Unlocking the Secrets of the Software M&A Market in 2026

0:00Greetings, everyone. I'm excited to welcome Jim Williams back on the podcast. Jim, I think this is maybe the fourth episode, so really looking forward to this update. Our last update was late last year, I think. Before we dive into some of these important questions for founders, tell us a little bit about yourself and GLC. Yeah. Hi, everyone. Jim Williams. I'm a managing director here at GLC Advisors. We are a national boutique investment bank. Got offices in New York, Denver, LA, and San Francisco. I help lead our technology investment banking group. We are primarily focused on sell-side M &A transactions.

0:31So think of that as growth equity, inventory recaps, full sales. And our passion is really helping founders and owner-operators through complex transactions. That is where we've spent 20 some odd years, depending on which one of us you're talking to. Ben has been gracious enough to invite me on to chat with him, and hopefully this remains relevant for you. And I'm certainly happy to answer any questions you have coming out of this. Yeah, definitely. And I know I hit you up maybe a month or two ago and you're like, hey, just wait a second, some interesting things on AI happening. So we'll get to the AI part at the end.

1:07But first, we're recording this early July, 2026. So tell us, what's the current state of the software M &A market? Is it what you expected when you started the year? Just give us a little rundown of how things are looking today. Yeah, that's a great question. No, it is not. And look, the last two years, I think coming into 25, it was similar to 26 in terms of there was a lot of optimism that it was going to be a blockbuster year. And that was from boutiques like GLC all the way to Goldman Sachs. Everyone thought it was going to be fantastic. And in some respects, it has. if you're doing some of the big work like Goldman, and then there's the rest of the market.

1:49And the reality is, no news to anyone here, is that the SaaSpocalypse headlines derailed things relatively early this year. And that is a continuing part of this market, and it's not going away. And just about every conversation we have been starts with AI in some capacity. Whether or not that question is informed by anything is not necessarily relevant, but it's in every deal we do, people are focused on the AI front. And what I would just say is the market has probably become the most selective I've ever seen. And AI has just frankly changed the lens through which companies are viewed. That being said, capital is available.

2:36Buyers are active. They're just much more discerning than a year ago. I was even more discerning than six months ago. But overall, and I said this last time too, there is absolutely a market for good software business. You don't have to be the shiniest AI penny to have an outcome in this market, but the landscape is changing and it's changing quickly. And frankly, we're all living this together in the M &A world. Yeah. Yeah. And that's interesting. And I like you bring that up again, because you've talked about it several times. is like, hey, if you still have a nice profile, financial profile, there's plenty of funding out there for you.

3:12And I remember our 2024 podcast where you said, boy, I think 2025 will start moving. We did our 2025 podcast. Nope, about the same. So midway through 2026, is the stream, the river flowing, or is it just still a slow trickle?

3:31It's a little hard to tell, honestly. The first quarter was interesting. It was actually pretty good. But that was before I think the full sort of force of the AI headlines got into the market. And the second quarter is down. And last month was way down, or I should say May was way down. Last month was down a little bit. So what we're seeing is the AI elements begin to just manifest themselves in the number of deals getting done, frankly, the number of deals launching that are looking like viable investment or acquisition opportunities. Diligence is protracting a little bit. The barbell that has existed for a couple of years, I think is exacerbated by AI.

4:21We've talked about this before where we had the really good businesses achieving really exceptional multiples. And then we had this skinny part in the middle, and then there were a bunch of deals getting done at lower multiples and AI has just made that the high end of the multiple barbell bigger where the folks who are AI forward or AI native, people are crawling over glass to get to those businesses. And I think there's probably in some instances unfairly the other end of the barbell, which is where good businesses with good metrics that have limited AI exposure are probably seeing depressed multiples.

4:55And I don't expect that to change. And if you're slower growth, or you don't have an AI story, or if you're in a part of the market where AI looks like it's going to be particularly disruptive or already is, all of those factors are compounded in your potential outcome in an M &A process. Yeah. Yeah. It makes sense. And we'll get to some of the metrics that investors are looking at, but let's talk valuations. If you're an equity owner, if you're a founder, we want to talk valuations and you still see, say, if you're a great rule of 40 and nice growth, both nice valuations, but then you mentioned the bar, but almost, okay, the rest of the group.

