Artificial Intelligence Podcast: ChatGPT, Claude, Midjourney and all other AI Tools

Is Artificial Intelligence Changing The Face of Private Equity With Lindsay Guzowski

• Jonathan Green : Artificial Intelligence Expert and Author of ChatGPT Profits • Episode 368

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Welcome to the Artificial Intelligence Podcast with Jonathan Green! In this episode, we delve into the transformative impact of AI on the private equity space with our distinguished guest, Lindsay Guzowski, a seasoned expert in leadership assessment within private equity.

Lindsay shares her insights into the current AI buzzword phenomenon, emphasizing the need for discerning genuine AI capability amidst hype. She discusses the challenges and opportunities in leveraging AI for leadership assessments and private equity investments, highlighting the importance of integrating technological advancements without losing human touch. Her perspective offers a refreshing look at deploying AI to enhance decision-making rather than replace human intuition and experience.

Notable Quotes:

  • "AI is the hot buzzword, but 80% of what people are throwing money at isn't going to pan out, and we didn't want to be a part of that." - [Lindsay Guzowski]
  • "People still want to buy from people. They still want to talk to people." - [Lindsay Guzowski]
  • "We see a lot of excitement. The more exciting something is, the more it trends on social media, the less useful it is." - [Jonathan Green]
  • "The purpose of AI is not to decrease human interaction but to allow us to do more." - [Jonathan Green]

Lindsay underscores the role of AI in augmenting intelligence rather than replacing essential human elements in private equity. She cautions against falling for the AI hype without thoroughly understanding its capabilities and limitations and emphasizes the continued necessity for critical human insights in investment decisions.

Connect with Lindsay Guzowski:

If you're interested in understanding how AI is reshaping private equity and want expert insights on maintaining the balance between technology and human touch, this episode is a must-listen!

All links for Lindsay's work and contact information are available in the show notes below the YouTube video.

