expense as Enterprise Generative AI Spend Soars 400% YoY

play_circle_outline Convergence of FinOps and ITAM/SAM for consumption-based SaaS management

play_circle_outline App rationalization: consolidating redundant tools and managing renewals

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Ben Pippenger, Zylo

Ben Pippenger

Co-Founder Zylo

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John Furrier

>> Welcome back over to theCUBE's live stream here in San Diego at FinOps X 2026. We're unpacking FinOps and its impact to the cost side, of course. The revenue being generated, the value being created with AI is off the charts. Our guest is Ben Pippenger, co-founder at Zylo here on theCUBE. Great to see you from Indianapolis.

Ben Pippenger

>> Yes, Indianapolis. That's right. Thank you.

John Furrier

>> All right. Where all the action is , I'm a Patriots fan, just going to say.

Ben Pippenger

>> Oh, I didn't know that. I think I wouldn't have been here if I knew.

Paul Nashawaty

>> Yeah, two of them.

Ben Pippenger

>> Oh.

John Furrier

>> Thanks for coming on. Appreciate it. We had to get sports in there somehow, but they'll have a comeback. We'll see how they do. Although Peyton Manning did a good round last round, Pro-Am. You guys are doing something different with FinOps in the cloud and SaaS. Explain what you guys do real quick in this context because it's a little bit of different approach.

Ben Pippenger

>> It is a different approach. So, we're a SaaS management platform. We really serve the enterprise and help them do a handful of things around the SaaS applications that they're buying. First and foremost, it's discovering all of them. So, we've got a machine learning based model that processes through payment data. It sits on top of about a $90 billion collection of SaaS AI and cloud spend to identify all the different SaaS applications that an organization's buying wherever it happens in the company. It could be through IT, it could be through your marketing department. It could be an employee expensing a piece of software on their expense card. And when we find it, we normalize that data, we bring it in, we create an inventory of all the SaaS applications that that company has and is responsible for.

John Furrier

>> So, you have a data collection mechanism.

Ben Pippenger

>> Exactly.

John Furrier

>> And then you run machine learning on it. And then what's the input? Is AI involved there? Is this more of a search paradigm or is it more-

Ben Pippenger

>> It's an ML model.

John Furrier

>> Okay.

Ben Pippenger

>> So, it's an ML model that, again, has a basis of $90 billion in spend data that it uses to then formulate and look at individual payment lines to identify applications that are being purchased.

John Furrier

>> And what is hot use cases for you guys right now?

Ben Pippenger

>> Yeah, I mean, there's a lot of them. So, that's our first step is we just tell you everything you have and people are typically shocked what we find. It's usually two to three times the number of apps and the amount of spend that they have. An interesting thing, it's usually about the amount of cloud spend. So, if you look at their total SaaS spend that they have, it's usually equivalent to what they're spending on the cloud. So, it's a significant amount of spend.

John Furrier

>> So, you mean like people who subscribed on the credit card, they're not using the app. There's no way to cancel it.

Ben Pippenger

>> Well, it's a credit card, it's stuff going through POs. It's everything from your Salesforce agreement to somebody buying Asana on a credit card and everything in between, right? So, we uncover all of it. And then we, as I said, inventory it, we keep your contract about that so you know your start and your end date and what you purchased. We also pump in usage data for all those apps as well. So, you can see here's how many licenses we have, here's how many seats we provisioned and this is what our usage looks like.

Paul Nashawaty

>> So, you've been around for a bit and when we look at what you've been doing, when you think about AI and the impact of what AI has been doing for organizations, you mentioned that you go out there and you kind of expose what spend is happening, which is important, right?

Ben Pippenger

>> Sure.

Paul Nashawaty

>> Now that we see lines of businesses kind of having more liberties, like years ago we'd have shadow IT, right? Now we have shadow AI, right? And lines of businesses are going out there and spending and doing things without the organizations knowing. So, are you seeing a huge uptick for one? And the second question is with that uptick or if you are seeing an uptick, what are you doing for organizations? Are you just kind of giving them advice and saying, "Hey, this is what it is." Or are you recommending some guardrails and stuff?

Ben Pippenger

>> Yeah, we're definitely seeing an uptick. So, we have a report every year called the SaaS Management Index came out in January of this year and there's two stats I'll reference from that. One is in the enterprise segment we saw gen AI spend go up 400% year-over-year. So, from 2025 to 2026. We also saw a ton of shadow AI and for the first time the number one expense application, can you guess what it was?