5:30And I don't know if that's been more compressed now as far as valuations, but what's it looking like today? The median, Ben, across all the deals is not, frankly, all that much different. And now I think the story is maybe not the median, which is still in that four-ish, four or five times range. It's really the dispersion of multiples on sort of either end of that, I think, and that is a product of a couple of different things. One is just coming out of the 2020 to 22 boom, and then a recalibration around those deals, because a lot of deals got underwritten in giant multiples with growth assumptions that never panned out.

6:11And now their private equity is owning those businesses through a totally different market. I think there is a rationalization of multiples to be paid, people looking at the exuberance of that time period and needing to step back and maybe return to some fundamentals. That's not a new story. Then the AI element is, I think, complicating a little bit of the viewpoint on what's a clean, clear story, especially on the platform side for private equity. I think on this GJUX side, it can get a little easier, but I think on the business. Yeah. And say that ballpark. So a founder listening and maybe thinking about selling sometime soon or near term, is there a ballpark?

6:55Let's throw out the outliers, the high and the lows, but is this a 3 to 10x football field we're looking at, 2 to 9? What's a ballpark range? So I would think of where most deals are happening right now, Ben, is somewhere in the 3 to 6 times range. Okay. And that's not all that much different in terms of multiples being paid. Now, what I do think is a little bit different is in order to get to those multiples, you need to be a better business. The bar just over the past few years, it just keeps going up, right? And that's product of what happened in the past. It's also product of what's going on right now.

7:37So while you think about the stratification of just like, what's the market multiple being paid, that isn't necessarily changing dramatically. But in order to achieve those multiples, the quality of the business kind of continues to need to be better. And then to get to the 10Xs, we can talk about this later, a whole bunch of factors have to align, you know, as you might expect. Yeah, that's been a recurring question in these episodes of just, sorry, what does it take that 10X, that high one? It's not 10x, but just, hey, we're shooting high here. So appreciate that. So generally say 3 to 6x. And like you said, not really changing too much.

8:13Now, a big impact on evaluations is error quality, revenue quality. Have the standards increased on that? Is it the same diligence as far as looking at what types of revenue streams that you have? And I assume all the retention calcs that they're going to do off of that. All that, look, the fundamentals for software businesses in what I'll somewhat oddly call the legacy SaaS model now. All of that remains the same. The bar, again, is higher. And I think part of that is what used to be best in class or, hey, we'll look at stuff and it has to be here. The specter of AI disruption has caused that bar to move because people are saying, if I invest at my kind of threshold level where it used to be, and there's any unintended or unexpected consequence of AI, all of a sudden I'm now owning a business that is probably going to be looking worse than where I came in.

9:13That could be a very hard problem to fix. And I don't have any room to make a mistake at that point. So everyone is building buffer into that equation, I guess I would say, Ben. But What has happened, certainly, maybe this is another question, is the impact of AI on the customer-facing productization side of AI, not the internal use of AI for your own efficiencies, coding and whatnot, has changed revenue models. And we've talked about this before in terms of usage and whatnot. And that is starting to become a diligence question. And I think the reality is it's the same as it has been in prior conversations, right?

9:58If you want to get credit for something that looks like recurring revenue, it has to look like and perform like recurring revenue. So if it's subscription, fine. If it's usage or outcome-based or a hybrid model or however you want to package your AI product, which I think everyone, frankly, is trying to figure that out. And we're all going through this together as well. if you want credit, it's got to look, it's got to look the right way and it's got to perform the right way. And I think people are getting more comfortable with that. They're going to have to get more comfortable with that because that's where a lot of models are going.

10:35Yeah. And last time I asked about usage revenue and basically it's probably the same where same valuation treatment, if you can demonstrate strong retention, predictable, repeatable customer behavior, just like subscription revenue. Now let's talk about EA revenue because we know, So yeah, pricing models are changing. We've seen these big tech companies change from subscription to hybrid platform plus usage to protect all that downside and all those power users eating their margin. You have to own. Is there more, and pricing is so hard, but then is there more diligence on the company's pricing model?