Connect with Jonathan Green

Artificial intelligence is changing the face of private equity, and we're gonna find it all about today's amazing special guest, Lindsay Guzowski. Welcome to the Artificial Intelligence Podcast, where we make AI simple, practical, and accessible for small business owners and leaders. Forget the complicated T talk or expensive consultants. This is where you'll learn how to implement AI strategies that are easy to understand and can make a big impact for your business. The Artificial Intelligence Podcast is brought to you by fraction, a IO, the trusted partner for AI Digital transformation. At fraction a IO, we help small and medium sized businesses boost revenue by eliminating time wasting non-revenue generating tasks that frustrate your team. With our custom AI bots, tools and automations, we make it easy to shift your team's focus to the task. That matter most. Driving growth and results, we guide you through a smooth, seamless transition to ai, ensuring you avoid policy mistakes and invest in the tools that truly deliver value. Don't get left behind. Let fraction aio help you. Stay ahead in today's AI driven world. Learn more. Get started. Fraction aio.com. Lindsay, I'm so excited to have you here because we've had some guests in the past that are in private equity and we talk a lot about how they audit AI companies and sniff test because it's five years ago if you said NFT, you got money now. Then two years ago if you said meta, you got money, and now it's as long as you say ai. We're even seeing companies pretend to have AI and get funding and they're just showing that it's just a bunch of VAs in a call center. So I'm really fascinated by how you sniff test, but also yeah, how you're actually impacting AI in your approach. Because one of the things I've noticed, and I know this is happening a lot in the hiring space. If you post a job on LinkedIn and you say remote, you're getting 600 applicants that're all AI generated within 10 minutes. And I have a feeling something similar is happening with people blasting out pitch decks on autopilot in private equity and in investing spaces. And it's like my AI will write the pitch, then your AI will read it and it's like there's no human involved and I'm really interested in all of that. So just take it away. Yeah. Thank you for having me here. I'm really excited to chat through all this. I completely agree with you right now. AI is the hot buzzword and one of the really interesting things with the Crucible is, we do leadership assessment for private equity and engaged in the diligence from that aspect of it. When we constructed our base model. We used a lot of machine learning techniques, but we're very explicit that it was machine learning and not ai. And people kept saying if you just call it ai, you'll get more money, you'll get more investment, you'll get more people interested. We were like, yeah, but it's disingenuous and also fairly convinced that, 80 plus percent of what people are throwing money at with an AI tag on it is not going to pan out, and we didn't wanna be a part of that. Bubble that was going to be thrown to the side. But what is interesting is that there are unique and creative ways that you can use AI to supplement, augment, and improve a lot of these products. Even when we're writing our code, we've used some AI to help us do that in a faster way. We've gone. One of the things that we said when we pioneered this project was that we didn't wanna be coaches. We're data people. We're excited about writing a software. We're excited about the diligence side. My background's in private equity. I'm not a career coach. And so in finding insights for leaders and teams, while we have phenomenal insights, the so what of it? We can produce the reports. We do those things. We then partnered with another group as a part of the PL three Alliance to create a product called Sage Forge, that then looks at sentiment analysis and understands what employees do, and then we tie that to valuation. But the plans that come out of that are actually created through generative ai because we can go across, huge amounts of data. To figure out, okay what are you actually telling us? Not just what do the results say? And what's cool about that is that you're able to take insights, turn them into actions, and then people, legitimate, tangible people can implement them. And that's the, I think, best use case of AI in this space is to make things that are happening in private equity easier. But not to replace that human insight, that human touch that makes businesses great, otherwise everything's gonna become similar and mediocre. Yeah. One of the challenges today, I'm glad you brought that up, is that if everyone has the same button that you push and everyone gets the same result and nothing especially unique anymore, and correct information becomes a commodity, and I have. Seen a lot of this and I love that you brought up so many companies that get investment are really popular for a little while.'cause they throw AI in the name and I find it really interesting 'cause I always I mean they about this a lot and it's there's two types of companies. There's companies that's doing something really cool and there's company solving a problem and it's about 80 20, right? And the 80%, it sounds really cool. And I'll ask them what problem do you solve? Then they go we actually do this and this. I was like, but if you don't like the companies that survive the downturns. Yeah. I built a couple of software tools myself recently to solve problems for myself. And then if other people are interested and they've actually started to get some legs. But I start from that point, I'm like, yeah, I built it for me and it solves my problem. If it doesn't solve my problem, like one of my tools, I was just testing, it's not ready. I'm not gonna release it till it works perfectly for me. And that is a very different than you see. We have this cool idea that's a feature and it's very interesting to you and we've seen this I know this is like the second or third AI bubble we've seen like machine learning bubble 10 years ago, then all these different phases and we see like they've tried to do virtual reality many times and they keep trying these different versions and it's always that. It's okay, if I'm doing my work wearing a headset. What does that, how is that better? Do I do more work faster? Do I get work done less? And it's no, but your neck hurts at the end of the day and your nose is really sore. It's those are bad benefits. Like the idea of wearing a headset is it's, there's a physical