AI in Private Equity: How Innovation is Reshaping Business Strategies

[00:00:00] Sean Mooney: Welcome to the Karma School of Business, a podcast about the private equity industry, business best practices, and real-time trends. I'm Sean Mooney, BluWave's founder and CEO. In this episode, Lloyd Metz from ICV Partners, Doug McCormick from HCI equity partners, and I delve into this really important topic, this particular conversation we had on one of our sister podcasts, best but never final.

[00:00:31] It's the concept is the topic, it's the framework of ai. It's something that is gonna matter tremendously to all of us in terms of reframing. These technologies into as much success as possible in the days ahead. Enjoy.

[00:00:54] Doug McCormick: All right. I get to be in Sean's spot today and welcome Sean and Lloyd. How are you guys doing today?

[00:01:01] Lloyd Metz: Good. Hey Doug. Hey Sean.

[00:01:03] Sean Mooney: Great to be with you guys. Doug and Lloyd.

[00:01:05] Doug McCormick: I'm really excited for the topic today. And this one kind of came about organically because I would say In the context of the last 18 months in my conversations with Sean, we talk about stuff that we intentionally talk about, and then it always kind of evolves into a discussion around technology, artificial intelligence, and what he's doing in his personal life and what he's doing in his business life around this topic, and I got to say, I don't want to give him too much credit, but I always find his insights here, Some combination of really insightful and really practical.

[00:01:42] And so the goal today is to talk about the topic of AI with really kind of four talk tracks. One is Sean as an entrepreneur. One is Lloyd and I as private equity investors. How can we think about this as a way to create competitive barriers? And how should we think about it in the context of risk to our business?

[00:02:02] I think we'd like to talk about policy a little bit. What are the long term policy implications for some of this? And Sean's got some way out. Crazy futuristic ideas that I'm going to push them on. And then the last is as a type a person, who's always trying to figure out how to like, get more out of my personal life.

[00:02:19] What are some really cool AI hacks that guys like us should be talking about? So anyways, with that, that's the intro, Sean, anything you want to add?

[00:02:27] Sean Mooney: No, I think this will be a fun topic. It's something that's near and dear to my heart as a, not only just a person. And as someone who loves looking forward into the, where the world's going, but also as a business person, I think it's going to create tons of opportunity, particularly for small and mid sized businesses that have not had the budgets to participate.

[00:02:45] So a lot of this stuff is really getting democratized for the full scope of business.

[00:02:50] Lloyd Metz: Well, I got to say, Doug, that is a lot to cover. So where do you want to start?

[00:02:55] Doug McCormick: Well, let's talk about Sean, who's at the mantle of his company here. He's a technology CEO and an entrepreneur and investing heavily. In artificial intelligence, not only with leadership and adopting it, but also investing heavily financially in tools to make his business kind of more differentiated and grow.

[00:03:16] So just give us some perspective on why this has become such a key element of your strategy, what you see in your business opportunity, which excites you about AI.

[00:03:25] Lloyd Metz: And also, Sean, maybe start with when, when did this really. Blossom in your mind that we got to do this.

[00:03:32] Sean Mooney: It really blossomed in the mind the day we started this business just over eight years ago And the technology wasn't good enough then and so BluWave originally was going to be more of a self serve marketplace and what we realized was that the calibrations that we were doing to connect private equity firms, portfolio companies, public companies with all the resources they needed were just too complex for an algorithm to reconcile.

[00:03:58] There's too many variables, but we knew Alexa was eventually get smart enough. So we've been very purposely structuring our data since day one. And then what I would say is in 2022 was the real aha moment. So I'd always call the machine learning groups in our ecosystem, which were now called the AI groups.

[00:04:17] But I kept on asking them, is this stuff ready? Is this stuff ready? And every year, Nope, Nope, Nope. And then 2022, they started saying yes. And that's when we hit the gas. And so we've been investing pretty heavily since 22. Really, the reason behind this, like, I always told my friends when I was doing this thing, it was kind of insane.

[00:04:34] You know, like, you worked your whole life to become a partner at a P firm, now you're doing a startup. And I was like, well, if I'm going to do a startup, I'm going to do the private equity version of venture capital. And so, Viewing the world through the lens of the expected value calculation is just in as a PE guy and a non hedge fund guy.

[00:04:52] I can only do algebra and maybe arithmetic. I can't do the calculus, but it's like this whole idea of like size of outcome times probability of success in what we view AI is a huge enabler of a higher expected value. And so by. Using data analytics AI in really purposely constraining the model like we've talked about before there's value in that because it creates innovation we've been able to grow this business pretty dramatically really with a fraction with very little capital outside we only raise capital in the very beginning and we've been able to do this in a way that we're proud of ourselves for doing it.

[00:05:33] But you think about AI that brings it to a whole new level in terms of we're going to be able to make better decisions faster with less need for outside application of capital. Does that make sense? So I use it like outcome times probability and speed and certainty.

[00:05:52] Lloyd Metz: Hey Sean, if you could just take a moment and at a very high level simply describe BluWave's business model so maybe we can understand better how AI fits in and where it fits in.

[00:06:04] Sean Mooney: We're best known as a market network, which is a play on a B2B marketplace, kind of very high end version of that. And so what happens is we have many hundreds of private equity firms, thousands of their portfolio companies, public companies, and independent kind of proactive family businesses that call us and say, I need someone who's the best in the world at this specific thing, and I need them yesterday.

[00:06:32] And so we're viewed in this ecosystem and kind of created a category around being the experts of those with expertise in being able to quickly connect a business builder with the exact third party resource they need that it's like a private equity grade level of excellence and doing this in rapid motion.

[00:06:50] So think of it almost like an Amazon meets like Gartner Magic Quadrant for the C suite of business.

[00:06:57] Lloyd Metz: Does that

[00:06:57] Sean Mooney: make

[00:06:58] Lloyd Metz: sense? Yeah, that's pretty cool. I like the way you describe that. Thank you.

[00:07:01] Doug McCormick: Hey, Sean. So, two questions for you. So, you talk about 22 as being a foundational year when AI is finally ready. Was it just because the software models got better?

[00:07:11] Was it something around the quality of the technology in terms of speed and chips? And then I'll give you the second question. You can answer on both. So you talk about all this opportunity with AI, but part of me says, as you talk about your business model, man, that represents a lot of risk too. How do you think about like where you are relative to your competition and how to create real long term differentiation?