11:07And if they're offering AI, is it subscription? Is it usage? Yes. Is it agentic? What is it? So is there more time spent in that area, especially if they say, yep, I've got AI revenue? Definitely. Yeah, it's, and we could spend probably two hours on this topic alone, but I'll just say, yes, the questions are coming. The sophistication of the questions depends on who's asking, frankly, and the answers depend on the client and how far along they are in their own understanding of AI and the application of it within their own business. But what is becoming a bigger diligence topic is around exactly what you're suggesting.

11:47So everyone is saying they have AI. In most industries, you almost have to say you have AI in some capacity. And the real search for truth is what does that mean? Is it, are you coining a public model like Claude at some data and providing some insights like a glorified BI tool? That might be really useful. Well, customers might love that, but it's probably less intriguing than a truly agentic solution that's handling really complex workflows. And that's viewed as more sort of proprietary and sticky and a higher barrier to entry and all of those different things. So they're trying to separate genuine product innovation from repackaging, I guess I would say.

12:37Right. And they're also looking at fundamentally, does AI actually improve the economics of the platform? Does it improve the value to the customer? Or is this just something you're doing to say you have AI? And in our experience, most businesses are very early in their own understanding of how they're going to employ AI in a way that actually makes a difference to the customer. And they're very early in their understanding of the cost-related elements of AI. How are they going to manage it? How do they price it? How do they throttle it? All of those things, the ROI question, hard to answer. The question of value add of AI into the platform is hard to answer.

13:23So people are trying to figure out how does it scale? Is it going to improve retention? Is it going to make retention worse because we roll it out too early and it doesn't work? Is it too expensive? Do we need to move to a different model? All of these things are happening. And all of those questions are being asked by buyers to varying degrees. And part of that depends on how far you are in your own AI journey. If you're way down the road, there's probably more questions to ask, right? If you're just starting, there's less to dig in on. Yeah. Yeah. That makes sense. Yeah. So it sounds like a whole bunch of discussion around that.

14:00And last time I talked business model clarity for founders, like what kind of company are we presenting here? And is it software? Is it tech enabled? Or is it really a service business wrapped up as software? But now let's go from the AI lens. It seems like it's the same conversation if someone says, I'm AI native or AI infused. What does that really mean? So maybe it gets back to the previous question and then your comments there. Because before you really get to the meat of that question, there's kind of this surface layer. Look underneath the first cover and see what's really there, right? And that leads you down the path of what you're really looking at.

14:38Most of what we see, Ben, through AI-nated businesses or very AI-forward, people who got way out in front of it, honestly, few and far between relative to software businesses that are on some form of AI transformational journey, meaning they're infusing it in some capacity into their platform. I think it's most powerful if you're a system of record employing it, because then you've got the data mode, you've got the workflow mode, you've got, you probably have some compliance or regulatory mode, maybe you have a vertical mode. All of that is real time in terms of how it's rolling out. Yeah. Yeah, no, interesting.

15:18And so today, what defines a high quality software company today? What, and I'm sure there's the AI angle like you've talked about that's diving in, but what does high quality look like today? Look, the fundamentals are the fundamentals and they haven't really changed. And in 2021, the fundamental was growth and that it was like no other fundamentals. And that changed pretty quickly. So it's growth, it's retention, it's margins, it's customer quality, it's scalability. For many more businesses now, it's profitability or defined path to profitability. There are more businesses now that I think on the software side being valued off of EBITDA than any time in the past, certainly the past six or seven years, which is different for some businesses.

16:14And then, yes, AI has been injected. And the questions are really about how does AI impact some of the fundamentals? Does it improve customer retention? Does it not? Does it increase the switching cost? Does it not? Does it improve unit economics? Does it not? Is it really something differentiated or is it just a feature? Or is it a potential pitfall? That's the question we're getting too. It's not like every question you get on AI is, how far down the road are you? what are you doing? What are you doing? Sometimes the question is, should you really be exploring AI or are you actually injecting risk into a very happy customer base?