John Furrier

>> OpenAI.

Ben Pippenger

>> It was ChatGPT.

John Furrier

>> ChatGPT, yeah.

Ben Pippenger

>> Yeah, ChatGPT. So, that was the number one expense app that we found on employees through their expense cards. So, we're definitely seeing it. It's real, it's happening both from known spend, but also through shadow spend as well.

John Furrier

>> One of the trends here is I try to map cost to value.

Ben Pippenger

>> Yeah.

John Furrier

>> You guys do any work there because a lot of people get more productive with ChatGPT, but it may not be the kind of productivity. We're seeing some of those. So, how are you guys doing the FinOps thing there?

Ben Pippenger

>> Yeah, it's a great question. I think it's the million-dollar question. I think both on the application side and what I'll call the infrastructure side to be able to really say, "Hey, we're spending this dollar on AI. What are we getting for it?" A lot of the big labs are just now providing access to the data that you need to be able to get to that level of detail. For instance, Anthropic just brought out the ability to see user level detail for Claude. So now we can see a user is spending this many tokens on this app. Was it Cowork? Was it Claude Code or was it through the Claude chat interface? And they also provide some level of metrics around how many PRs were submitted as a result of that engineering person using Claude Code. So, there is some of that coming out. I think the more forward progressive thinking SaaS providers that are starting to baking consumption pricing into their pricing models, there's a couple of different ways, flavors of it, but the one I like the most is outcome based. So, when they put outcome-based pricing, they're saying the value is, let's say a lead created or a case closed, we want to track that for them. We want to make sure that the buyer of that application knows that, "Hey, for every lead I close, it's going to cost me 10 cents." In that case it's pretty straightforward, but that's not always the case.

John Furrier

>> So, what's your take on the SaaS apocalypse because that was a big rage. Of course, I was negative on it, but I mean, it is just narrative that's come out from the Anthropic theme, but that's really not really the right way to look at it because you mentioned there is a shift to pricing per seat to usage.

Ben Pippenger

>> Yep.

John Furrier

>> How does that factor into your business?

Ben Pippenger

>> Yeah. So, I'll address that in two ways. I think the first one on the SaaS apocalypse, I think it's overblown. I mean, I do think that there's some sort of easy to build SaaS apps that will get replaced, but for the most part, you think about what we're doing or what a large Salesforce is doing. I mean, it's a CRM, it's deep in technical knowledge, has lots of capabilities. Someone's not going to vibe code that on the weekend and they'd have to maintain it. So, I think it's a little bit overblown. But I think on your second question on the consumption side, so we sort of think of it as a spectrum. FinOps talks a lot about the ITAM and FinOps convergence of those two disciplines coming together. I think on the ITAM side, you're really looking at, they're helping you track specifically on the software asset management side, the products and services you're using to run your business. So, what apps are you buying that you're giving to employees to get their job done? On the FinOps side, it's the services you're using to build and run a product, right? So, it's the infrastructure layer, right? Now those worlds are coming together and the convergence zone in the middle is you now have consumption-based SaaS, which for a SAM team to manage consumption-based SaaS, they need skills that FinOps practitioners have. They need to know variable data. They need to get real-time data. That's stuff they haven't dealt with before, but FinOps practitioners have mastered, right? And then on the FinOps side, you have the platform as a service vendors, the Datadogs, the OpenAI API, the Anthropic's API, which SAM teams are also going to want to get visibility into because they're going to be responsible for those contracts. So, you have this like convergence in the middle where those teams need to be collaborating, working together, sharing best practices in order to be really successful.

John Furrier

>> How's that work in organizations? Because that's intersecting disciplines, a lot of cross-pollination, collaborations needed. What's your observation on how well it's going? I mean, it's change management at the end of the day.

Ben Pippenger

>> Yeah. I would say we see a spectrum. We see everything from, we now have FinOps buyers of our platform, which we hadn't before. I'd say probably two years ago when the foundation added SaaS scopes in and we started to see FinOps teams starting to take over the management of SaaS. So, that's like where they've come together under sort of one persona. In the middle, you have where you have common leadership. You may have one person that's sitting over software asset management and FinOps. You may have where they're separate, but they're still collaborating. They're sharing best practices, how you do this and then you have others where they're siloed. And the siloed is not going to work. They're going to have to figure out where they sit in the spectrum, what's going to make the most sense for their organization in order to be really successful.