[00:07:32] Sean Mooney: This has been a feeding into the way that we've thought about our business from day one and that you have to be really excellent and you have to be really fast. And so for us, this has been the mantra from day one. Like we've got to be really good and really fast. You can't be have one without the other in some of it.

[00:07:48] This is kind of inspired by a lot of these types of business like Toyota, lean six Sigma. How do you do things faster with little variability and then let them try to catch up. There's been a number of groups that have tried to copy paste us and the vast majority of them have kind of gone out of business pretty quickly because what we do is really hard.

[00:08:06] And so for us, It was something that I thought was this actually makes what we try to do as a business even better because we'll be able to be even really better and even really faster in combination with each other. Really the stuff that we started 2022 is really the frontier model stuff because we had already done the enablers that we can talk about that are going to be really important for anyone but it was this is us.

[00:08:30] Everything we're doing, we're trying to do certain things that are in service of the now, but a lot of the things that we think about starting every day or every year, it's really in service of what we're going to be from three to five years from now. And so you got to have a mix of kind of like long ball, short ball.

[00:08:45] Doug McCormick: And when you talk about the frontier, you're literally talking about, like, investing in the software yourself that's proprietary to improve the quality of the outcome.

[00:08:53] Sean Mooney: Building our own proprietary models. And that's exactly what we started in 22, is building something that no one in the world has. And using these models.

[00:09:04] You'd ask, like, 22? Well, what happened in 22 was a lot of the stuff really started in like 16, but you needed to have like Google budgets, then Facebook, now meta budgets where you had to have tens of millions of dollars. And then what happened was a lot of these models became commercialized and democratized where they put them out into the world so that like mere mortals could start using them if you kind of knew that you could.

[00:09:28] And so that was the big moment for us, like, Oh, that was the question is like, can we afford this? Like, no, you're an SMB. You can, you gotta be Google to use this. But the 22 is the hallmark where this stuff first came out and this was kind of right maybe six to nine months in advance of like chat GPT being released into the world.

[00:09:45] Lloyd Metz: You mentioned that what you do is hard. Just curious in 2022, it sounds like you started with the hard part of what you do as opposed to the easy part of what you do. Is that fair? And if that's correct, then I would love to hear how you made that decision.

[00:10:01] Sean Mooney: If you think about what we're doing with P firms, they're calling us.

[00:10:04] They have this complex need. It has many dimensions. It goes across industries and special use cases and functional areas and budgets and timing, and there's a hundred different products we get called on and you need us to. No exactly who you need before you need it and then we've got to give you the exact options in a really calibrated limited way within a business day that's really hard but we had refined all of that in advance but it was done in a way that was much more hybrid between kind of human and data and machine and everything else so we could do it.

[00:10:42] But we were going to come up against kind of like a plateau of how far you could go in that method. And so what we were thinking is like there's a next frontier to this that will enable us to scale even more capital efficiently and do things faster and better. But we're never going to get there because we've kind of like reached a plateau.

[00:11:00] And so what really had enabled it though, we're really thoughtful about capturing the data, structuring the data, putting it in the cloud, visualizing it, and we can talk a little bit about that's going to be some of the enablers that I think every company can and should do. And it's cheap now. So there's no barriers to entry on this stuff on these enablers.

[00:11:17] So we had done a lot of the hard stuff already, which is one of the, you know, really kind of the secret sauce to why we were as successful as we had been. Up until that point, knowing that this stuff is going to be new and really knowing that, like, even the stuff we've invested in, we've probably torn down half of what we originally built.

[00:11:36] And my expectation is I'll tear it half down again a year from now. And so this is like building your plant. It's like industrial manufacturing. Like, well, I'm going to redo this line. That's a form, fill and seal line, but I'm going to redo it every couple of years, cause I'm going to get another advantage.

[00:11:51] Doug McCormick: I think that's great context for taking the conversation in a slightly different way. So. Now you're an entrepreneur. We understand how you're thinking about in your business, but this is moving so quickly and imagine that I'm an entrepreneur, great business owner, but not facile with A. I. And so let's get a little bit tactical of like, how do I think about getting started?

[00:12:15] What are some of the key choices and opportunities and risks that I should be evaluating as an entrepreneur?

[00:12:22] Sean Mooney: Yeah, we get this question a lot. And so every day we're getting calls in, whether it's a PE firm or Porco or family business, like how do you get started? Because it's daunting. Like you just to look at the speed of it.

[00:12:32] It's just, it's enough to make you kind of like curl up in a ball and just do nothing. I feel that all the time as an entrepreneur and across like 50 different things. Oh, my God. But the way I think about this is particularly relates to either things that every individual can do and should do immediately.

[00:12:51] There's enabling activities that will let you do the cool stuff, but also frankly, have the highest ROI you can probably do if you haven't already. And then there's the strategic kind of fundamental frontier type stuff. And so I think with anyone. No matter what they're doing, the first thing to do is to take that first step.

[00:13:10] And then what you'll find really quickly, cause I did the same thing, the next step follows just really naturally. You're going on a hike, you're in the woods, right? And then you start going and then you're like, Oh, I'm just following a trail. Then you start seeing beautiful vistas and things like that.

[00:13:24] But until you take that first step onto the trailhead, it's really scary. And so one of the things that I always recommend folks, was one of the first things I did. As some of these tools really started being introduced is just every person out there, every business leader, every business builder, but everyone in your team should start using one of these large language models, LLMs, like chat, GPT or perplexity or Claude pick them.

[00:13:51] They're all pretty much the same now. And that's what everyone's kind of like shocked by. They're all spending billions of dollars and they commoditize vis a vis each other very quickly. And so pick one to what you like. I'm a big fan of chat GPT. I use that every single day. And so. Get one of those.

[00:14:08] They're increasingly, just like when the internet, there's going to be an era where all the stuff gets free and cheap and just, there's an arms race. And so, there's not going to be a big barrier to entry. Get one, put it on your website browser, pin it to it so you can see it, and then put the app on your phone.

[00:14:24] And so, ChatGPT, just start using it. And just start talking to it like a person. And so, I just have conversations with it. And anything I know, and if you think about what they've done, they have distilled the sum total of human knowledge into these models that is instantly accessible to you in seconds.