16:55And that can be a difficult question to answer for folks. Yeah. Yeah. Interesting. Yeah. And AI is maybe not always the right path or maybe not everything is meant for agentic, which is by belief, right? Depending on vertical or after. Yeah. And you mentioned EBITDA. I want to get back to that because we think when we value software companies a multiple of AR which is derived off of many different things and you mentioned EBITDA and of course when PE invests in software behind the scenes they're running their forecast models and those cash on cash returns just see all right at our exit are we going to get a nice return on this and maybe that conversation never is like an actual conversation with founder right they're keeping that math behind the scenes but is that more of a discussion like hey why are you running at these EBITDA levels or we need higher EBITDA Because before it was like, hey, we don't want to buy a company that's burning a ton of cash, burning the EBITDA, break-even or so, that's fine, and we'll scale it.

17:49But is there more focus on EBITDA now? There is, and certainly from the sponsor side. So the strategics may or may not care because they've got different levers they can pull. Burning a lot is still an issue for strategics. Unless there's something really compelling and strategic about it, which would be AI native platforms, it would be transformational in AI roadmapping. And you see those deals happening. Those are big deals, big multiples. But let's take the more kind of middle of the road standard business, which is probably the most applicable to the audience here, even as absolutely playing a bigger role.

18:28And on the sponsor side, look, this is not a new trend, but bigger deals in software generally trade on EBITDA multiples. When the sponsors, mid-market sponsors are thinking about selling to the up-market sponsors, EBITDA is a really serious consideration. It might be the most impactful valuation metric. And when the really big guys are selling to the really big guys, it's absolutely EBITDA, right? I just had a conversation with the Corp Denley who's talking about interesting on the AI front. I can pay X for an AI business because I've got 500 million of EBITDA. And if that AI deal turns my EBITDA multiple when I exit, so that's how he's thinking.

19:13By one turn, that's$500 million in enterprise value. Those are just to give you an example of just like the math that's going on in some people's head. AI has changed that a little bit, but EBITDA is very important to a lot of buyers. Not everyone, but a lot of buyers. Yeah. And of course, once you say the sponsor, the financial sponsor PE buys the company and usually they lever up with debt and we need some EBITDA cashflow to service that debt. So real quickly, interest rates right now, credit markets and how that's impacting things, because I know I would love to refinance my house right now, but the market creates continue to just kind of plug along.

19:52So, and that seems nothing new here, but does that, is that factoring in at all or just making things harder? Look, credit, credit is not, I guess I would say private credit in general remains supportive of software deals. I, some people have backed away, but the people who get it and understand it and have been in that space for a long time continue to be active. It's not financing that's holding back software M &A in general. Lenders are willing to finance good software businesses. Sponsors are willing to acquire them. I think the reality has been the equation has changed a little bit. So lower leverage, more focus on profit, less focus on pure ARR lending, especially as business models change.

20:39Lenders are risk-averse. The impact of AI is unknown, right? That creates maybe a little bit of speed wobbles on some deals, more stress put on LTE loan value metrics, and frankly, just more stress put on business quality. But it's still there. Like when we're doing a deal, I'm not worried about the leverage components of it. Okay. Okay. We have a restructuring group at GLC that is seeing all sorts of things related to the bigger deals that got done years ago and were over levered. Most of the stuff in the mid-market is very conservative around leverage. is our first time growth. And then that puts out financial engineering.

21:18Yeah. Yeah, I saw a chart somewhere tracking. These are the most at-risk deals. These are bigger software companies who have had a lot of debt. Yeah, there's lots of stuff out there around people opining about the deals that have happened in the not-too-distant past that were over-levered on assumptions that didn't pan out. Yeah, yeah. And let's talk due diligence. So say I called GLC six to nine months ago and, hey, I'm ready to sell. Let's get everything ready. and we go to market, how long can I expect, I guess, once we have that LOI where we do all the preliminary tire kicking, but once I go in with, say, PE firm A or strategic A, how long is diligence taking?

21:58And then what metrics are they really looking at? Yeah. So look, we generally tell people when you go into a deal, we're trying to get it done as quickly as possible. Obviously, everyone is, generally speaking. But most things happen between 30 and 60 days. We usually point people 45 to 60 as a, just get comfortable with that timeframe. It could absolutely go faster than that. We closed a deal on seven dates. Those things happen. And there was a time period where that was not terribly uncommon, right? This is a little bit of a different market and diligence is protracted mostly around just risk mitigation, which is exactly what you would expect.