Paul Nashawaty

>> So, understanding all of this, this makes a lot of sense on exposing or just having the visibility into where the money's going.

Ben Pippenger

>> Yeah.

Paul Nashawaty

>> Okay, that makes a lot of sense to me. Organizations need to be focused on where they're spending because it's the ROI piece, but not every dollar spent has equal value. So, meaning if you're innovating and you're trying new things, it doesn't have the same value as a production workload that's driving towards revenue. So, how do you kind of balance that or do you balance that with regards to reporting? Like a dollar, token spent on innovation to try something new versus token spent for production workloads that's directly related to money.

Ben Pippenger

>> Yeah. Yeah, I think it's a little different for SaaS because when we think about AI, it's the AI that's in your SaaS application. So, it's your vendors as they're adding in AI capabilities that they're then, as a result, charging you for, because they got to cover their margins. They're also hopefully providing some form of additional value that the buyers want to pay for, right?

Paul Nashawaty

>> Yeah.

Ben Pippenger

>> So, there's still going to be experimentation there, right? If an app creates some chat assistant that you can use to get your work done, I'm going to try it out and use it. And that could result in me burning some form of unit or whatever it is that they're charging me for. I would say right now the telemetry probably isn't there to know if somebody in a SaaS app, are they doing that experimentation or did that result in savings of time, a unit of work that they were trying to accomplish?

Paul Nashawaty

>> Yeah, but this is, I think, where things are moving towards SaaS or not. The equivalence of AI adoption is like what was happening in the cloud, right? Cloud adoption, the difference is everyone is using AI, right? Not just the tech teams, not just the IT teams. And then when you're looking at SaaS, now people have access to it and they're using it. So, the model is going to have to pivot and change in order to understand the telemetry of what's happening, to your words, the telemetry of what's happening really needs to be exposed.

Ben Pippenger

>> Yeah. Yeah. I totally agree with you. And I think a good example of that is like if you just use Claude as the example, right? I think it's the perfect example of like the convergence too, because Claude is a SaaS app. The actual thing on your desktop, if you use a desktop, that's a SaaS application, it's a subscription you pay for, you get a seat actually and you get tokens that you can burn through with your seat, right? On the FinOps side, they're going to care about engineers using Claude Code. That's what they're going to be focused on and understanding how they're using that and then do their job to distribute that cost out accordingly. But what about the marketer that's using Cowork to build a marketing campaign?

Paul Nashawaty

>> Yeah. Yeah.

Ben Pippenger

>> I mean, that's just as important, right? Because they're going to be burning tokens in the same way that an engineer would. And are they using the right model? Are they doing it responsibly? Did they actually create what they needed to create? And I think all those things are going to be really important and we'll have to really figure out how we attribute value to-

John Furrier

>> Has there been a trend where certain AI native apps are starting to eat into renewals because you guys do a lot of renewal management.

Ben Pippenger

>> Sure.

John Furrier

>> We're talking about software estates and tech estates.

Ben Pippenger

>> Yeah.

John Furrier

>> Managing licensing comes up, that's on the other adjacent sectors to FinOps, but renewals coming, I might not want to renew that.

Ben Pippenger

>> Yeah.

John Furrier

>> How do you see that going? Who's winning? Who's losing?

Ben Pippenger

>> Yeah.

John Furrier

>> What's the winners look like?

Ben Pippenger

>> The interesting thing, renewals used to be like, we call it the moment that matter. I mean, it still is important for what we do for seat-based licensing because otherwise you couldn't change your contract. You were sort of stuck with, I bought 1,000 seats, I'm stuck with that 1,000 seats until my renewal and that point in time I can make some sort of change. Now true-ups and things like that come into play, which can affect some of that, but there's simply not true-downs. It's usually you're going to pay for, if you go over what your allotment is. Now that's changing with consumption pricing as well, because you're no longer tied to just that renewal and that moment that matters, you could blow your budget in a single day. I mean, we see it like a really good example of just like the non-AI version of that. It's like DocuSign with envelopes. You can buy envelopes and you can burn through all those envelopes really quickly and then be stuck paying one and a half times what you agree to in your contract. The same thing exists for AI driven features as well where there's some sort of consumption pricing model for it.

