Will AI Kill Consulting? (w/ IGS CEO Matt Umscheid)

You need your teams to be able to sort of do something that's achievable, right? Like if you leave them on the five yard line with, you know, no pads on, they're going to get killed. Totally. I lasted one week at Pop Warner. I got run over once when I wasn't paying attention, probably picking daisies and I was like, that's it. Handed in my helmet like, I'm a lover, not a fighter, man. It's not venture capital, it's private equity. It's the private equity fun cast. Pour yourself a drinking house. Hey everybody. Welcome back to the Funcast. We have a good one for you. Today we're going to talk about the state of the consulting industry, especially consulting into private equity. If you see one side of the trade is consulting over for $20 a month, you can just do all the due diligence you need without anybody's help. The other side is anthropic and AI are throwing billions of dollars of building consulting firms to drive humans into companies to make AI work. I've got a great guest. It's been A friend for 27 years. A three time private equity backed CEO. A year ago he joined to become the CEO of Investor Group Services. IGS is what we call them around here. They're our go to commercial diligence and go to market provider. We've worked with them on dozens of engagements. We're engaged with them on something right now. So there's nobody else better to walk us through the current moment and what's happening. Matt Amscheid, the CEO of igs. Thank you. Excited to be here. All right, so let's start just quick, who are you? How'd you get here? What is igs? Because you could explain it better than I can. Really appreciate the opportunity to sit down and talk with you about this stuff today. It's only been 27 years in the making. Right, right, right. Devin and I got to know each other at Tuck many years ago. My background is consulting. I worked for Arthur D. Little and then lek. In between, I spent time at where we got to know each other. I then moved to Parthenon Capital and worked on their operating team for nine years and then moved into operating roles, various commercial leadership roles and then into the CEO role. IGS is the third private equity backed company that I have led in the CEO role. It's sort of an interesting experience to come full circle, to have started my career as a consultant, carried the bag, done the work, and then been a buyer of the services in private equity. For many years. That's where I actually got to know IGs originally and now to be a consumer of consulting as an operator and to have that put in sharp relief where I feel like consultants can bring value and where there's opportunity for IGs and where I think we can really differentiate ourselves. All right, well, no business is being transformed more, or at least threatened more by AI and consulting in general. Right. All different kinds of consulting firms. We've used IGS as our go to go to market commercial diligence provider for years. That's why I wanted to have you on here because I know what you guys do and I know the quality of the product and we depend on you pre and post deal. But if you read the headlines, it's over, Right? Right. All you need is a $20 a month subscription to Claude and you can do all your commercial diligence and all your research and all your market diligence with an analyst. We know that's overdone, but like from your perspective, CEO of a company that primarily, if not exclusively, works with private equity owned businesses, what's going on with AI and consulting writ large? And then we'll kind of narrow it down from there. Sure. So let's start with just pace of change and I would say two years ago, from my perspective, AI and the AI opportunity was something that was on people's radar and something that they felt like was relevant to them. But man, it felt like it was going to be something that was hard for them to reach. So maybe you had somebody inside the firm, consulting firm, using the heck out of it and be like, wow, this is transformational. But it was kind of isolated in that one person's capability, not spread out across an organization. Right, right. And what I'd say over the last two years is we've gone from sort of early, early adoption across the broad group of consultants, particularly middle market consultants, to a place today where I feel like it's really become embedded in the business. And I'd say there are the large players that you're familiar with who are at the leading end of the curve and scale and investment, who have partnerships with large AI players. They've built tools internally and invested in some cases hundreds of millions of dollars. But I would say at the delivery level, what a client experiences probably hasn't changed that much. What I have seen is, is companies have gone from sort of experimentation, which I think a year ago was something that was either in its early stages or maybe fully developed, to a place where like everybody get a cloud Account, play around with it. Let's get together once a week or once a month and talk about what we've learned. Share skills, share tips and tricks and all these things. Figure out how to cheat at your job. Right. Get ahead, do work more quickly and more efficiently. Today we're at a place where that is no longer sufficient and not a good approach in terms of really getting something that is additive to your offering. Where we are today is to have a need for a very clear vision around what that is inside of. We can use consulting firm as an example, how we deploy that and then within our leadership structure. And this goes outside of a consulting firm. I think of it as sort of line management. Right. The line management has to have a view of what this is and, and where it goes. Yeah. We've talked in the past about three things you think about when you think about AI is kind of risk and defensibility, how to value creation. Right. How do we move the needle consistently and kind of with impact. Right. And then just internal AI readiness. So give me a little snapshot of each of those three. What does that mean? Yeah, sure. So, you know, I would start at the, at the level. And, you know, the first thing that I would consider is to what extent is AI reshaping this market? Is it relevant to the business model? And then, you know, what are the, the considerations there? If you then move into, you know, the risk assessment on the company side, there's digging into, you know, how does it affect the product or the service? How does it, you know, change the competitive landscape? Okay. So it feels like one in three, like risk defensibility and then AI readiness of the team and the organization. Relatively easy for a third party to come in and say, we've got our scorecard. We ran it up against a scorecard. You're a two out of 20. You're an 18 out of 20. And we have the same one. I mean, people can go and download on GitHub our AI readiness skill and run a company through it. So what about the middle this value creation piece? Is AI changing the ability to drive change post acquisition? Yeah, it really is. From a value creation perspective, we look at leadership and we look at people, we look at their process, we look at the technology infrastructure and to what extent the change can be supported there. I do like the BCG framework that sort of says people in process are 70%. I think that's a good way to think about it. Doesn't matter what technology you have or what data you have. If you're not if you don't have conviction around pursuing this and you don't build yourself a good process, you can't get there. And so from a value creation perspective, the coaching mindset is the most important because you need your operating team, the operators of the business, to drive it. I've been in the business for 30 years, and there's been these times at which there's the big freak out of, hey, we gotta get somebody in here and help us figure this out, right? So the first was, you know, I started in 95. The Internet, we gotta figure out the Internet. Maybe it was Y2K. Are we going out of business? Then in 2005, 2007, it was China, India. I mean, we laugh at some of the decks we put together. 