22:39And the things that the things that get people caught up, Ben, and why we spend so much time up front. It's really quality of financials and quality of the data that supports all of your KPIs and being able to present that in a very clean, concise fashion that answers the questions quickly and directly in a way the buyer expects to see them answered. And that is sometimes an enormous amount of prep work. But where you don't want to get caught with that is post-LMI, right? Or even once you've kicked off, right? It's never good to be on your heels answering questions that you don't have answers to.

23:24And so we spend a ton of time trying to get in front of all of that. So we dictate the story, we control the message, we've got the leverage, right? All of that really matters. But all the stressors that you probably remember from when we did our deal, all that's the same. All the people still wean on the same things. Some things have changed on the legal side around IP and data privacy and AI is starting to play into that. But a lot of it remains the same. Yeah. So I assume same metrics players, gross revenue retention, that revenue, gross margin, even a concert concentration. So same set of metrics that buyers are going to diligence.

24:00And on the, so this question, I talked to a lot of founders and look at their metrics and maybe they want to raise, or maybe they want to exit. And I see a few numbers like, boy, I don't know, this could be a tough one. When you have those initial conversations with founders, and maybe they share some financials or some metrics, are there any metrics that stand out where you're like, maybe you should wait, maybe this is not the time to sell just based on some of the financial numbers that I'm seeing? Yeah. The answer is yes. And most of it is around really basic things, the fundamentals, right?

24:34The building blocks of the business that represent the health of the company, right? Outside of the softer factors. But the reality is, I think I said this last time too, you can go into a sale process and tell everyone your business is fantastic. And what's going to support it is the metrics and the data and the numbers. And that is where the proof lies. So if you say you've got a bunch of really happy customers and your retention is terrible, people get to the answer really quickly, right? The things that we really focus on because we know they are just frankly hurdles, Ben, is stuff like gross revenue retention and really being focused on better than 90%.

25:16And the more into the 90s, the better. And it does move the needle. And net, certainly above 100, hopefully closer to 110 plus. And again, like these bars, I would say, it used to be 90 and 100 for gross and net. And now I think that's probably inching closer to 90 to 93. And then net is probably 110 to 120. Right? And I say that, And maybe this is important to understand that those are median metrics for SaaS businesses. So if you're not at those numbers, it's not that you don't have a good business. It's just saying that's where the stress points are, is people are looking to those things to invest in the top quartile or the top 10 % of businesses.

26:05That's where they want to put their money, right? So that's that dynamic of sort of fundamentals, Ben, remains very much the same. Yeah. And before we talk 10X exits and just shooting for high valuation, it seems like in my client based segmentation is coming up a lot. If you have, and this is not like we have 200 enterprise customers, they may all look the same, but like 10 ,000 users, 100 ,000 users getting up into those ranges, or maybe you have, you know, a thousand enterprise customers. Is there going to be an expectation when you create that customer cube, the MR schedule, MR waterfall, that stuff.

26:38And I give, say, here's my MR schedule for 10 ,000 customers. Is there that expectation going to be, okay, I need segments of that, termographics, pricing models, et cetera? So what are the expectations around when that could actually hurt you as a founder coming forward with your data where you have not segmented your customer base? Yeah, no, that's a great point. And yes, that is absolutely part of diligence is, especially if there is a sponsor involved, your data is going to be cut up a million different ways. some of which will be relevant to your business, some of which will just be data cuts.

27:14But getting on top of that early and thinking through your own customer base is very helpful. And frankly, having an advisor to wear that hat in advance of a process is helpful too. Look, when we think about customer cuts, we can get very granular in terms of it's by product, by customer size, by geography, by end market, all of these things. And then you begin to stratify even within those buckets, right? And people begin to tease out where you've got a hole in the bucket, right? And as an easy example, we have customers that have a long tail of SMB, right? Usually what you'll find if you even do some basic cuts is that the majority of the churn from a logo perspective is the SMB customers.

28:01It might not be terribly impactful on your revenue piece, but you've got to answer these questions. Or if you're a business that is partnering with a system of record or something like that. Like what you can certainly, especially in today's environment, what you can certainly expect is people are going to run all sorts of retention based on what type of system of record you're connected to. So if you're in the government space, which you know, if you are connected to Tyler or Accela and Central Square or Civic Plus or however you want to think about it, and your retention characteristics are totally different by system of record, that's going to be a deep area of due diligence, right?