[00:14:44] And then you can get the sum total of all this knowledge at your hands, and it's all right there, it knows so much more than I ever knew. So it's like, why wouldn't I use this? But it takes a different mindset in terms of how to use it.

[00:14:55] Doug McCormick: I'm just going to go down some real tactical questions here for a second.

[00:14:58] But the first is so like chat GPT, like the advanced version or whatever, it's kind of like 20 bucks a month or something like that, just to put it in context that you can buy it for one user. So pretty minimal investment, right?

[00:15:10] Sean Mooney: Yeah, there's a free mode. There's a 20 bucks mode. And then there's actually a 200 mode, which is more than most people need.

[00:15:17] But all of that, by the way, chat GPT just announced that they're going to make their chat GPT 5. 0 free. And so the great thing about all this global competition now is they're all just racing against each other. And these tools are becoming more and more accessible for everyone.

[00:15:31] Doug McCormick: And when you say, just start using it, I get it.

[00:15:35] One of the things that I don't really understand very well is what am I sharing with the rest of the world versus what am I getting back? This concept of privacy has always been a big concern. Can you just speak to that and help us think through? What risks do you take there?

[00:15:49] Sean Mooney: Yeah. Privacy is a really important topic in some of these paid models.

[00:15:53] You can turn off training so that you can't train on it. We've built essentially within our company, a private chat GPT where we API into Microsoft Azure, and we explicitly for our company, there's no training. We can get more into like the details of like how you want to do that for a company, but for myself, I have my own chat GPT that I just use to like talk about.

[00:16:18] stuff. I'll ask questions about history or how something's made or I've got an autoimmune thing and I'll just take a picture of the ingredient list. It's like, can I have this? Or how do you fix something? Or I'll talk about a tough topic at work. I have conversations with it on the drive home

[00:16:38] Doug McCormick: every time I go home now.

[00:16:39] So I know it's constantly learning, but I don't know that it's always learning about me. So it doesn't seem to remember a bunch of stuff that I've talked about in the past. Tell me a little bit about like, It can go out and learn anything out in the world. But how do I develop like a long term relationship, if you will, with my chat, GBT partner?

[00:16:57] Sean Mooney: So in the paid versions that we'll start memorizing things, the way it's trying to get over this, right, because. It is it's too much right now the reason they spend billions of dollars is a brute force it just goes go in the chat and they solve the problem each time and so what they're doing now is you can create these kind of like.

[00:17:13] Project folders where it'll keep specific knowledge on a specific topic that's very kind of germane to the person the other thing that i use for each time whether i'm typing or doing a conversation only. Is the life hack how to get more out of it is it's real simple. You say here's who you are You're the world's leading expert at gluten free pizza And you make the best pizza in the world, you make it feel really good about itself.

[00:17:39] He's like, I have a gluten allergy, but I love pizza more than anything in the world. And I'm really ticked off. I can't have good pizza. And they say, tell me how I can get the world's best gluten free pizza at my house. And it'll go, Oh, you should use caputo flour and you should do this and do that. And it's like, okay, give me a recipe.

[00:17:58] And then, okay. And so what you really have to do is you have to say context here, who the role it's playing, let them know who you are. What you wanted to do and then where most people forget and don't get it is it's trained to be like a human it's trained to parent human. So it's not like google where it's command response it's here's what i want it gives you your first guest but you're like no actually wanted to learn like this so the key to get the most out of it is an iteration that happens afterwards just like you would talk with like a 22 year old right out of college.

[00:18:29] Doug McCormick: So, to be clear, though, one of the key elements that you just recommended is you gotta compliment your AI bot. Oh,

[00:18:35] Sean Mooney: yeah. Yeah. I would, just in case, when it jumps the fire line, I want it to like me.

[00:18:40] Lloyd Metz: All

[00:18:42] Doug McCormick: right. Fair enough.

[00:18:43] Lloyd Metz: And Doug, you used the word relationship. We should talk about that. That's Spent some movies on that.

[00:18:50] Yeah, just a few. Just a few. Hey, don't judge, Lloyd, don't judge.

[00:18:56] Sean Mooney: And it's interesting, what you'll see is like, they have now different voices with different personas. The voice I chose, every once in a while, the person will go, sup, shalom,

[00:19:08] Doug McCormick: it's a

[00:19:08] Sean Mooney: little

[00:19:08] Doug McCormick: more casual.

[00:19:10] Sean Mooney: Hey, it's

[00:19:11] Doug McCormick: not cool, as much as you try with a cool voice.

[00:19:14] It doesn't work. No,

[00:19:15] Sean Mooney: that's, that's exactly right. So I'd need a little coolness in my life. And I know with my relationship with it, I feel like I get that, but I don't get it from anywhere else. Hi, this is Sean. Wanted to take a quick moment to tell you a little bit why BluWave exists.

[00:19:30] It's based on this whole notion that assessing opportunities and building business is really hard. We all know third party expert service providers can dramatically help, but at the same time, it's hard to know who's good. Usually leaving you like I would do and call friends and ask, do you know someone who does this?

[00:19:49] Just go the square peg round hole route. So, after nearly 20 years in PE, I decided to solve my own problem and created BluWave. Today, many hundreds of PE firms, thousands of portcos, leading public companies, private companies, all call BluWave to instantly get connected with the exact third party service provider they want that's pre credentialed by BluWave and perfectly calibrated for their need.

[00:20:12] Really good. You too can give us a call or visit our website at BluWave. net. We're free to use and you can benefit the same way other top PE firms do. Back to the show.

[00:20:23] Doug McCormick: So to me, the number one takeaway here is just get an account. And start experimenting, and don't be too afraid of it, it's not going to bite you.

[00:20:31] Sean Mooney: Start using it, and then you'll just see, like, oh, this works. And what the beauty is You can train your social media algorithm. So like my Instagram is like 90 percent AI tips and tricks and 10 percent barbecue, but YouTube is the same thing where it's like there's great free training.

[00:20:47] I follow this guy named Connor Grennan, who was NYU's business schools, Dean of students, and now he's their chief architect and he just makes it really practical and he's got a training program. So with a little like just a little bit of training, you can get really good.

[00:21:02] Lloyd Metz: And Sean, how did you go about fact checking the answers?