John Furrier

>> I'm just curious, Ben, have you've seen any changes on products? Because one of the things that SaaS apocalypse we had a lot of debate around, which we agree with you, by the way, is that the products have to evolve because my answer to that was bad software always dies, but products are getting more comprehensive, more multi-capabilities. Are you seeing some of the customers look at their product portfolio and blending in either adjacencies because sometimes a standalone SaaS product that you're paying for like, "Okay, I can get that over here." Is that in the analysis?

Ben Pippenger

>> Yeah, for sure. So, we've got a big outcome that we drive forward and it's all around app rationalization. And so, app rationalization, so a couple of things. It could be you're buying the same app multiple places in your business, like consolidate your contract, but it could also be, "Hey, we have two apps that are very similar that have similar capabilities." And we surface all that information so that you can then say, "Hey, why do we have 15 project management tools? We don't need 15, we may need five, we don't need 15." And then put a process in place to end those agreements and consolidate.

Paul Nashawaty

>> Yeah, that makes sense. I mean, in our 2025 research, we find that 75% of respondents indicate they're using six to 15 different tools for management. And so to your point, right? And they don't want that. 54% of those respondents indicate they're in favor of full stacks look without having all those tools. So, you're spot on. I think that's really the right direction with the audience, where the market is shifting.

Ben Pippenger

>> Yeah. It's harder to do than what it sounds though, right? When I say you have 15 project managements or your stats, yeah, we got to fix it, but you think about what it takes to then fix that.

Paul Nashawaty

>> Right, right.

Ben Pippenger

>> Right. You got change management, you got to move the users around, you got to align it to your contract term, you got to get procurement involved, the whole bunch of stuff.

Paul Nashawaty

>> And there's always reasons why there's 15 different tools.

Ben Pippenger

>> For sure. Yeah.

Paul Nashawaty

>> Yes.

John Furrier

>> It's hard as hell to come out of them, but not just contracts. That's not my problem right now.

Ben Pippenger

>> I mean, you really need executive top-down directive to say we're fixing this problem and you guys have to figure this out and come together-

John Furrier

>> Yeah. I think rationalization on the portfolio, optimization on cost, what drives productivity and revenue, these are all kind of coming together here at FinOps and the Tokenomics Foundation, what's your take on that? That's pretty cool.

Ben Pippenger

>> I think it's great. I mean, I think it's very smart of the FinOps Foundation to sort of carve that off and separate it because it is different and there's a different level of depth to it than what you have sort of in your normal cloud FinOps practice. Now there's definitely crossover. There's some practices that are going to be the same, but I think having a dedicated group of really smart, bright people thinking out ahead of what is needed is going to be really important. I mean, I think everyone here is hungry for that like help me understand what I need to do. And I think it was really smart of them to separate it out and have a different group -

John Furrier

>> Ben, final question for you. Advice to people who are seeing all the chaos, they know they got to lean in because there's a competitive advantage for doing it if you're a company. What's your advice for people who are trying to get their arms around this market? Obviously costs are flying everywhere. It's a top conversation with tokenomics. What advice do you have?

Ben Pippenger

>> I mean, I think in general, it can be scary. I think especially the tokenomics can be scary because it's so new and it's changing so fast, but you have to get started. I think that's the process is like get started, figure out where you can make an impact and start there. And that's the same for SaaS too. I mean, when we come in and do discovery and we find hundreds or potentially thousands of apps, it's overwhelming and people are like, "I don't know what to do." It's like, "Well, let's help you prioritize where your biggest impact can be made and start there. Get some wins, get them under your belt, socialize them across your business and then build the program up from there."

John Furrier

>> And business good?

Ben Pippenger

>> Business is great. Yeah. We celebrating our 10-year anniversary actually this year based in Indianapolis, which is the hotbed of Midwest tech, I guess.

John Furrier

>> Nice. Nice.

Ben Pippenger

>> So, it's great. Yeah, we're-

John Furrier

>> Awesome....

Ben Pippenger

>> enjoy it.

John Furrier

>> I've been on my bucket list. I always go to a game.

Ben Pippenger

>> Yeah.

John Furrier

>> So, -

Ben Pippenger

>> Yeah, come to the race actually. Come to the 500. That's the -

John Furrier

>> All right. . I'll send you LinkedIn. Ben, thanks so much.

Ben Pippenger

>> Yeah. Thank you.

John Furrier

>> I'm John Furrier, Paul Nashawaty here on the ground floor here at FinOps. The market's changing. The demand curve for tokens, the demand curve for AI certainly is disrupting the innovation curve and that's just rationalizing what you got, understand the cost of the new stuff, putting it all together. We're doing our part to put it together here. Thanks for watching.