cost to it. I get really dizzy. I cannot do it. And the thought of being in a virtual reality headset for an eight hour workday okay, great. That's why, and there's that's why those products disappear. So I really think that's very interesting that you start from the data driven approach. Yeah. And a lot of people don't know the difference between machine learning and ai. They think it's just Yeah. The same thing. And also one of the struggles on this show is that the definition of AI has gotten so broad. It used to mean like sentient computer, right? It meant computer that wanted to roll the world and now it means. Pretty good word processor or something that can make images. So can you quickly give your definition just for everyone listening, like the difference where the line is between machine learning and when it shifts to ai? Yeah. I think that machine learning is about statistical techniques that can help simulate and aggregate data and extract some insights from a specific data set. Data, data window that, that ability to make that analysis easier in, truly using some of those statistical statistical models. The AI side of it is when it gets into predicting text, when it gets into thinking about, okay, how do I scrape. Scrape concepts, learn from those concepts, and then take that back into developing something quote unquote new or at least replicated in a real-time fashion. And I think there's a big distinction there because one is about creating a tool that can help you gain more insights more quickly. Another one that you could absolutely do all the same things if you just did it out the way we traditionally did. My background's in quantitative sociology. I can't tell you the number of hours I spent in various computer labs, writing various lines of code to try to analyze these things that now I could do in 25 minutes. But when you truly get into that AI sense for me. It's about taking something that is a level beyond that. It's something I could not have done. Something that involves somewhat of that black box of, a truly nascent information that's being pulled from somewhere. Thank you so much for explaining it. I think that's really helpful to see that part of AI is the creativity element. The benefit is that it can be creative, but it also means that there's an inconsistency, right? So that's where you start to get risk, where you ask the same question 10 times and one outta 10 times. It gives you a different answer, and that's one of the challenges when I'm building or working on projects, is trying to get the creativity without getting it to go outside the line, to color outside the lines. One of the really interesting things we're seeing is that even though everyone says they're data driven, it really seems like even now a lot of investing is relational and emotional. Like you get excited about a project and very rarely is it. Is there a full logic chain? It's like a lot. It seems like a lot of investing is like fomo and it's what if it works? And we've seen that with a lot of companies like that. In last year there've been a couple of AI SPACs and it turned out they just put AI in the title and there's no AI component at all. They did massive raises and now we saw a company that faked all their numbers and had no AI component at all. Just a call center. So what is the core element or the value of an AI in a company and what are the kind of things when you're doing your data analysis that. Move the emotion out of it and first have that logical step which go, wait, before we get excited, before we fall in love with this business, what are the things we look for that we can look for statistically that are signs that it's going in the right direction or the wrong direction? Yeah, I think that's a really interesting question because as much as people say, they're very data-driven and private, equity's an interesting space because there's so many numbers and those numbers are. Often directional and often can be manipulated. And when I was on the deal side doing the analysis, while I was in my MBA doing my internships and things like that, I come up with the numbers and I come to the investment meetings with my presentation. I'd start talking about the leadership, or I'd start talking about the fundamental business model, or I'd start talking about, the supply chain and I'd get stopped and they're like no, but what are the numbers? The numbers can say whatever I want them to say. I put in a four times return, and so it looks profitable. You put in a two times return and it's a less good deal. How do you know what's gonna happen unless you can talk through the fundamentals of the business. And I think that's what gets lost when you're investing in a bubble. Is that people don't know what those fundamentals should be yet in some of these areas. And so when I'm looking at, and I actually recently invested in an AI based business. I looked at one, to your point earlier, what problem are they solving and how do they go about doing it that I can't do through a combination of existing tools. So then you get into, okay, what's your cost structure? How are you thinking through this? What are you doing that is going to make this replicable, scalable? All the other things you look at, if you were talking about producing widgets, and I think at the end of the day you have to get back to some of those fundamentals of do you have the right leaders in place who can take this forward? Do you have the scalability of your teams? Are your margins going to be appropriate? Do you have a growth path that isn't relying on this bubble or concept or the idea that, AI's taking over everything? And how do you ensure that what you're doing isn't replicable by eight other groups, or if it is, how do you do it better, faster, or with. A more compelling pitch. And that's where I think it, it really looks at the end of the day, like every other investment that you're going to look at, but people are wildly emotional in a space where people think they're very data-driven. And it's actually probably one of the worst kept secrets in the investing world is how much data there is and how little it's used at the end of the day to make the decision. Yeah. One of the things I've seen having now worked with some VC projects is like words have no definition. So I work on a project and they said, we have this many users. I said what's a user? Yeah. Because I know daily active user and I know paying customer, right? And they were like anyone who's ever given us their email address. And I was like, that's Oh. I go, okay, so you're maximizing, you wanna give