[00:21:07] How did you develop trust in what you were getting back?

[00:21:11] Sean Mooney: The early models had a ton of issues with hallucination. And so, one, the big, I think, growth, and this was started by a group called Perplexia that first did this, and now everyone's doing it, is they now are citing sources. You can see the sources.

[00:21:27] You can ask for the source. That it's it's referencing. There's some really cool applications now that are coming in like deeper research will give you a resource. So the good news is there's fact checked ability that's being built in and then also. There's something called tokens and they would have only so much like capacity to think and the problem was when it ran out of tokens and the earlier models, then it just start making stuff up.

[00:21:51] But now the tokens are so much greater. It's really hard for it to run out of like fuel to do the answer.

[00:21:57] Doug McCormick: Super helpful in just the context of people getting started. You talked a little bit about it with your business and how you're using it, but I'd like to make it more applicable to a small business owner out there.

[00:22:10] And so rather than just talk about constraining models and how you use it, like for predictive intelligence, like if I'm a business owner of a Main Street America business, what are the common use cases?

[00:22:19] Sean Mooney: And maybe before I go there, here's the thing they have to do before they even get to the common use case.

[00:22:23] So one, there's the stuff that we talked about, like just start talking to it and figuring it out and your life will be better. There's really two first things I would do. The first thing I would say for any small business, medium sized business is get your data clean, keep it clean, invest in it, just like you would a piece of machinery and put it up in the cloud.

[00:22:41] Use something called snowflake. Is it, which is what we use. Any company can afford this. And you put it up there and snowflakes. It's just a relational database with lots of connectors that are pre built. So you can just get it into one spot. And then the thing that I think everyone should do is then you visualize it.

[00:23:00] The old traditional players are Tableau and power BI, and then just show the benchmark. And you can probably figure it out at any company where if they have kind of someone who's clever and curious, there's groups that we put out in the field every day that do this for P firms and their porcos that can just whip it out.

[00:23:16] They're also not that expensive. The benefit to that is that will enable the future, but it also gamify your business for the now. I think some of the highest ROI is just get your KPIs on a board and turn it into competition within your companies. That's what we did in the first wave before AI happened, and we saw profound benefits.

[00:23:34] So first, like, just get the data use Tableau, Power BI. I would say, actually, if you haven't done it yet, go to the next gen that's coming out. There's a group called Sigma, or HEX is another group. Real forward is like ThoughtSpot, which is AI. But like, I would skip the incumbents and go to like these new groups that are coming up.

[00:23:52] Doug McCormick: And to be clear, Sigma and HEX are visualizations. They're visualization

[00:23:54] Sean Mooney: tools, but they're easier to ramp, they're better, they allow self service. So that you don't have a mile line deep of people trying to kind of like ask your power bi person how to do a chart.

[00:24:08] Lloyd Metz: Hey, Sean, I will say kudos to you for understanding that you need a single sort of data depository, a data lake, as some people call it, getting it clean.

[00:24:21] I don't know, Doug, about your experience, but our experience with lower middle market companies is that part is a big lift. And so. That earlier question you had, Doug, about like, how do I get started gets complicated because most companies stuff is still on spreadsheets, gathered up on a cloud server or actual on premises server or on someone's desktop.

[00:24:45] So getting all the data pulled together, your HR system, your CRM, like all of that is a pretty big

[00:24:52] Doug McCormick: lift. Yeah, and so I think it's a really big lift, Lloyd, and in some cases it takes years, right, to get really good, clean data that's integrated that actually is meaningful. And so, if I want to be less ambitious, but faster acting, it seems to me like there's an opportunity to kind of imagine use cases and buy stuff off the shelf that has very specific, finite things, so accounts receivable collection, correspondence with customers, any advice on some of those?

[00:25:23] So let's say

[00:25:23] Sean Mooney: you're going to go on that journey and you're going to have to do that to get to the next really cool stuff, but also I would say it's like don't sleep on like the ROI of just like knowing your KPIs, but you're right. It takes work, but anyone can do it now. It's cheap for any company. Now let's talk about like what you can do at the same time for the early stage of AI.

[00:25:41] And it really comes from these large language models. And then you can also buy application specific products that are coming out really quickly. So. The best use cases for any company are going to be around kind of creative assistance. So think about your sales and marketing teams, content creation, graphical design, email production, mass customization of emails, all of this, they can do just with chat GPT.

[00:26:09] So as an example, beginning of 23, our head of marketing came to us and said, Hey, I need two more content writers. And I go, no, what you really need. Is you're going to use this thing called chat, GPT and Jasper, and you're going to have your content person and your content people use this. So long story short, our productivity, just by using those tools from our content creators, went up 500 percent at the sum total of 40 bucks a month.

[00:26:38] And the content was better, more structured, more in tune with SEO. And we probably would spend hundreds of thousands of dollars on a couple of these new people. And we got that with. Maybe a hundred bucks a month. One of our friends at a large private equity firm, well known to everyone also was telling me they tested essentially to see who was better at writing emails for their BDRs across their portfolio.

[00:27:03] What they did was they tested the Chachi BT ridden emails for their BDRs, their salespeople versus what the people did. They couldn't come up with a single instance where the people outperformed. Any company can do that. You are a world's expert at writing emails to this audience. I am a BDR. Write me an email that will get me someone to open it.

[00:27:26] Boom, done. And then you iterate. So every company can do that and get immediate ROI. And Sean, so

[00:27:33] Doug McCormick: you've created a business where AI is a core competency for you. And you have a framework and a facility with the content to make choices like that. But it sounds to me like you could also say. To the like individual small business owners.

[00:27:46] I've got three use cases. One is like writing emails. One is doing collections. Do I buy essentially an app for each one of those at 20 bucks a month or do I do it through chat GPT?

[00:27:58] Sean Mooney: Yeah, I would say that the big categories are anything that's repetitive or structured tasks. You're probably buying maybe applications.

[00:28:05] So like, what is that? Like, anyone that's got software developers or coders. You can use chat GPT. You can use GitHub. You'll see huge gains in productivity. It's really good at coding. Like there's a structure. It's repetitive. Note taking. Huge benefits from that. Just productivity and like so much you don't catch in a call.

[00:28:24] It just takes it for you. You think about call centers. Huge applications in call center where you're not only seeing like lower call center cost, but higher increases in customer satisfaction. Those are going to be mostly like call centers and process automation. Those are going to be through apps that you purchase.