Ben Pippenger, Zylo

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John Furrier

>> Welcome back over to theCUBE's live stream here in San Diego at FinOps X 2026. We're unpacking FinOps and its impact to the cost side, of course. The revenue being generated, the value being created with AI is off the charts. Our guest is Ben Pippenger, co-founder at Zylo here on theCUBE. Great to see you from Indianapolis.

Ben Pippenger

>> Yes, Indianapolis. That's right. Thank you.

John Furrier

>> All right. Where all the action is , I'm a Patriots fan, just going to say.

Ben Pippenger

>> Oh, I didn't know that. I think I wouldn't have been here if I knew.

Paul Nashawaty

>> Yeah, two of them.

Ben Pippenger

>> Oh.

John Furrier

>> Thanks for coming on. Appreciate it. We had to get sports in there somehow, but they'll have a comeback. We'll see how they do. Although Peyton Manning did a good round last round, Pro-Am. You guys are doing something different with FinOps in the cloud and SaaS. Explain what you guys do real quick in this context because it's a little bit of different approach.

Ben Pippenger

>> It is a different approach. So, we're a SaaS management platform. We really serve the enterprise and help them do a handful of things around the SaaS applications that they're buying. First and foremost, it's discovering all of them. So, we've got a machine learning based model that processes through payment data. It sits on top of about a $90 billion collection of SaaS AI and cloud spend to identify all the different SaaS applications that an organization's buying wherever it happens in the company. It could be through IT, it could be through your marketing department. It could be an employee expensing a piece of software on their expense card. And when we find it, we normalize that data, we bring it in, we create an inventory of all the SaaS applications that that company has and is responsible for.

John Furrier

>> So, you have a data collection mechanism.

Ben Pippenger

>> Exactly.

John Furrier

>> And then you run machine learning on it. And then what's the input? Is AI involved there? Is this more of a search paradigm or is it more-

Ben Pippenger

>> It's an ML model.

John Furrier

>> Okay.

Ben Pippenger

>> So, it's an ML model that, again, has a basis of $90 billion in spend data that it uses to then formulate and look at individual payment lines to identify applications that are being purchased.

John Furrier

>> And what is hot use cases for you guys right now?

Ben Pippenger

>> Yeah, I mean, there's a lot of them. So, that's our first step is we just tell you everything you have and people are typically shocked what we find. It's usually two to three times the number of apps and the amount of spend that they have. An interesting thing, it's usually about the amount of cloud spend. So, if you look at their total SaaS spend that they have, it's usually equivalent to what they're spending on the cloud. So, it's a significant amount of spend.

John Furrier

>> So, you mean like people who subscribed on the credit card, they're not using the app. There's no way to cancel it.

Ben Pippenger

>> Well, it's a credit card, it's stuff going through POs. It's everything from your Salesforce agreement to somebody buying Asana on a credit card and everything in between, right? So, we uncover all of it. And then we, as I said, inventory it, we keep your contract about that so you know your start and your end date and what you purchased. We also pump in usage data for all those apps as well. So, you can see here's how many licenses we have, here's how many seats we provisioned and this is what our usage looks like.

Paul Nashawaty

>> So, you've been around for a bit and when we look at what you've been doing, when you think about AI and the impact of what AI has been doing for organizations, you mentioned that you go out there and you kind of expose what spend is happening, which is important, right?

Ben Pippenger

>> Sure.

Paul Nashawaty

>> Now that we see lines of businesses kind of having more liberties, like years ago we'd have shadow IT, right? Now we have shadow AI, right? And lines of businesses are going out there and spending and doing things without the organizations knowing. So, are you seeing a huge uptick for one? And the second question is with that uptick or if you are seeing an uptick, what are you doing for organizations? Are you just kind of giving them advice and saying, "Hey, this is what it is." Or are you recommending some guardrails and stuff?

Ben Pippenger

>> Yeah, we're definitely seeing an uptick. So, we have a report every year called the SaaS Management Index came out in January of this year and there's two stats I'll reference from that. One is in the enterprise segment we saw gen AI spend go up 400% year-over-year. So, from 2025 to 2026. We also saw a ton of shadow AI and for the first time the number one expense application, can you guess what it was?

John Furrier

>> OpenAI.

Ben Pippenger

>> It was ChatGPT.