20 years ago about India, I was like, have you been to India? Have you been to China? No, but I'm worried about it. Then it was obviously GFC stuff like, hey, are we dead or are we allowed? We default dead, default alive. Kind of figuring that kind of risk thing out. Then it was the Cloud 2012. Hey, the Cloud, the cloud, the cloud. Then it was remote. Oh, my gosh, we are Covid. We got to figure out how to remote and retool the organization and kind of live in a hybrid world. And now it's AI. Maybe I missed a couple along the way, but each of these times were times when somebody picked up the phone at a private equity firm or a private equity owned company and called a group like you and said, give me some perspective. I think that AI is changing businesses more rapidly than any of those things have in the past. Because I think the pace of how it is affecting individual processes through the business, up and down the scale, and the just sort of. The democratization of that technology means that the change is sort of ubiquitous. It's. It's everywhere. Meaning for 20 bucks a month, everybody's got the most powerful model in the world in their laptop right at the end of an Internet connection where with China and India or remote or the cloud or whatever, the Internet, it was like, I don't know, okay, I'll wait for the change to happen, then I'll adapt to it. There's nothing I can do right now about it. Is that weird? Is that fair? Yeah, yeah. I'll use a. Well, maybe not a funny analogy, but like, I remember pre Covid sitting in a conference room in Denver, Colorado, having a conversation with someone saying, gee, do you think Covid's gonna come? Come here. And both of us looked at each other and said, nah, it's not coming here. Well, two weeks later, I was home for months. We were buying a company at that time, an add on for a company we owned. And the owner was in Florida and he was like, this is gonna all be blown over in two weeks. Yeah. And he was like, I'm not changing the price. I'm not changing, like you either buying it or not buying it. And this was in the aviation industry. So we bought aviation software business in the spring of 2020 as an add on to a business we already owned. And it was like, there are no plane. I mean, this was like the planes were still flying. Right, Right. Nobody on them. Yeah. But he was like, well, I mean, either if you're not still buying, I'm walking and I'm going to go, you know, find somebody else to buy it. Now, he wouldn't have been able to find anybody else to buy it for a while, but business held up. Great. Aviation, you know, planes got back in the air and everything in that transaction had been fine. But totally same thing. I was at a they Might be Giants concert, like March, this is dating me, but like March 9th or something with my brother who flew in from Boston to see the show at the Vic here in Chicag. And because they canceled the Boston show, we are standing next to a couple who are like, we flew in here from London because they canceled the London show, because Covid's all over London. I'm literally sitting in a room with 2,000 other people breathing each other's air with two people from London where they already shut London down. And we're like, this is fine. Right? So I mean, that was my, you know, six years ago experience. So I want to talk about red flags and green flags. How do you pick a consultant on an AI project without, you know, making a mistake? But before we get that, we got to talk about anthropic and OpenAI building these consulting firms, you know, with billions of dollars of valuations, hundreds of millions of dollars investing, and these kind of like, hey, we're going to go. And these big private equity firms investing them to bring them to their portfolio. Like, what's your take? Because I have one. I just want a more informed take from somebody actually knows what's going on. Look, I think great distribution opportunity for them to embed their technology. So I think it's a smart strategic move for the model companies. Yeah, I mean, for the model companies to do that. Exactly right. And so. And I think that, you know, biggest opportunity is the largest businesses in terms of transformation dollars and scale and, and benefit. We live in the middle market and the middle market is a different place. Right. Most middle market companies are not paying McKinsey or MBB rates. They're certainly not paying it for any kind of transformation work. It's far too expensive and may not even be the right fit. And so I think what we're seeing is a need for AI technology and real thinking in the middle market. But we're also seeing the need for somebody who can sort of bring to life a strategy. And by strategy I mean actually something really tactical, like how do you build a roadmap of stuff to do that you understand, your team understands, and when you're putting technology to that, you have a clear understanding of what you need to build, how much that costs, where your ROI is and what it's going to do for your business. Yeah. I have two things I say to management teams that are sick of me hearing it. This is a middle market, right. For small companies that are trying to execute every day strategies for people who hit their numbers, hit your numbers, then we can talk about what the strategy is. Right? Right. But we don't need any strategy until you actually go execute the plan, like, save that for later. And then two is there's no difference in a middle market software company between the product strategy and the corporate strategy. They are one in the same. Right. Like your product roadmap, what you're doing with the product is your strategy. So you don't need a whole bunch of other stuff unless, you know, you've nailed the product thing and there's other more interesting things to do. Here's what I don't understand about the whole deploy company concept. One, where are these consultants coming from? They work at like PwC and Capgemini and all. They're like, they got to hire a bunch of people to like build these companies. Right? Right. Yeah. They've got billion dollars of valuations with no revenue right now. Right. We know what consulting firms are worth. They're not worth multiples of revenue. Generally, they're worth multiples of ebitda. Right. Where are these people coming from? Because anybody who's good at Claude is like a week ahead