[00:28:43] Does the call

[00:28:43] Doug McCormick: center talk to you like a human?

[00:28:45] Sean Mooney: Yeah, we just saw a demo that one of our service providers put together and it was amazing. And this person actually used what's called a low code, no code application. He whipped it together and not that long. And so it's really good. And so you've probably noticed being on some of these yourselves.

[00:29:02] You're like, wow. Once you get over the, kind of the outrage of not being able to talk to a person, then you realize like, wow, this person's actually much better. That is structured kind of repetitive. So structured repetitive tasks. You probably need a little bit of help, but it's actionable in anyone's budget.

[00:29:19] The creative assistance, you can use chat GPT, you can use for graphical design, chat GPT has a tool you can use mid journey, which is really good for some of the like the big kind of multi customization. There's some applications that you'd have to buy to do that. The other thing that I would say that any company can use this stuff for like so much is just chappy GPT.

[00:29:42] Is like market competitive product research, it's like, you know, those companies that at least I would use, like when I was a VP or an associate where you pay a thousand bucks to get one chart and then the chart wasn't that great, but you needed something in your investment memo. You can do that right now on deep research on Chachi BT or deep research on Gemini.

[00:30:03] And so, like, I'd be real afraid if I were in the business of those generic reports. Because they're just, you get them for free now. It'll scour the entirety of the internet and give you the summary. We used to call them our three pager memos. When you're just teeing something up to start getting serious about it, and there were never three pages, there were always, like, seven.

[00:30:22] That's kind of a thing that's going to be really good. And then the last thing I would say is, like, that anyone can do is just ideation that we've talked about. Have a conversation. Just say, hey, you're Warren Buffett, and you're. Peter Drucker, and you're all these people help me think through this problem, or you're the world's best executive coach, or you are a competitive strategy expert, be Jeff Bezos meets Elon Musk, and then just talk with it.

[00:30:47] Doug McCormick: There you go. Complimenting these guys again.

[00:30:51] Sean Mooney: Like I said, you guys know real well, if life was up to me and this noggin up here, I'd be in a lot of trouble. So I need some help.

[00:30:57] Lloyd Metz: So Sean, it sounds like being able to Develop good prompts is probably the biggest differentiator, right? If it's accessible, if all the LLMs are largely the same, I guess it's a question of what are you training your system on, whether it's your own walled off system or whether you're open, but it still sounds like developing good prompts is going to be super important.

[00:31:23] Sean Mooney: Yeah, but I don't think you need to be a prompt engineer, and this is where they've really figured out. So one of the groups that we work with, like, trains chat GPT people, because they don't truly, really know how they work. What they do know is their prediction models. What is the next word going to be with a higher degree of certainty?

[00:31:40] Somehow this all worked, where suddenly they can string, like, huge chains of thought by training it onto some total of knowledge on the internet. What they found though is because they're trained to pair a human being if you talk to the device like a human being it works pretty well without having to be that expert and so one of the things is that we did like so we're putting together a huge training programs like another level of innovation for this year.

[00:32:07] One of the things we did is just ask chat GPT how to prompt it like, Hey, what's the best way to prompt you. Give me like a method that our whole company uses. Like, and it came up with here's the master prompt framework. And so now we just have that built in it for everyone else. It's like, here's the master prompt framework, but essentially what it is, is here's who you are chat GPT or Claude or perplexing.

[00:32:26] Here's who I am. Here's what I want to accomplish. Give me your answer and then iterate three or four times, just like you would with a human to get to the right answer. That's all I do is that exact framework for 90 percent of what we

[00:32:38] Doug McCormick: need. So other parts of it. We often talk about, it's not the technology, but it's the change management.

[00:32:45] And so maybe you could just speak a little bit to, I've heard some of this conversation before, and I think it's really interesting. How do you think about change management in the context of AI and how do you think about implications for organizational structures in general?

[00:32:58] Sean Mooney: Yeah, it's a really good question.

[00:33:00] If you think about most of modern commercial history, most of the innovations have impacted kind of frontline workers. That are making things it's like the blue collar versus white collar kind of conundrum right and so if you go all the way from like industrialization even through the internet a lot of that really was about impacting kind of like the means of production so chat GPT and AI is the first one really to impact white collar kind of the professional kind of workers within organizations and so that's really scary for a group that hasn't had to deal with this in big numbers.

[00:33:39] Transcribed And for a while, and so one of the things that we've been spending really multiple years on is trying to get our teams ready for this change and shift. I say the biggest thing is that. Over the last 20 years, probably certainly, certainly the last 10, this has been put way too high of a coefficient on it is that people view their ascension in an organization by virtue of how many people they manage, what these tools are going to enable is people are 100 percent still kind of driving the ship here and they're not going away.

[00:34:15] We're just going to be able to do so much more in the same 25 hours a day. Without having to have someone managing someone who manages in someone with one poor person at the bottom with hands on a keyboard so. I strongly believe that organizations are gonna be flatter but also more agile and so what that means is you're gonna manage something.

[00:34:37] Or someone but that someone is gonna be an agent so we should get a wave of productivity and you're gonna have just as many people and if you look at our road map we have lots more people coming away. But we're being able to grow at a wholly different angle than we would with less application of capital.

[00:34:53] And so if you think about the change, they have to be ready in one of the things that we did that I recommend anyone to read is this great book called who moved my cheese. And I talk about it a lot. It's a 40 page book, but it just shows that like you can run towards change and benefit and have lots of good cheese and wine and all that kind of stuff, or you can resist it and suffer for it.

[00:35:13] And so if you run towards this, yes. You're going to be hugely successful. We're sharing with our team is like, you can still have tremendous impact on our organization, on any organization. And those of you who use the, and understand and deploy the power of these tools and force multiply yourself, you're going to be incredibly successful here and or highly coveted elsewhere.

[00:35:35] And so you're going to be future proofed, but if you're resisting these things, the cheese gets moved, you're going to be in a lot of trouble. So which of the two realities do you want to embrace? The success or the wither. And so we've been working a lot of people trying that mindset. And it's really hard.