John Furrier

>> ChatGPT, yeah.

Ben Pippenger

>> Yeah, ChatGPT. So, that was the number one expense app that we found on employees through their expense cards. So, we're definitely seeing it. It's real, it's happening both from known spend, but also through shadow spend as well.

John Furrier

>> One of the trends here is I try to map cost to value.

Ben Pippenger

>> Yeah.

John Furrier

>> You guys do any work there because a lot of people get more productive with ChatGPT, but it may not be the kind of productivity. We're seeing some of those. So, how are you guys doing the FinOps thing there?

Ben Pippenger

>> Yeah, it's a great question. I think it's the million-dollar question. I think both on the application side and what I'll call the infrastructure side to be able to really say, "Hey, we're spending this dollar on AI. What are we getting for it?" A lot of the big labs are just now providing access to the data that you need to be able to get to that level of detail. For instance, Anthropic just brought out the ability to see user level detail for Claude. So now we can see a user is spending this many tokens on this app. Was it Cowork? Was it Claude Code or was it through the Claude chat interface? And they also provide some level of metrics around how many PRs were submitted as a result of that engineering person using Claude Code. So, there is some of that coming out. I think the more forward progressive thinking SaaS providers that are starting to baking consumption pricing into their pricing models, there's a couple of different ways, flavors of it, but the one I like the most is outcome based. So, when they put outcome-based pricing, they're saying the value is, let's say a lead created or a case closed, we want to track that for them. We want to make sure that the buyer of that application knows that, "Hey, for every lead I close, it's going to cost me 10 cents." In that case it's pretty straightforward, but that's not always the case.

John Furrier

>> So, what's your take on the SaaS apocalypse because that was a big rage. Of course, I was negative on it, but I mean, it is just narrative that's come out from the Anthropic theme, but that's really not really the right way to look at it because you mentioned there is a shift to pricing per seat to usage.

Ben Pippenger

>> Yep.

John Furrier

>> How does that factor into your business?

Ben Pippenger

>> Yeah. So, I'll address that in two ways. I think the first one on the SaaS apocalypse, I think it's overblown. I mean, I do think that there's some sort of easy to build SaaS apps that will get replaced, but for the most part, you think about what we're doing or what a large Salesforce is doing. I mean, it's a CRM, it's deep in technical knowledge, has lots of capabilities. Someone's not going to vibe code that on the weekend and they'd have to maintain it. So, I think it's a little bit overblown. But I think on your second question on the consumption side, so we sort of think of it as a spectrum. FinOps talks a lot about the ITAM and FinOps convergence of those two disciplines coming together. I think on the ITAM side, you're really looking at, they're helping you track specifically on the software asset management side, the products and services you're using to run your business. So, what apps are you buying that you're giving to employees to get their job done? On the FinOps side, it's the services you're using to build and run a product, right? So, it's the infrastructure layer, right? Now those worlds are coming together and the convergence zone in the middle is you now have consumption-based SaaS, which for a SAM team to manage consumption-based SaaS, they need skills that FinOps practitioners have. They need to know variable data. They need to get real-time data. That's stuff they haven't dealt with before, but FinOps practitioners have mastered, right? And then on the FinOps side, you have the platform as a service vendors, the Datadogs, the OpenAI API, the Anthropic's API, which SAM teams are also going to want to get visibility into because they're going to be responsible for those contracts. So, you have this like convergence in the middle where those teams need to be collaborating, working together, sharing best practices in order to be really successful.

John Furrier

>> How's that work in organizations? Because that's intersecting disciplines, a lot of cross-pollination, collaborations needed. What's your observation on how well it's going? I mean, it's change management at the end of the day.

Ben Pippenger

>> Yeah. I would say we see a spectrum. We see everything from, we now have FinOps buyers of our platform, which we hadn't before. I'd say probably two years ago when the foundation added SaaS scopes in and we started to see FinOps teams starting to take over the management of SaaS. So, that's like where they've come together under sort of one persona. In the middle, you have where you have common leadership. You may have one person that's sitting over software asset management and FinOps. You may have where they're separate, but they're still collaborating. They're sharing best practices, how you do this and then you have others where they're siloed. And the siloed is not going to work. They're going to have to figure out where they sit in the spectrum, what's going to make the most sense for their organization in order to be really successful.

Paul Nashawaty

>> So, understanding all of this, this makes a lot of sense on exposing or just having the visibility into where the money's going.