of you. Right? Is that right? Yeah, I, I think it's, I think it's a, I think it's a fair question. You know, one of the things we're seeing is that people are entering consulting today around AI services. And, you know, they may have been accomplished operators or they may be software developers, but consulting is a real skill set and engineering is A real skill set. And both of those things, I think in the world of AI transformation need to come together. And so, you know, I think they're going to hire people. Yes, there are, there are trained consultants out there that you can pull from big firms. But I don't understand how that's any different than what they're doing today instead of the firms they are at all. Right. You probably can't say this as well as loudly as I can. They're going to hire some amazing people from competitive consulting firms who have this great opportunity to build a new consulting firm, AI first in the image. They want to build it with unlimited funds to do it. Right. Right. Maybe even some of the operators inside these private equity funds who invested in them would go and join them to help deploy across amazing conceptually opportunity. These are humans, there's process, this is messy. The technology is evolving. Why in the world would any, you know, insert large private equity firm, portfolio company standardize on one model versus the other? The whole point of and the whole challenge with these models is there's zero moat. Each of our portfolio companies, we use bedrock, AWS bedrock across the portfolio. We can swap out any model, open source, you know, foundational model, Chinese model, American model, French model on the fly. Right. So like there's no. The switching costs are so low. I don't get why anybody would lock in on one of these models. And then I assume it's all forward deployed engineers and all this stuff. It's like where are they coming from and do they know the business? And we've also had across the table from a consultant, you running a company right now and you hiring people to help you when you were at in private equity and you hiring people when you were CEO of private equity owned businesses. If you don't know the business cold, you can't sit shoulder to shoulder with somebody in the business. Yeah. Understand what they're saying, what their pain point is. Map the workflow, automate the workflow, close the loop. That's really hard for really smart people who've been in the business, in the industry for a long time. Here comes Joe Schmo from Capgemini. No offense to Capgemini, who's just like, hey, I'm your forward deployed engineer and I work with OpenAI. I think that's a pretty hard proposition for me to buy off on that. I'm going to get a ton of value from it. I guess maybe two things. One, at the highest level, consultants are trusted advisors and trusted partners to work with and they build that trust through often a long period of time. And so that's very hard to replicate. The vertical knowledge can be portable, but if you're trying to layer in a completely new approach to that, I think that's very risky. Right. Like, I think, you know, you're likely to come up with an outcome that doesn't meet your expectations. And one of the things that we'll get into here at some point is an experience that we had where we hired a firm to build something for us. Smart engineers, great pedigrees. But I would say overall, the arc of that project did not meet our expectations, in part because they were using new tools, they didn't know our business well enough, and they just couldn't go fast enough to keep up with the pace of change in the marketplace today. Let's dig into that here. Right. Again, this is no knock on consulting. I mean, for better or worse, I'm stuck with igs. I'm happy to be stuck with you guys. But you know us well. You know the types of businesses you're in, the businesses we own from before we even bought them, or even some where we wind up not buying because of work we did together. I'm kind of in the place. Like, Matt and the team there are going to figure this out for me. They're going to figure out the tools, and I'm going to get more out of them because they're going to figure it out. All right, so you guys hired somebody. It didn't work out. Tell me a little bit more about that, and I'll tell you about same experience we had earlier this year. Yeah, we have two really, I think, helpful experiences that I'm happy to share with other operating teams and with other investors as they think about supporting their operating team. So the first one was something we started probably a little over a year ago and invested in building out a sort of a technology, I'll say an AI technology capability, and be any more specific than that intentionally. But we invested, we made some progress, we got some benefit out of it. You know, we have, you know, 4,000 projects that we've done and data that is well organized, and we did that through that project. But what we didn't achieve was the ability to use that information in the way we wanted to. You know, I think what we found was that that group was constantly relearning our processes. Right. So we. We did the basics, and that foundation is sort of portable for us, but it never reached its full potential because they couldn't really get into the process. Of what we did and how we used our information and how we deployed that into the work that we do for clients. So for that project specifically, hey, come in. Help us build some technology that we can then scale and then deploy across our clients. Use internally, close the loop, like finish it. What could you have done before you started to make that have gone better? Yeah, that's a great question. You know, I would say we would have probably looked for, for example, work that we could build on. And I think we were a first project for them. But who isn't a first? Who isn't a first right now? So you're like, oh, show me some project you did like this. Or like, it's too early. We have. The models have all changed. We couldn't have done this even six weeks ago, let alone six years ago. I do think there are people who have done the work with different technologies at different times and who are skilled at learning businesses and building technology, regardless of what that technology is. And I think we would have been able to sort of assess that better. I think the other thing that's true is our DNA is consulting. We didn't have any DNA of software development inside of our shop. Having run two companies where we, we did software development at pretty significant scale, what you realize is it is it takes a great deal of skill to build software and to build technology and deploy it inside of a company and, and to have a real sense for that oversight. And we just didn't. So take a step back. Like thinking somebody, anybody from the outside could come in and build software specific to your own business. Probably too, too hard a putt. It's hard. Yeah, it's hard. And it's hard for, for folks who are hiring those advisors to really pressure test their work. Yeah, I think one of our core tenets is don't do a consulting project unless you have a strong leader in that function to own it. Right. We've done those. And what happens is you learn a lot and then it