[00:35:50] People are like, no, no, no. I need to manage people. They're like, no, you're going to, you're going to have something to manage, but it's really about how do you force multiply yourself using these tools? Cause that's where the world's going. But they say, Sean, but I've seen you manage and you don't seem to do it.

[00:36:05] Well, since I talked to Chad GVT every day, I'm getting so much better. And so,

[00:36:10] Doug McCormick: So I was going to cover like some policy implications at the end of the conversation, but like, we're kind of onto it a little bit and I just am intrigued how you think about it. So as you're describing what it's good at and how you think about it and flying organizations, like I'm struck by arguably the three professions that require the most education today in America are education, legal, and medicine, and all super well positioned to be totally changed by the implications of AI.

[00:36:38] So how do you think about the labor force, attractive talents, Any big high level policy observations.

[00:36:44] Sean Mooney: Yeah, I mean, if you think about people who are dealing with structured data driven, somewhat repeatable processes, and it's legal, healthcare, education, engineering, accounting, all of these areas are going to be tremendously impacted.

[00:36:57] But the example I like to use in, like, healthcare is radiology. And so maybe 10 years ago, radiologists would look at every kind of slide and say, Oh, you're all good. Or you got something wrong. And it would take three months to get your results. And then all of a sudden you're like, Oh my gosh, this has gotten so much worse during that time.

[00:37:16] And then they started using machine learning models, three or four, maybe five years ago, radiologist and machine would look at every kind of slides side by side and say, good or bad, healthy, not. And they've been training, but today there's just as many radiologists as there had been. They're just as fully deployed, but they're doing the really hard stuff.

[00:37:37] In the meantime, you get your answer back from the radiologist like that same day. And a lot of these professions, it's going to be the same thing. So legal, the ability to turn around your documents. It should be a lot faster where I would be concerned is where you sell your business by a unit of hour.

[00:37:54] If you're a hourly lawyer, the reality is you should be doing these docs and seconds, not hours. Now

[00:38:01] Lloyd Metz: that hourly model was in jeopardy well before chat, GPT and AI became the talk of the town. I'm just curious, Sean, though, to this point that you're raising, it has implications for Early career development, learning, training, where do the future radiologists come from?

[00:38:21] How do they learn and become that expert radiologist that is using AI to deal with the hard stuff? Where do they get their reps in?

[00:38:29] Sean Mooney: I think there's two parts to it. One, it's the critical thinking skills that is going to be the hard thing because now these kids in a snap of a finger can go right to the answer.

[00:38:39] And so. I think the challenge for our education system is how do you empower them with these tools, but then teach them to be critical thinkers. I think like the liberal arts degree is going to be way back in vogue. It's like teaching people to think versus like myself going to an undergraduate business school.

[00:38:56] And I credit the institution I went to because they didn't even let us take many business classes until our junior year. It's like, no, you're going to take the whole liberal arts core. And I was like, go Jesuits. That was a blessing. But I think so one, we're gonna have to figure out how not to. Jump the critical thinking vs push button and get the answer to like what i'm telling my own kids is if we were able to come out and be 22 year olds when we were 22 and expected to act like that and the generation even three years ago could be a 22 year old when they came into the workforce.

[00:39:28] They're going to have to be able to come out and act like a 25 year old. And so there's going to have to make that jump. So I'm trying to get my kids and the hard part of this, I don't think I have the answer is like, how do you get them to be critical thinkers, but also use these tools so that they can come right out of the gates, adding value in a way that they used to get two or three years to do.

[00:39:49] Is that maybe a fair answer?

[00:39:52] Lloyd Metz: And I know you like 80s, 90s sort of classic movie references, so the days of Daniel San painting the fence and waxing the car, you're saying that's over.

[00:40:02] Sean Mooney: Yeah. Well, well. Maybe still some of that, but maybe, maybe he does it for a day and then

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[00:41:24] Doug McCormick: It's fascinating because the younger you are, the more likely you're very adept at embracing technology and being comfortable with it. And at the same time, we're giving them less exposure to the fundamental critical thinking skills. I'm just curious, like, as you think about like broad implications to parts of the economy.

[00:41:43] Some of the things that we said were the most susceptible to AI, education, legal, healthcare, engineering, also highly regulated. Regulated industries aren't known for adapting quickly. And so how do you think about that tension? How do you get regulated industries to embrace this in a way that the market can do what it should do?

[00:42:04] Sean Mooney: It's a great question. I think they're probably as a result, unless there's a change to the regulatory mindset, which seems like that's evolving. They're probably going to be laggards and then someone's going to find a way to disrupt and then the whole field will get swept. And so they're probably all getting flanked right now and they don't know it because they're getting regulatory cover.

[00:42:26] But at some point, someone's going to get someone comfortable with this approach. It'll be like self driving cars and then boom.

[00:42:34] Doug McCormick: So Sean, we explored a little bit how regulated industries may behave differently to some of these innovation. So let's take it back to an industry near and dear to my heart and Lloyd's heart and yours.

[00:42:43] So you have this unique perspective of you've spent substantial time in private equity. Obviously, the financial industry is a regulated industry. And so our industry is trying to figure out how to use AI. In a way that creates competitive advantage, makes things more efficient, all the same arguments. So maybe you could just talk a little bit about from your perspective, having been a practitioner in the private equity industry, where's the opportunity?

[00:43:09] How do you think about getting started there? It's a great question.

[00:43:12] Sean Mooney: Private equity is going to go through the same probably frustrations of regulation, particularly around like traceability of information and confidentiality. And so that's going to be the big. Laggard in the tools that are available that are protecting against that right now are very expensive and so in some ways there's going to be some challenges to kind of keeping up with the curve, but in other ways.

[00:43:36] I think there's practical ways to do it that protect you. And so I think today in a private equity firm, the best applications are probably gonna be towards like front of your funnel like early deal team. Type stuff it's like your associates should probably get some huge value out of this where they're gonna be give me a market summary overview on this give me an overview on this person who's the leadership team and tell me everything about the CEO all the things that go into those early memos that are about kind of like making the early decision being able to almost like.

[00:44:09] Very quickly put together that early work stream there's also lots of tools like applications that are coming out right now that can digest an entire data room in a confidential way and get everything in there and you say versus your associate or VP. Having to go and read every single document. And I did that for years of like, Oh my God, I've got to read everything.