Ben Pippenger

>> Yeah.

Paul Nashawaty

>> Okay, that makes a lot of sense to me. Organizations need to be focused on where they're spending because it's the ROI piece, but not every dollar spent has equal value. So, meaning if you're innovating and you're trying new things, it doesn't have the same value as a production workload that's driving towards revenue. So, how do you kind of balance that or do you balance that with regards to reporting? Like a dollar, token spent on innovation to try something new versus token spent for production workloads that's directly related to money.

Ben Pippenger

>> Yeah. Yeah, I think it's a little different for SaaS because when we think about AI, it's the AI that's in your SaaS application. So, it's your vendors as they're adding in AI capabilities that they're then, as a result, charging you for, because they got to cover their margins. They're also hopefully providing some form of additional value that the buyers want to pay for, right?

Paul Nashawaty

>> Yeah.

Ben Pippenger

>> So, there's still going to be experimentation there, right? If an app creates some chat assistant that you can use to get your work done, I'm going to try it out and use it. And that could result in me burning some form of unit or whatever it is that they're charging me for. I would say right now the telemetry probably isn't there to know if somebody in a SaaS app, are they doing that experimentation or did that result in savings of time, a unit of work that they were trying to accomplish?

Paul Nashawaty

>> Yeah, but this is, I think, where things are moving towards SaaS or not. The equivalence of AI adoption is like what was happening in the cloud, right? Cloud adoption, the difference is everyone is using AI, right? Not just the tech teams, not just the IT teams. And then when you're looking at SaaS, now people have access to it and they're using it. So, the model is going to have to pivot and change in order to understand the telemetry of what's happening, to your words, the telemetry of what's happening really needs to be exposed.

Ben Pippenger

>> Yeah. Yeah. I totally agree with you. And I think a good example of that is like if you just use Claude as the example, right? I think it's the perfect example of like the convergence too, because Claude is a SaaS app. The actual thing on your desktop, if you use a desktop, that's a SaaS application, it's a subscription you pay for, you get a seat actually and you get tokens that you can burn through with your seat, right? On the FinOps side, they're going to care about engineers using Claude Code. That's what they're going to be focused on and understanding how they're using that and then do their job to distribute that cost out accordingly. But what about the marketer that's using Cowork to build a marketing campaign?

Paul Nashawaty

>> Yeah. Yeah.

Ben Pippenger

>> I mean, that's just as important, right? Because they're going to be burning tokens in the same way that an engineer would. And are they using the right model? Are they doing it responsibly? Did they actually create what they needed to create? And I think all those things are going to be really important and we'll have to really figure out how we attribute value to-

John Furrier

>> Has there been a trend where certain AI native apps are starting to eat into renewals because you guys do a lot of renewal management.

Ben Pippenger

>> Sure.

John Furrier

>> We're talking about software estates and tech estates.

Ben Pippenger

>> Yeah.

John Furrier

>> Managing licensing comes up, that's on the other adjacent sectors to FinOps, but renewals coming, I might not want to renew that.

Ben Pippenger

>> Yeah.

John Furrier

>> How do you see that going? Who's winning? Who's losing?

Ben Pippenger

>> Yeah.

John Furrier

>> What's the winners look like?

Ben Pippenger

>> The interesting thing, renewals used to be like, we call it the moment that matter. I mean, it still is important for what we do for seat-based licensing because otherwise you couldn't change your contract. You were sort of stuck with, I bought 1,000 seats, I'm stuck with that 1,000 seats until my renewal and that point in time I can make some sort of change. Now true-ups and things like that come into play, which can affect some of that, but there's simply not true-downs. It's usually you're going to pay for, if you go over what your allotment is. Now that's changing with consumption pricing as well, because you're no longer tied to just that renewal and that moment that matters, you could blow your budget in a single day. I mean, we see it like a really good example of just like the non-AI version of that. It's like DocuSign with envelopes. You can buy envelopes and you can burn through all those envelopes really quickly and then be stuck paying one and a half times what you agree to in your contract. The same thing exists for AI driven features as well where there's some sort of consumption pricing model for it.

John Furrier

>> I'm just curious, Ben, have you've seen any changes on products? Because one of the things that SaaS apocalypse we had a lot of debate around, which we agree with you, by the way, is that the products have to evolve because my answer to that was bad software always dies, but products are getting more comprehensive, more multi-capabilities. Are you seeing some of the customers look at their product portfolio and blending in either adjacencies because sometimes a standalone SaaS product that you're paying for like, "Okay, I can get that over here." Is that in the analysis?