just sits on the shelf. There's nobody to take it and drive it. So sounds like a similar thing for you as a piece of advice to a CEO or a private equity firm who's thinking about this is, hey, somebody inside the firm has to own it and think about it every day rather than, hey, here's the project, we could build it for you and hand it off. Absolutely agree. And I've got a couple finer points on that. One is, you know, there's a, there's sort of leadership and you can have good leaders who are generalists, and so they can do a good job and you can trust them. I think two other things. One, there is a drive that you have to have around this transformation, and that's got to be something that comes from within the company. And then secondly, having technology as a specialist or a special capability and depth in that makes a huge difference. Yeah. Okay, you said there are two projects. That was one. What's the other one? So that was first one and then the second one. And I chuckle a bit because we're now doing this ourselves and it's just remarkably different. The classic strategy and roadmap project. And there are many, many consultants out there who will offer to do this for you. And I think these were earnest guys and I think they tried really hard. But what we got at the end of the day was a PDF document that was created by ChatGPT. And there was a lot of jargon in it that, you know, I couldn't really sort of penetrate and there was not enough specificity. Right. So if you need to come up with an AI strategy, what you actually need is to understand all of the context that we've been talking about for the market, the business, the risks and the opportunities, and you need to plan. Right. And so what does that plan look like? That is a set of projects. That is a list, a very clear list that can define what the investment is to achieve or build these things, and then what the return is going to be in your business. So how much time are you going to save? How much faster can you go? What new products or capabilities you're going to bring to market, and what's the value of that? And if you can't get to that specificity, if the people you're hiring can't give you that list, that roadmap, and can't actually bring that to life, then you can't really get going. And that was the result of version 1.0 of that. Happily, we took that on internally with a team that we've brought in in mass under a Chief AI Officer, Justin Bass, who's an accomplished machine learning engineer who, who's led technology organizations at scale and deployed enterprise technology. And so, man, what I see is a huge difference. I see our team marching together. I see very specific investments that I know that we can make and technology that we can build that's gonna benefit our business. And as disappointing as that project was, sometimes you need to go through that to get to the point where you say, you know what, we just need to do this ourselves. Yeah. And that's kind of maybe what the organization needed. You needed to go through that to get to the place where you're like, we're ready. We can do this ourselves. It's going to be hard. It's going to be distracting. Let's, like, resource it the right way and execute it. Yeah, I found that. I would have been happy to skip it. You know, scars are well covered, but I get it. But like, you know, sometimes, like, yeah, like with your kids, with family, sometimes you just need to go through things. Right. And just to experience it. Right. You want your kids to, like, actually have some, Some. Some stress in their lives. Adversity. Adversity and challenge is a good thing. Yeah, yeah, 100%. It's a great teacher. It's good for resilience. And then you also get the organization rallied around it. So I'm not advising that everybody go have a failed strategy consulting project before they take it internally. But again, like, right. Given where we are and how fast things are moving, like, you know, you did what you thought was right, and now you pulled it internally. So here's ours. So last fall, so this is. We're talking in the spring of 26, so the fall of 25, we just got inundated with calls from AI workflow tools that could automate private equity. Workflows was happening in banking and legal. And here comes for private equity, meaning you get a SIM in from a banker in a data room. We can build the model, write the memo, do the market diligence, do everything. And you don't need any analysts or associates anymore, basically, is the pitch. So I was like, I don't believe it, but like, let's demo every single one of these products. So a couple of people on my team, we demoed them, we recorded every demo, we recorded every meeting. We posted it on our basecamp or, you know, our internal intranet we use so everybody could see everything and then like, you know, pros, cons, costs, you know, what could it do? What could it not do? We would throw our own stuff at it to see if it worked. We'd get, you know, demo accounts and play around with it. And what we came to realize is very expensive wrappers around ChatGPT or Claude. And none of them actually could close a loop. We spent more time QA ing what the machine did than we would have done if we just built it ourselves. Let alone kind of the laziness factor of, like, I don't know, really ambitious. Associates who come into private equity didn't come here just to Orchestrate a model and have it do everything for them. But the people who are really good, I think the people at Parker Gale were like, no, I like doing that. And that's what I'm learning. So I'd love something to accelerate, make me go faster, better, further than I ever could have gone on my own. Like, you know, a co pilot, right? Co working, you know, kind of like the Ethan Malik model. We just wasn't there. So we're like, okay, we're not going to spend a couple hundred thousand dollars on one of these tools. Fast forward to December. We're like, let's build it ourselves, just like you. So we went and hired a few guys out of Y Combinator. I'm going to keep them anonymous for this. But like wicked smart guys, worked in private equity, investment banking and engineering. They were in a Y Combinator cohort and we were going to be like the test case. And again, we have a CTO as my co founder in the firm. Like, we're as technical as private equity firms get internally. We use a lot of software. We built a lot of stuff ourselves. We're very technical. I purposely had all the associates work on this instead of having my CTO and me work on this. I was like, you guys do it, you know, all the workflows. This is. If this can't make your job 10 times easier and get rid of all the boring stuff so you can spend all the time in the exciting stuff, let's not do it. So it was a deal comes in, an email comes in, have that person put in the CRM. If the person's already in the CRM, update the CRM that we got a deal from them, pull down the sim, put it in Ignite, which is our file server, build the data room, build the folder, the file system for a new deal, draft, do a quick draft of the notes from, from the SIM and put it in Basecamp where we kind of do everything and then, you know, update the CRM stuff. Not very hard. Ignite, Salesforce, Basecamp, couple other tools. LinkedIn. Couldn't do it. Yeah, literally