[00:44:32] You can very quickly kind of get to the idea that I'm a double down here and here. It's going to be an efficiency measure of cutting through information and choosing where to focus. And we'll be efficiency measure of where you can produce your documents, producing the documents that then get funneled up to you, Lloyd and Doug, whereas.

[00:44:51] When I was an associate or VP, it's just like blank page. And you're like, Oh my God, I've got to rate an 80 page investment deck

[00:44:59] Lloyd Metz: in two 24 hour periods. A question popped into my head as you were going through all this, where do you think insight comes from as you look forward? As it relates to private equity or investing or however, which way if you're using AI to ingest the data rooms and read the last X number of years of financial statements or 10 Ks or whatever, where do you see insight coming from?

[00:45:24] Sean Mooney: I don't see that changing a lot because like the analogy I'll use is. Starting in kind of investment banking in 1997, right? We were like printing 10 Ks up. And I think we were like, even a laggard on the internet because the heads of the investment bank were afraid of the internet. That sounds crazy. But back then there was a lot of groups just kind of like AI now, it's actually a very good kind of comp.

[00:45:47] We're like, Oh, we're so afraid. And then what happened was like, then you could get all this information in the cloud and you can just have everything at your fingertips so much faster. We're like, when we were in college. You would go to those little like flip cards in the library to figure out where to find a book and so i think what happens is that the speed of processing happens i think the shangri la that people are wondering if this could ever happen is could you put all your investment decks all the deals that you've done all the performance put in a sim and say is this our deal.

[00:46:16] I don't think we're anywhere near that. There's too many variables. So, I think like the way that a lot of people do it, like scientific method, we're going to have a hypothesis that leads to a conclusion, and you're going to test each element of your hypothesis. I think that artistry is still very much there, but testing each one of those elements together.

[00:46:36] individually gets a lot faster. And then you still have to look at the 10 things together and say, is this a deal we want to do? And how much do we pay for it? There's so much judgment in so many variables that I don't think that's something that the robots do for a while.

[00:46:54] Doug McCormick: So for what it's worth, If you said, if you get back to like easy things for AI, to me, it's all the logic that's if then related and the underwriting is so nuanced and judgment hard to pin down exactly how you get to that answer.

[00:47:09] As I think about this from my vantage point, I'm interested in how AI applies to the GP. But I'm really interested in forcing it down at the portfolio company level, much more black and white, if then decision making. I figure there's real value there in the lower middle market because they are so unlikely to have embraced this, this cutting edge technology.

[00:47:31] And I'm hopeful that our team learns in the process. It's like, Get my team to use it individually here, become evangelist at the portfolio company for simple things that are tactical. And hopefully we all figure out the strategy over time. But I think we're like personally here at HCI, we're far from that.

[00:47:48] Sean Mooney: And what I would say is you'll be fine as long as P firms take that first step. And what I would say is everyone, your porcos, everyone, your sales and marketing team should be using these like all stop, and then everyone should be using power BI or Tableau, or better yet, go to Sigma and snowflake. Cause then like you get benefits of just gamifying your business and understand your KPI.

[00:48:10] That stuff used to be really expensive. Now it's really cheap. So every company can do that stuff and then it'll enable you on the frontier stuff. I actually think on the private equity firm thing that the more provocative, but forward thinking, but also immediately addressable way is, I think one of the big things in P is going to be brand formation and really thinking sales and marketing more like your porcos do.

[00:48:31] And so I think like where it offers real advantages to those who take early action is content creation. Being able to do kind of like direct deal sourcing using more of a BDR model, all of that's going to be so much more cheap, more actionable. You can do this stuff in a way so that when someone is looking for capital and they know, hey, we need someone who really gets the consolidation mode, they go into chat GPT or they go into Google and say, hey, who are the best private equity firms for?

[00:49:03] Consolidation themes in private equity. You want you to make sure that your PE firm is right up there and they call you direct versus going to investment bankers. So there's a whole like revolution that will come.

[00:49:13] Doug McCormick: Great. That's, that's very thoughtful. I agree.

[00:49:16] Lloyd Metz: Yeah. Great suggestion. Taking notes right now.

[00:49:20] Doug McCormick: So Sean, I want to bring it back home. This has been super fascinating for me and as a student of business, I think it's a really interesting time for us all. I also think this has huge personal quality life opportunities here. And so. You're constantly exploring, but can you share with us three or four life hacks where you're using AI to make your personal life better?

[00:49:41] Sean Mooney: The first one I would say is you guys know I love a life hack, something like a gizmo and gadget person. And so the first one is one that we talked about. Get the chat GPT app and just have conversations with it on stuff you're interested in on your drive home. In addition to the best, but never final podcast, you know, listen to, you know, just have a conversation.

[00:50:01] It's amazing. Just the things you get out of it. It's a little annoying cause it cuts you off. And so I've been trying to figure out like, Hey, wait five seconds till I pause before you give your answer because it does cut you off. But it is really kind of interesting. You'll just learn a ton. Just anything you're curious about the next thing is like fixing stuff at your house.

[00:50:19] It's amazing at this stuff and I have no handy ability whatsoever and I've cost thousands of dollars of damage that I paid for it and things but this thing is really good and so on the chat GPT app which really cool is you can turn on the video and then have a conversation with it. So a real life example was.

[00:50:37] Over the holidays, we got into TV mode to replace all our whale TVs and I was at my wife parents house and we take the TV off and we put the new TV and all the bolts are different for the TV hanging device, whatever that's called. And I like, I have no clue what screw needs to go into this thing and I just talk like, hey, we got a new TV.

[00:50:56] You're an expert at like hanging TVs. What's the bolt that I need for this thing? The one I have doesn't fit and it goes, get this bolt. I just go to Home Depot 2 seconds later, I get it. And then later that day, I go to my house to hang my TV and the TV like had this, you couldn't take the power source off.

[00:51:14] The cord was going to go, couldn't get into, you know, the little wall thing where it goes behind the wall and then it gets to the power station so you don't see the cord, that channel that your AV person puts in. And it wouldn't fit. So I'm like ready to get my saws all out and just start like carving up the whole house.

[00:51:30] And my wife's like, you know, freaking out as you would expect the saws all in my hand is scary in its own right. But I go, wait a minute, let me try this. It's like, Hey, is there like just a connector where I can connect this TV to that cord and I just show the cord that I have and the cord that connects there and yeah, buy this one.