Ben Pippenger

>> Yeah, for sure. So, we've got a big outcome that we drive forward and it's all around app rationalization. And so, app rationalization, so a couple of things. It could be you're buying the same app multiple places in your business, like consolidate your contract, but it could also be, "Hey, we have two apps that are very similar that have similar capabilities." And we surface all that information so that you can then say, "Hey, why do we have 15 project management tools? We don't need 15, we may need five, we don't need 15." And then put a process in place to end those agreements and consolidate.

Paul Nashawaty

>> Yeah, that makes sense. I mean, in our 2025 research, we find that 75% of respondents indicate they're using six to 15 different tools for management. And so to your point, right? And they don't want that. 54% of those respondents indicate they're in favor of full stacks look without having all those tools. So, you're spot on. I think that's really the right direction with the audience, where the market is shifting.

Ben Pippenger

>> Yeah. It's harder to do than what it sounds though, right? When I say you have 15 project managements or your stats, yeah, we got to fix it, but you think about what it takes to then fix that.

Paul Nashawaty

>> Right, right.

Ben Pippenger

>> Right. You got change management, you got to move the users around, you got to align it to your contract term, you got to get procurement involved, the whole bunch of stuff.

Paul Nashawaty

>> And there's always reasons why there's 15 different tools.

Ben Pippenger

>> For sure. Yeah.

Paul Nashawaty

>> Yes.

John Furrier

>> It's hard as hell to come out of them, but not just contracts. That's not my problem right now.

Ben Pippenger

>> I mean, you really need executive top-down directive to say we're fixing this problem and you guys have to figure this out and come together-

John Furrier

>> Yeah. I think rationalization on the portfolio, optimization on cost, what drives productivity and revenue, these are all kind of coming together here at FinOps and the Tokenomics Foundation, what's your take on that? That's pretty cool.

Ben Pippenger

>> I think it's great. I mean, I think it's very smart of the FinOps Foundation to sort of carve that off and separate it because it is different and there's a different level of depth to it than what you have sort of in your normal cloud FinOps practice. Now there's definitely crossover. There's some practices that are going to be the same, but I think having a dedicated group of really smart, bright people thinking out ahead of what is needed is going to be really important. I mean, I think everyone here is hungry for that like help me understand what I need to do. And I think it was really smart of them to separate it out and have a different group -

John Furrier

>> Ben, final question for you. Advice to people who are seeing all the chaos, they know they got to lean in because there's a competitive advantage for doing it if you're a company. What's your advice for people who are trying to get their arms around this market? Obviously costs are flying everywhere. It's a top conversation with tokenomics. What advice do you have?

Ben Pippenger

>> I mean, I think in general, it can be scary. I think especially the tokenomics can be scary because it's so new and it's changing so fast, but you have to get started. I think that's the process is like get started, figure out where you can make an impact and start there. And that's the same for SaaS too. I mean, when we come in and do discovery and we find hundreds or potentially thousands of apps, it's overwhelming and people are like, "I don't know what to do." It's like, "Well, let's help you prioritize where your biggest impact can be made and start there. Get some wins, get them under your belt, socialize them across your business and then build the program up from there."

John Furrier

>> And business good?

Ben Pippenger

>> Business is great. Yeah. We celebrating our 10-year anniversary actually this year based in Indianapolis, which is the hotbed of Midwest tech, I guess.

John Furrier

>> Nice. Nice.

Ben Pippenger

>> So, it's great. Yeah, we're-

John Furrier

>> Awesome....

Ben Pippenger

>> enjoy it.

John Furrier

>> I've been on my bucket list. I always go to a game.

Ben Pippenger

>> Yeah.

John Furrier

>> So, -

Ben Pippenger

>> Yeah, come to the race actually. Come to the 500. That's the -

John Furrier

>> All right. . I'll send you LinkedIn. Ben, thanks so much.

Ben Pippenger

>> Yeah. Thank you.

John Furrier

>> I'm John Furrier, Paul Nashawaty here on the ground floor here at FinOps. The market's changing. The demand curve for tokens, the demand curve for AI certainly is disrupting the innovation curve and that's just rationalizing what you got, understand the cost of the new stuff, putting it all together. We're doing our part to put it together here. Thanks for watching.