couldn't do it. And again, these guys were brilliant guys. These people would be forward deployed engineers at any one of these consulting firms. And it's just really hard if you're not in the day to day with the workflows and you don't know how it works. This wasn't like super hard stuff. We weren't like, hey, go like write a credit memo and underwrite the deal for us, right? So we spent a Little bit of money. A couple of things happened. One, we learned a lot about workflows and kind of how our own systems are working where some bottlenecks were. That helped. Yeah. Two, we Claude cowork really got really good in February. Really good. Everybody was just like, hey, I could just. Then we just like went on this like skill building spree while we were working with these guys. So I called Friday Fry AI day. So every, every Friday I told everybody you have to spend at least two hours, if not four to six playing with Claude and just seeing what good to do, finding the edges of it. And then on Monday you had to come in to our Monday meeting and tell everybody what you worked on. You could do it over the weekend, you could do whatever, but you had to come in Monday and show your work. So we built all kinds of cool skills that we've now shared across the team and people were kind of falling out of love of this YCP project. Now fast forward to today. Kind of the model works pretty good, right? We've built a lot of cool stuff in Claude. None of it perfect, but definitely accelerators, ceiling razors, not floor razors. So like making our best people better and doing stuff they normally wouldn't do or wouldn't have paid a third party to do. Now we're coming back around and demoing all those third party products again and those tools have gotten really good. So here's what we're going to do is like we're probably going to swap out a bunch of our tools for new modern tools. So we're probably going to leave Salesforce and go to something else. We're going to leave a couple other things and go to something else. We're going to connect all those things through an MCP server or through their own APIs. My sense probably APIs or agents rather than MCP. And everybody's really excited where the technology is now and kind of invigorated that this nine month project of being deep in the stuff and seeing it. They have way more context and way more excitement about what could happen and they're way smarter. The second thing that happened, first one was long, second one's pretty quick. They have a lot more sympathy for our software companies who build stuff and it's hard, it's really hard to build product that people want to buy and use and get value from. So they now hopefully step into a board meeting with a little more empathy for our CTOs and our engineers who are trying to build stuff for very complex vertical markets where our customers have way more domain expertise than we do. So that was helpful, just from a karmic standpoint. I love the empathy idea. I'll pick up. That's because we went to Tuck. We love empathy. I mean, you know these Wharton guys. It's a good lead leadership characteristic. And this has all forced us to be incredibly light on our feet. Right. There is a short success failure loop that we have to go through. And if something's not working and you know it's not working, you got to move away from it quickly. And that's not new news. Right. Like, that's early in the private equity playbook. Yeah. But we had. We learned this lesson over and over and over and over again. Right. Over and over. And it's. And it's bringing your teams along with that sort of, you know, agility, I guess. And that's a good skill to have as an organization. All right, let's knock through here real quick. Red flags, green flags. So you have an AI project. Right. Tactical, strategic, somewhere in the middle. Whatever you need to. You want to bring in a third party. Right. So red flags, as we talked about heading into this interview. And they lead with technology before kind of really understanding the problem. So, like, hey, we've got this amazing technology. That was our Y Combinator problem. We got a. As the Spicoli said in. In fast times at Ridgemont High, I can fix it. My dad's got a bitch instead of tools. Right. You can't fix this car. Spacali. I can fix it. So there's that. The Spicoli, like, look at this cool thing I have. It's a black box. Don't worry about it. Run away. Right, Right. So what do you mean by, like, they gotta understand the problem. The more specificity, the more depth and the more understanding that somebody can bring just allows them to start, you know, further up the mountain and to help you climb faster. There's somebody in this world who has solved this problem before. As we say, like, the future is already here. It's just not evenly distributed. Right, Right. So there's somebody in the world who's done this thing. Your job is to go find them, not hope that you're going to teach some plain vanilla consultant your own problems. Right. I mean, to your point, Right. That this is sort of mapping workflows, understanding automation, deploying, building that automation and deploying it inside of the firm and understanding holistically how that all fits together. Yeah. The second one, which may be a 1A to that is too general. You have to be Able to speak your language. And your job is to go find the people who can go do that. I mean, this is the igs, Parker Gale relationship, which is, you know, we buy kind of messy founder owned deals, often with high nps, low market awareness. So you're trying to determine, you know, that about us. Us. So when you're doing customer calls and surveys, you're not like raising some red flag for us. It's like, oh my gosh, nobody knows who these guys are. Right? We're like, yes, nobody knows who these guys are. We can fix it. Right. Or like the NPS is cracked. Like what you were seeing before isn't actually true. And we kind of really got into it. So again, like, we speak each other's language. We know your team super well. They know our companies well. Management teams feel like we're working together. Like that's hard for us to, you know, there's some switching costs there. Right. So anybody who's too general. And again, we, I have hired some of the big guys for other projects. You know, it was a little, it was a little. The slides were way prettier. I will say slides are a lot prettier. There was way more words on them too. Holy cow. They can fit a lot of words on those slides. But it was kind of like it was on the shelf pretty fast. Yeah. So again, I think we learned our lesson there. And then you talk about like cons, you know, constantly needs to relearn your business. What do you mean by that? Yeah, I think that, that just goes back to, to our first example where, you know, we felt like we were teaching their engineers over and over again what, what we were actually trying to do. And, and it, it just was yield loss. Right. And so you can't go fast and be productive with somebody who really doesn't understand what they're doing. But we're all learning right now. Well, what AI is learning right now? Boy, is that last mile hard. Right? Right. Yeah, boy, is that hard. Right? And you know what? As the models get better, the complexity of what we're asking to do will get