28:39And frankly, you better have enhanced as to why, right? And so if you think about where that winding road could lead you as you're running your business, spending a lot of time understanding your customer base and how to segment it is very important because it eventually gets to you. And sometimes it starts with, Ben, what is your ICP? Yeah. And then, because this is what we sometimes see is people will say, here's my retention. You got that looks pretty good. Then I get a full data set and it turns out that retention was one segment of customers. And then there's a whole nother segment of customers that doesn't look like that.

29:20And it's not better. It's worse. Right. And then the ICP question becomes really important. You go, is the really good stuff your ICP? Or is that just a group of customers And really, you're still selling a lot to this group that doesn't retain that well. Right? That's a question you're going to get. And that's something that you can position around. But look, savvy buyers know you're buying the whole business. And you got to be mindful of the messaging around, don't look over here, because that can lead to some odd questions. Don't look over there. What value should I ascribe to the revenue that I'm not supposed to pay attention to the retention metrics on, right?

30:02You just got to think about that stuff and you got to get on it and you got to have a story. You got to be straightforward about it. The business is the business. Yeah. So yes, it gets very detailed on segmentation. Yeah, definitely. Yeah. Okay. Yeah, that makes sense and what I'd expect. So a couple more questions here and then we'll have some Hatsy questions then wrap up, but we'll talk, okay, 10X, what's shooting for high and then let's get into the little AI strategy, AMO. But so if we're a founder, go to market and we want to shoot high, right? we think we've got a great company. We want that nice 10X or whatever.

30:32Maybe it's a double-digit valuation. What does that financial profile look like today? Yeah. Some of it's the same. The scale, I think, continues to creep up. It used to be eight of ARR, 15. I think it's more in the 15-ish range now. And look, a lot of this depends on the second piece, which is growth. You just have to be grown. And there are a couple of reasons for that, some of which are obvious. But if you think about the relative value of a business that's growing now for a strategic acquirer, all you need to go do is look at the growth rates of public SaaS businesses. At one point in time, then we had a whole bucket of 80 or 90 SaaS businesses where the median growth rate was like north of 25%.

31:19Now the average growth rate of the median growth rate is 9 % or 10%. So the value of you growing at 40 % or 50%, 30 % or 100%, however you want to look at it, that can be really valuable to someone. And your scale is obviously going to play into that. So I usually think of certainly double digit ARR, well, in north of 40%, good gross margin, which I would think of as blended north of 80 would be great and profitable, or at least break even with a path to profitability, like all of those things need to come into play. And now there's a lot more stress on things like, what is your AI moat? Are you employing AI internally to save money, externally to sell the customers?

32:07All of that is coming to a forefront and has been here for a while now. And that will continue. I think, honestly, in order to start getting to the 10 times plus sorts of deals, you have to have an AI story. And it can't be thin, tight, kind of wrappery type stuff where someone goes, yeah, but anyone can do that if they have the data. What's so different about that? That story, I think, needs to be refined. And it's not, we think we've got something really cool on the AI front. There's got to be some proof in how it's being used. Is it adding efficiency? Is it better functionality? Is the adoption where it needs to be?

32:48Do you have a pricing model that works? Do you have control of your cost? All of that's going to play into it, right? Certainly. That being said, before you ask another question, AI by itself doesn't justify a premium valuation. The business has to perform, right? People probably just need to hear that is it is, even in this conversation, it's AI in some capacity. Right. Yeah. The bedrock still matters. Yeah. I'm glad you brought that up because just if you claim, and maybe you were founded two years ago and you're AI and AI native through and through, but it seems like it's still going to come back to business fundamentals.

33:29Like you said, growth and retention and margins, right? Just because you're AI doesn't mean it's going to be just an automatic great valuation. Absolutely. Which leads us to the next one. And I had a PE firm on a couple months ago. And of course, the AI question, it seemed like they had developed proprietary questions. They developed their checklist for the AI audit on Target. And so what are you seeing? We talked a little bit about digging into revenue streams and pricing models and all that stuff. But are you seeing that they have their AI checklist that they're walking through just to figure out where this company stands?