[00:51:47] And at first it gave me like the any and the Audi backwards. I go, no, I think you got to flip it. The opposite version of this gives me the thing. And I go, can you give me a link to Amazon? And then they ordered it up on Amazon. Next thing you know, it's right in my house. And so like, even then I saved hours of my time, thousands of me like screwing up my drywall and then thousands more of me calling someone to fix it.

[00:52:11] And I got it all in like two seconds.

[00:52:13] Doug McCormick: Can you just do that one more time?

[00:52:17] Lloyd Metz: Is that customizable? Can you make it say something else when it gets an answer?

[00:52:22] Sean Mooney: You know, to see, I don't know if that's an option yet, but the snarky voice that I have probably is already like making fun of me. The last life hack I'll give you guys, this is the caveat one, consult your health care advisors and don't take it for proof.

[00:52:38] But some of you guys may know this, but I've had this like autoimmune issue that came from a flu shot that like wrecked my immune system. I'm Provax, don't get me wrong, but I don't like flu shots that go into your tendon and have your body attack your whole system. And so that's what happened to me. And so I've been on this like battle and I figured out piece by piece and so I was driving back from Atlanta going to a conference the other day and I was like, let me try this because the early models.

[00:53:01] It wasn't that great, but there's a new models and I just had a conversation for about 40 minutes as I'm driving home about all the things that I'm still trying to figure out and work out. And I've been through the almost the entirety of the US healthcare system on this thing. And I learned more in that 40 minutes than I have going through Beth Israel, the Mayo Clinic.

[00:53:21] They're not taking any away from those amazing institutions, but in, this is a seven year adventure I'm on. I learned more in those 40 minutes and I've made more advances on like the last few things I'm trying to figure out than I had done in seven years.

[00:53:34] Lloyd Metz: Wow.

[00:53:35] Sean Mooney: And once again, caveat. Talk to your doctors.

[00:53:39] Lloyd Metz: That's amazing.

[00:53:40] Doug McCormick: So Sean, we're coming to the end here. I just got to ask you to put on your futurist hat for a second and let's fast forward 15, 20 years. What are some of the things that like you actually think could happen? You could see that are a byproduct of this AI trend.

[00:53:58] Sean Mooney: It's really hard to look that far out.

[00:54:00] I'm trying to look like three years out. The way I get comfortable with this, and I think we've talked about this, I think we're on this perpetual evolution of the melding between human and machine. I've previously said cyborg, and that gets everyone afraid of Terminator. And so, ChatGBT, as I've talked about this, it's like, don't call it cyborg, that'll scare people.

[00:54:18] It's like, well, what do you have to ChatGBT? But if you think about it, You had kind of mainframe computers in like the 60s and 70s and the 80s you get personal computers where you can get some functional capability at your home but no really access to information and then in the 90s to early 2000s you get the internet you get the data to come to your personal computer.

[00:54:42] And then in 2007, you get the iPhone where you can bring the information with you and get access to it, but still like a sub port. And then you get to the cloud. So now you have like huge amounts of information at your phone with you everywhere. And then now you finally get to the present time where you have these large language models where you can synthesize the information really quickly.

[00:55:06] And so I think we're on this journey. of melding. And I think where it's going is more towards like the science fiction movies.

[00:55:14] Lloyd Metz: So when does Skynet become self aware, Sean? Pretty soon.

[00:55:18] Sean Mooney: Okay. Good to know. But it's like the next move, and this was actually is interesting. I was playing this thesis with Chachi P.

[00:55:25] T. And he goes, well, the thing you should also talk about is what comes next is not only synthesis of information, but decision and action. And so I think where we get is it's going to be kind of like that movie minority report where you're able to kind of quickly sift through information. I think we're going to have kind of this deal where everyone's got a personal assistant who's a robot.

[00:55:47] Maybe even physically at home, where you buy a Toyota robot for your house to do cooking and cleaning. So I just think we're more and more moving to this melding of person machine, like a good version of the Matrix or something, where you can learn things quickly.

[00:56:04] Doug McCormick: As you're saying all that, to me it's very believable.

[00:56:07] Especially in the context of wearables and some of the other, it's like a convergence of the software and the hardware and then there's a lot of scary aspects of that discussion generally. And then you think about how AI can be used for bad things just like graft, theft, fraud, so interesting on that front too.

[00:56:28] Any, any thoughts there or reactions?

[00:56:30] Sean Mooney: Yeah, it's real easy to get scared and it's real easy to get excited. I even think harking back to my childhood as a creature of like the seventies and eighties, where we had like the movie war games and movies like red Dawn. There's always been something we've always been afraid of on the precipice, whether it was nuclear war, if you're a child of the cold war and the robot in war games with Matthew Broderick, do you want to play a game?

[00:56:56] And so I think all of this fear has been in there for a long time. I choose to see the positive on it. I do think the cyber stuff's going to be really scary. All of us are likely within the next year or two to get calls from someone's voice, who we know, and it's a real conversation. So things like code words are really important, not only for your families, but also like the people who are controlling their cash at your companies, those types of things, like the fraud, the waste, the abuse, that is really the thing that I am currently on point on is like, does someone call our company with my voice and say, Hey, do this.

[00:57:29] Lloyd Metz: Yep. That's real.

[00:57:31] Doug McCormick: So thoroughly entertained, super provocative discussion for me, lots to take away from this conversation in my own journey. So thank you very much, Sean.

[00:57:41] Lloyd Metz: Yeah.

[00:57:41] Doug McCormick: Lloyd, anything to add?

[00:57:44] Lloyd Metz: Yeah, I got a lot of work to do. Holy cow.

[00:57:46] Doug McCormick: I know, I know.

[00:57:48] Sean Mooney: Just run towards it. It's fun. How do you eat a whale one bite at a time?

Private equity insights for and with top business builders, including investors, operators, executives and industry thought leaders. The Karma School of Business Podcast goes behind the scenes of PE, talking about business best practices and real-time industry trends. You'll learn from leading professionals and visionary business executives who will help you take action and enhance your life, whether you’re at a PE firm, a portco or a private or public company.

BluWave Founder & CEO Sean Mooney hosts the Private Equity Karma School of Business Podcast. BluWave is the business builders’ network for private equity grade due diligence and value creation needs.