harder. Will get more and more complex. Yeah. The last mile is still going to be there, right? Last mile is always going to be there, no matter how good the models get, because we're going to throw more complex problems at them. It's a great analogy. I think that's a great analogy. All right, green flags. When are you like, yeah, yeah, yeah. So first one you said to me is the. They have demonstrated experience of real process depth. So how can you tell that? Like, you're getting pitched, we're getting pitched. Sounds good. Slides are pretty. People are smart, you know, they went to tuck. So how do you discern that? Yeah, yeah, maybe, maybe two ways. One, you know, I think reference ability of their work. Right. Somebody, somebody in their past should be able to say they've done that for me and they did a good job. The other thing you can ask for is an anonymized, deliverable. There are three slides that I would look for from somebody and if they can't put those in front of me, then I know they're full of it. Yep. Okay. Second one is engineering capability beyond PowerPoint. Yeah, we talked a little bit about this. You're talking your own book here because you're building it, which we'll get into, which is fine. Meaning, like they need, if you're hiring a consultant, you want to see engineers on the team or it's part of the solution. Yeah, I go back to your last mile discussion. Right. And so, like, there is a lot of ability, I think, to sort of at a high level discern a strategy around AI. People can do that. Right. But for you and what you need, you need someone to take that sort of good. Getting more specific, getting more specific, getting more specific guidance to something that they bring to life. And that is where the rubber meets the road. It's, it's the engineering capability. And so if you're relying on somebody to hand off their assessment to somebody else to build it, it's really hard because the build it guys don't know exactly what the, you know, the strategy guys we're talking about. And if that's not hand in hand together, your estimates probably aren't right, your timeline's not right, your costs aren't right, and your returns aren't probably wrong too. And so we, we feel strongly that that's, that's critical. Yeah, well, this episode is like, how do you hire an AI consultant? Right, right. And you're not hiring an AI consultant for strategy or for tactics that actually can't implement the AI tools themselves. Right, right. Yeah. I mean, you, you need your teams to be able to sort of do something that's achievable. Right. Like if you, if you leave them on the five yard line with, you know, no pads on, they're going to get killed. Totally. I lasted one week at Pop Warner. I got run over once when I wasn't paying attention, probably picking daisies and I was like, that's it. Handed in my helmet, like, I'm a lover, not a fighter, man. Where's the debate team and Aladdin Club? Sign me up. So the last one we had here is kind of Green Flags is focused on results tied to company strategy and objectives. That seems pretty basic, but like, you know, what does that mean to you? Somebody who's been on both sides of this? Yeah, that. That is somebody who can, you know, put that roadmap in front of you with a cost estimate and an ROI estimate. You can think about your enterprise value impact of that, value creation impact of that. And they're able to. To sort of give you specific examples of deployments that they've done that bring things to life. All right, so we've talked about what's happening in consulting in general, right? All the doom and gloom, but also all the, okay, consulting's over, but the two smartest companies in the world, growing the fastest, have started consulting firms. That should tell you something about the future of consulting. Probably pretty bright for the people who have figured out. Yeah, talked about how to pick a consultant. Red flags, green flags, things to look for. So let's talk a little bit about what you're doing about it. Right? You are the CEO of a consulting firm, largely go to market, commercial diligence now, AI capabilities across functions. So, all right, let's get inside your head. You're in the boardroom and the exec team meetings. What's happening? So, you know, the. The first thing that I got asked or the second thing I got asked in my interview with the IGS board was around AI. Fast forward that into joining the business and looking at opportunities. The management team and the board really rallied around this notion that it was an area for us to invest and that we needed real expertise. It was sort of. It was just very clear that we needed our own internal capability. And an internal capability in consulting is people are people. And so, you know, what I think is unique about what we have done is we've brought a team in that has experience together. And so in the last 18 months or so, this group of people have done 35 projects together. So strategy to AI implementation and transformation. You know, they're now embedded in our firm. Our partners are learning that business. They're building trust together. You know, we have hundreds of trusted relationships with private equity firms, and our opportunity is to bring what we think is a really amazing offering to all of them. Whatever we do needs to meet the standard of excellence that IGS has established for 25 years. That's why we have such an amazing business. And so many repeat clients. So we made that investment and we're off and running. How did you explain the why? How do you communicate that to the organization? It felt very natural inside because in parallel to that, we were trying to break our own trail in AI and. And we were, you know, we had a. We had essentially 10% of our organization, you know, really smart young folks dedicated to thinking about how do we improve our work process and our work quality. And they made amaz. They made amazing. They made some amazing progress right out of their own hard work and their own curiosity. But I think what we all felt collectively inside the business was this growing wave of opportunity around AI And I think the need to put a finer point on our direction. And so I think when we announced this internally and when we plugged this team in, it went well. I would say that probably one of the most important things in consulting is culture and man, from a people perspective, it just fit hand in glove with the team that we. We brought in. Amazing, because. So it wasn't the Mark Zuckerberg move of like, I'm doing all this AI to suck all the value out of your brain so I can automate this right in the machine, and then we're going to give you a really healthy severance package on the way out. No, I mean, that's. That is some of the concern across all industries. But consulting, too, is like, oh, no, let's just. Let's get context. We're going to fire the context when we fill. When we feed the model. Yeah, yeah, yeah, yeah. We have. I mean, we have got to tell. That story is like, no, no, no. This is a supercharged to what you guys are doing, not a replacement. Totally. Yeah. The story we hear from you guys is, hey, we're consulting plus engineering, right? That's different. It is a story. So what is, What's. What does that mean to somebody who. Yeah, like