34:08I think I would tell you, Ben, the reality of an AI checklist strategy is probably very, and not a lot of people have it in a way that is terribly refined. So I think my answer to that question, is there foundationally that trend building where people are trying to frame the aspects of AI where they think that they can identify differentiation or reduced risk. And on the risk side, it's trying to not be beholden to one model, trying to get away from the really expensive inference cost and stuff like that. Are you being savvy? The simple ones are like, are you being savvy about what model you're using?

34:57Not everyone needs the latest, greatest, most expensive GPT or Claude or whatever, right? There are plenty of models out there that are older models or models you can bring in-house, open-weight models, things like that, where you can get control of the cost. I think those things, Ben, are getting onto people's help. Yeah. How much power do you need, I think, is one, right? Literally, how much compute power and sophistication in your model do you need? And how are you addressing that? Because ultimately it gets to cost and there is a mix of, I think, sophistication and deliverability of a solution and cost associated with whatever model you're going to use.

35:43And you're probably talking to tons of people about how are we going to figure that out, right? And what is the right model. And it's hard to know that until I think you start getting some scale and seeing how people are really going to use it. Right. And to your point, there's a stratification of power users and people who use it less. How do you manage that? How do you have this ability into it until it's up and running and going? Hard to predict, right? Yeah. Yeah. Incremental cost of a subscription SaaS customer is not zero, but close. That might not be the case with your AI solution. I think those are where the checklists are starting to come out.

36:26That and trying to get to the bottom of what are you really doing? And is it really differentiated? And is it really going to move for the customer? Or do we have a glorified BI tool? Which by the way, could be really useful. But again, I think the really powerful stuff begins to lean more on the agentic side of things, truly agentic. And I think there's a lot of stuff that gets partially there and people are moving towards more sophisticated agentic offerings where you don't need a human involved at any point. A directive is given and it completes the task and it might have all sorts of different workflows that it addressed.

37:09And then you didn't have to do anything. Manifested itself without human beings, right? That's part of diligence for sure. One more thing on say gross margins with AI, a lot of debate on where AI gross margin initially is like these are going to be 40 to 50%. And there was a lot of shade thrown on SAS metrics. Yeah, you can't apply same SAS metrics to AI companies, all this stuff. It's a different business model. Well, now I think that's coming back to center, but there are definitely some AI metrics evolving. I have an AI metrics course now that are applicable, but are there discussions around the margin front if a sponsor, if a strategic sees an AI revenue line?

37:49Yeah, they want to know what that cost looks like. And frankly, how are you tracking it? Who's controlling it? How do you throttle it? And it all, there's this kind of circular reference back to pricing. A lot of this is just solving the pricing model, I think, might be one of the most difficult elements of the transition to AI for a lot of businesses. It is a stark departure from the predictability of your annual upfront payment, right? and your COLA or CPI entry, wherever you want to think about it, right? And that covers your cost entries. This is a totally different equation. And again, I think it's very early in how people are getting their head around it.

38:39But those questions are being asked. And frankly, they're being answered with varying degrees of sophistication and detail because a lot of this is very early. We're seeing a lot of people, Ben, pilot AI products. They don't know what the adoption is going to be. They don't know what the adoption is going to be, and they don't know what the cost is going to be. And frankly, there is some concern that people are going to say, you should just give that to me as part of what I'm already paying. Kind of a scary concept. We can perfectly control the cost, right? The fixed price with the uncontrolled cost is like the death spire, right?

39:18There's all of that going on. I'm sure you're hearing all manner of stories. I'd be interested another time to hear how you're seeing the AI TPI dashboard evolving over time as people continue to use AI. And by the way, I don't mean to overly focus on the sort of outward facing AI. There's a whole question inward. I'm like, so we're using Cursor or Cloud or whatever to help with our software dev. And we took our eye off the ball and our developers went bananas on it. Now I've got a giant bill and I can't figure out if we made progress or not. Was that money well spent or was that a disaster? And so there's that whole element of it too, which is people are trying to leverage it to save money.

40:03And that's where I think the ROI and the productivity gains are, it continues to be murky. I think some stuff feels really obvious. Yeah, I did that a lot faster. And then there's the other parts where I think people are still trying to understand on the net, what exactly has happened with my use of AI? And that remains a lingering question. Yeah, definitely. And we haven't even touched upon internal AI focus. And I've actually hopefully have a future webinar coming up on that because that is the theme of the day for CFOs is getting AI spent under control, especially that ROI and on the dev side.