somebody on the client side, somebody listening from a private equity firm who's like, hey, I need help. Or a CEO of a company who's like, hey, I've been asked by my board, figure out AI. If you're on the other side of the table interviewing consultants, you should know the answer to this question in the first five minutes, Right? So as you hear their backgrounds and as you ask them about their capabilities. Listen, listen for a couple of things. There are words around sort of offering a plan and coaching, right? That's one flavor of consulting. Or we worked with you and we developed, we delivered, we transformed, we helped you with governance and change management. Like, and that That'll come out in the first five minutes of a conversation. And if the only thing you want are pretty PowerPoint slides, option one is going to get you what you need. Nobody wants that. That's what they get. And that's the knock. And on you guys we got, private equity's got plenty of knocks. We got all this value creation but we don't actually help. Right. We just say value creation, value creation. But then we actually do anything like smart, not useful. Right. Kind of. That's our issue. Yeah. Lawyers, same knock. Yeah. So yeah. So I know what you guys are good at. We've used you guys forever before you ever even showed up. And now I have even more confidence to work with you guys given our relationship. So I can put you in front of a company and feel, feel good about it. But for people who are listening before we get to the speed round, like when should they think of IGs like we're great for what? Yeah, we're great at helping private equity investors and their operating teams from the beginning of an investment to assess the opportunity and weigh the risks and really embed smart thinking into the sort of the investment strategy and the investment answer through the value creation period with a very strong focus out of the gates on growth and we can get very tactical on that side on pricing and go to market and then through the hold period in terms of transformation particularly around tech transformation, AI transformation and then in exit preparation. And so we can do market work on the exit side and we can do go to market work on pricing work and then and help you with AI strategy. And so the total focus on middle market, exclusively private equity owned businesses or mostly private equity. Yeah, we, I mean we're happy to work for, for non private equity backed businesses, but what we found is that 99% of our work is, is for private equity firms and their portfolio companies. Yeah, well, hey, multiple expansions, dead debt and debt, you know, leverage pay down is dead operating efficiency. There's only so far you can go. In fact things probably going to get more expensive, a lot less expensive. So kind of margin expansion is hard. So it's all growth. I mean if you read all the, the reports, all growth, all the value in private equity is coming from growth, accelerating growth, maintaining high growth. As I think of you guys, it's bringing you in on the front end before, before you ever own the business, help you figure out whether you even want to own it, where the growth opportunities are. And I'm hearing now and with the new capabilities with the stuff you guys have done in the last 12 months is let's sit shoulder to shoulder with the private equity firm, the operators and the business and our engineering team to actually drive it to make it happen. Yeah. And then before you sell, make sure you check the math and have us run, do the same thing we did before you bought it and make sure the new buyer feels comfortable that the growth opportunity is still there. There. Yeah. I mean, now's a good, now's a good time especially to sort of really take a look at a business that you have that you've been in for three to five years and, and maybe you haven't done a market check. You know, maybe you haven't really gotten deep on your, on your pricing or go to market capability or you really don't have sort of validation that the AI progresses where it needs to be. Yeah, yeah. We have a tendency to like kind of re. Underwrite every deal every year. Everything changes so fast in software. It's like what we thought three years ago is useless. What are we trying to do now? No rear view mirror. Just go forward. But make the right decisions going forward and kill your darlings. Don't hang on to some strategy you thought was right that's now wrong. You're too stubborn to change. And having some outside influence to tell, like, hey, you're actually missing the boat here is helpful. So ready for the speed round? Let's do it. All right. You have to answer in the form of a question. It's like Jeopardy. No, I'm kidding. 12 months from now, which function do you think inside of a typical middle market business is the most transformed? Oh, that's not necessarily AI, but just in general. Maybe it's because of AI, but what is it? Well, I think the biggest opportunity is in finance. And you know, I have to laugh because my fairly new CFO spends lot of her time talking to Claudette and having Claudette do a lot of work for her in the background. And so I don't expect this to be a place where we reduce our staff, but as we bring in new platform technology and as we bring in these language models and their capabilities, I see our ability to sort of scale our, our work in finance and in particular put a much sharper lens on our business, just dramatically accelerate. And I think that's the opportunity. I think it's not on the cost side, it's on the business information side. You and I didn't plan this. I 100% agree. One, because finance is the furthest behind. Not in a bad way. It's Just the tools haven't been good enough yet. Where you would didn't spend more time auditing the answer than you did, you know, you could do on your own. So that's one, two is the tools are getting really good and in the middle market, lower middle market. Yeah. We already have pretty lean finance teams, right? Let me guess, got a pretty lean finance team. We have lean finance and the new CFO didn't come in and be like, hey, I need to hire five people. Right. Arap, you know, FP&A. All these things like, yeah, good luck, you're not going to get it right. What we have found is again, ceiling razor, not a floor razor. Our best CFOs are using the heck out of these tools. The third party tools are getting quite good. AI co pilots or kind of wrappers around Excel are getting quite good at auditing things. We may get to a place where like the bookkeeping is getting automated and then you're kind of to a daily close. I'm not putting this pressure on you and your cfo, but we will be at a place in the next few years, if not sooner, where you can do daily close hoses of the business, largely automated. So we're finding is our finance teams are doing things they never would have done before because they just didn't have time to do it. Right. Right. We've got. Cass has a calendar of all the time in a month. The CFO has the opportunity to be strategic and think all the big thoughts. Yeah. Not very many days in the month. Right. When you're closing the books and doing all these other things and reporting to private equity, et cetera, et cetera. There's more and more days in the month where your CFO and you could sit down and be really strategic planning the business largely because of these tools. So 100% agree. 12 months from now, finance will be the darling of most companies. Middle market companies of hey, look what we can do with these tools, in my opinion. Yeah, yeah. I mean, I'm super excited about it. I think if you've been part of a big company with a significant FP and a function, you sort of know what the art of the possible is. And most middle market companies don't have that. Yeah. Big companies are going to use AI to cut costs and small middle market companies are going to use AI to punch way above their weight. Right. All right, what do you think? A prediction for private equity, AI, whatever. Where we're at, other people would think you're crazy. Yeah, I feel like this is A bet I've already made. But, you know, there are so many AI native consulting models that are coming out that are all tech focused. And you know, if you talk to very experienced consultants and the people who, you know, engage with them in a relationship around, you know, important advisory, what it will, what it will tell you is the potential of those businesses reach a ceiling. And so I think there's a lot of automation opportunity in data gathering and data processing and maybe some assembly. What is still foundational in consulting is the relationship. And I think all these businesses that are sort of pure technology businesses, you know, will not supplant what is real consulting. You know, I know some of these founders out there, I think they're super smart guys. But, you know, the ones that I see being successful are tech platforms that are automating, you know, access to information, not supplanting, you know, real advice and real counsel around decisions. And the one thing they lack is distribution. And distribution's really hard. Hey, I've got this really cool tool. You don't need a consultant. You can do it yourself. And you're like, I'm not hiring a consultant for that. It's the whole jobs to be done thing. What are you hiring somebody for? What am I hiring this tool for? What am I hiring this software for? I'm hiring it to solve my problem. Yeah, I don't really care how it gets solved. Yeah, like, I trust you guys. Here's my budget, here's my expected outcome. Deliver it. Don't really care what else happens. I agree with you. I think a lot of these things wind up inside other things. But I'm also in the on record as saying enterprise software will domesticate AI. AI will not replace it. But you know, I'm talking my book too. All right, so you're a CEO, three time private equity backed CEO. You give CEOs of other private equity firms advice like what, what advice are you giving them right now on AI or anything? Sure. Well, I'm very humbled by the opportunity to do, do that. I would say AI is an enormous risk and an opportunity. And I'd say the first thing to sort of recognize is getting going in a meaningful way. And the CEO may feel like they have a conviction around this. What they really need to do is to look deeply into their business and connect with their team to ensure that that is not sort of falling flat somewhere in the organization, because it does take the whole organization. I'd say the next thing is, which is related is having a, you know, having a Plan. Right. So, you know, good businesses transform well, if they have a plan. And so hire somebody who knows what they're doing to help you build a plan. It's really hard to do it yourself. Get a specialist in your. Going to get much further, much faster and you're going to be able to have something that you can use. I think thing three is all of this needs to go somewhere carefully. We run a business that is entirely based on the quality of our work. If we drop the ball on the quality of the work, the business has lost its value. And so we must protect that at all costs while, while trying to sort of embed the opportunity with AI. And I know other CEOs have businesses they need to protect. And so the governance of how you embed AI needs to ensure quality as well as, you know, achieve things like velocity or efficiency, you know, in your objectives. So I think that that's, that's kind of the top three things that, that I would stay focused on. It's great advice. Let's end it on that. Matt, 27 years in the making. Look at us. We turned out okay. You better than me, probably. Thanks for being brave enough to come on and talk about what's going on in consulting with AI. I haven't heard a lot of conversations from CEOs of consulting firms who are in the mix right now, which one side of the trade is saying it's over, AI can do everything. And the other side of the trade is saying, you know, you still need the humans in the loop and we're all figuring it out real time. So the fact that you were brave enough to come on and actually talk about it in gory detail and give a bunch of other people advice, I think we are going to get a lot of benefit from. So I appreciate it. Yeah, thank. Thank you. I think this is a, this is a time when we have to, you know, have some courage and, you know, and really drive forward. Yeah. And thanks to you and your team for taking care of us at Parker Gale and our portfolio companies, likewise as a client. Thank you so much. Appreciate it. Neither this podcast nor any of the information contained here constitutes an offer to sell or a solicitation of an offer to buy any security or instrument in, or to participate in any Parker Gale Fund or other investment vehicle. Past performance is not indicative of future results and there is no assurance that any Parker Gale Fund will achieve its objectives or avoid significant losses. This podcast may contain forward looking statements. Such statements are subject to various risks and uncertainties. Parker Gale is an investment advisor registered with the United States securities and Exchange Commission. Registration with the SEC does not imply a certain level of skill or training. Guests appearing on the podcast may or may not be a financial sponsor of the podcast or an episode of the podcast. Parker Gayle may have business relationships with certain guests, sponsors, or organizations mentioned during the program. In some cases, guests or sponsors may provide services to or receive services from Parker Gayle, which creates potential conflicts of interest. Any sponsorship of this podcast does not imply endorsement by Parker Gale and is not provided in exchange for nor intended to solicit business between the sponsor and Parker Gayle. The appearance of any guest does not constitute an endorsement or testimonial of Parker Gayle or any fund. For additional information regarding Parker Gale, Please refer to ParkerGale's website www.parkergale.com or form ADV available@advisorinfo.sec.gov from the heart of Chicago to all over the globe, Couple private equity geniuses. They share what they know. They love to mess with technology where the future is synchronized or swim It's a private equity fund. Cast with Devin and Jim. Technology issues, middle market, PE backed companies. They bicker with each other and they don't take themselves too seriously. It's not venture capital, it's private equity. It's the private equity fun Cast. Pour yourself a drink and have a seat.