40:41But one more. So we've got Outlook question here, then we'll throw you a hot seat for some quick answers. But I won't ask you about next year because who knows, but Outlook for this back half of the year, is it going to improve a little or do you think it's just going to stay the same? I guess I'm always optimistic, Ben, that our world of software is pretty resilient. in. I don't really know how to handicap the back half of this year. And usually I have enough conversations with folks where I can get a pretty good read. My gut is it's going to be more of the same and it's going to be pretty choppy.

41:17And I don't see it recovering up into the right in any meaningful way. I don't see it like dropping off the cliff. I think it's going to be a little bit of up and down. And we've already seen that in the second quarter where April was kind of business as usual, May was not good, like down 30 % when more data is coming in. So maybe it won't be epic to drop off, but it's July now. So a lot of that data is in. And then it looks like June kind of bounced back, but not all the way. And so I think we're going to just continue to see more of that as we go through things. And the public markets are all over the place and we've got stuff in the Middle East and various things happening, but I think it'll just be more of the same, honestly, maybe with a little more up and down volatility month to month, then maybe a little harder to get deals done.

42:04I mean, the bars are a little bit higher. Yeah. No, that seems very fair. So more of the same. All right. So some hot seat questions. So quick replies here, and then we want to wrap up in case investors would like to reach out to you and some more questions about the market. But first question, is this a buyer or seller's market? I think it is a big time seller's market. I mean, if you've got the right AI split, I think it is a buyer's market for everyone else. And I don't think that's going to change. Look, is there a room for margin around the edges there? Yes. But I think that's probably generally true.

42:40And that doesn't mean you have to be high-flying AI native, but you've got to have a story. Right? You've got to have a story. It's got to be a real one. And I think you've got great potential this year. Okay. And are buyers focused on platform or add-on acquisitions right now? I'll receive one or the other. They're still way outpacing platforms, which would be the case probably in any year, but just proportionately, it's been skewed pretty significantly the last few years. I don't expect that to change. I think that's actually interesting for the mid-market, where maybe most of the folks on this sort of podcast are listening in are relevant, where your business might be a really nice add-on for a strategic.

43:22And that's a good thing. The platforms are just few and far between. The bar is really high for those right now. Funds have a ton of money. They need to deploy it. They also need to sell some stuff, which we're still waiting for. But AI has made it harder, so I don't expect to see a resurgence in larger platform yields on a percentage basis. Okay. And final question here, rollover equity. So if there is some rollover equity involved and the PE firm, say, wants the founder to roll some over, What is a general range that you're seeing? So most deals that are like 20 to 40 % would be a pretty typical range.

44:00You want to roll less than that. Usually it's coupled with the desire to step aside in a period of months or years. But that's typically what people ask, 20 to 40. Okay. All right. That's a little higher than I thought. So unless, like you said, the founder is going to step aside. So interesting. Yeah, and that doesn't mean that there's not room to roll less. It just means that's usually where the ask starts. We see a lot of deals at 15 % to 20%, some down to 10%. You start getting less than that, but it's why? Why are you rolling that? No free rides with private equity, which I totally appreciate, by the way.

44:39They want you involved. They want you to add value. Earn that. Yeah, exactly. So they want to get in the game. Yeah. All right, Jim, really appreciate it. We almost went an hour, a long time here, but a lot to dive into. So I appreciate your time and the market update here. Now, if listeners have more questions and want to reach out to your GLC, how should they make contact? Jim.Williams at glca.com is the email address. You can certainly find our website. Just look for GLC Advisors and all of our contact is there. They can reach out to you and bug you for it, Matt, although they hope you're not inundated.

45:12And then we provide our capital markets report as well, which has our contact information in it. And we're in the process of getting our June 2 report done shortly. So as soon as that's done, we always provide it to you. And I think you'd beat it out to folks. And certainly, if anyone has any questions on that, we're going to discuss anything in that report or, frankly, any other questions people have. All right. Perfect. We'll put some of that in the show notes plus your LinkedIn profile. And again, Jim, appreciate the software update today. Yeah. Always good to talk to you. Thanks, Ben. Thanks.