the biggest number possible, right? So you, and there's all these things that happen. And then of course, two companies will both become customers of each other to increase the number of customers they have. I'll spend a hundred dollars, you spend a hundred dollars With me, now we each have one more customer and our revenue, even though our net is identical and a lot of this. If you are just looking at numbers and you don't pay attention to what's the next to the number, right? There's a huge difference between daily active users. Monthly active users. Yeah. Total users and like customers. I've worked on a project where they considered a free trial person, a customer, and I was like that, and I'm very old school, so I come from, I don't, I've never taken investment for how I build companies. I only have money if I make it. So to me, I've had employees, I had an employee who was in social media, and he was like, here's our reach. And I go, cool. That's not a real number. Reach is like how many friends I could have had in high school. And I was like, my reach was 400, my real numbers was three. So it's really different. Like I could have been friends with everyone in high school. I wasn't. And it's like my favorite metric starts with a dollar sign. Yes. Because that's the concrete thing. When you're taking this approach, how do you pull people out of the emotion? Say, and that's the thing that's really important. I've always known this and I was like, all numbers can be, you can make any number look good or bad, right? It's all about how you describe it, how you modify it. So I see that a lot of, like startups get excited and people get excited, but they don't have what's the correct structure? What is the structure for the right type of business. What's their business model? What's the type of customer they're seeking? What's the path through revenue? It's yeah, but it's so exciting to have ai. So how long, maybe, this is interesting. How long do you think the hype cycle for AI will last before we have enough failed investments that people will go, let's stop throwing money at it? Let's start going back to being a little analytical again. I think it's gonna be a question of how much overhang continues to exist in the investing space. So right now there are trillions of dollars that need to be invested and a lot of businesses that aren't being sold right now, because they were, they've been owned by these VCs and PEs for seven plus years. They're not returning that money to the investors. The investors are saying, okay, but you have all of our money that you're not deploying into new stuff.'cause you're telling us that nothing's on the market. So then people are excited about things that aren't real. That's going to create a pretty significant wash and a loss of actually a fair amount of value for people if people are overhyped. And so I think that. Hype cycle will go on a little too long. If fundamental businesses and things that people bought, just pre COVID aren't being sold in the next, two, three quarters. I think if they do start moving things out of, a lot of those roll-ups that were done of, service companies and other things that got really hot in the PE space, if they can start moving those. It'll put a damper on the AI hype cycle because they'll be able to invest the money in things that may require a little bit more diligence or may require a little bit more risk taking, but risk taking based on some old school fundamentals as opposed to some hype, which. I'm not confident that's gonna happen. So I think that you're looking at probably a little too much hype and a little for a little too long. I think also every time you get a big win out of AI, that's going to elongate What's happening here and what's hard on that front is that AI can do some really cool things and there are great use cases for it. I used. I used an AI tool earlier this week to help develop some messaging for a secondary ICP that we were trying to figure out, okay, how is this message different than the message we typically use when we're pitching? It was a great application of that. It was limited. It was easy, and it was protected because it wasn't going out to everyone and their brother with the information I was providing. But you have to be aware of that, and you have to understand how to utilize these tools in the right ways. But I think every time there's a big, public story about how there's a phenomenal new AI company, it then inspires people to feel like they're missing the boat or that, if they only could have invested in Amazon on day one, look at what billionaires we'd be. One of the things I've seen is that a lot of companies had a big valuation like three or four years ago, and like we're close to getting acquired. Suddenly companies are like maybe we can do that with ai. We don't need you anymore.'Cause people are so unsure of what AI can and can't do. We've seen a couple of cycles, like you could replace your entire staff with ai and we fired a whole customer service department and replaced with ai. And now all of our customers are angry for some reason. So we're seeing some like big swings that. I think have led to some hesitation and then like they go your company was amazing three years ago. Maybe just AI can do it now. And there's that open question is also seems to be affecting acquisitions. Yeah. And I think a lot of it comes down to, it all comes down to some core things, which is that nobody knows that AI means the definition is really broad. And that we're not sure. The usefulness, like I think I always approach when, same thing when I'm trying to think of buying a tool, I go, how is this useful? Will it save me more time? That's worth the money of the cost, but we see a lot of tools that are cool. Yeah, making AI videos is cool. It's not gonna help my business at all. It, there's no right value to an AI video for growing my business. I'm not making videos before, so I would make videos now. Same thing with AI music. It's cool, but not useful, but we see a lot of excitement. The more exciting something is, the more trends on social media the less useful. It's, there's almost a perfect inverse correlation. So how can companies that are having this struggle where they were like, thought they had a good valuation, were looking to exit, and then suddenly people go maybe AI could do it. You do what's the answer to that? So we actually got that question for The Crucible the other day from actually three different groups that I talked to in one week. And it was a question of why would we give your leadership assessment? Couldn't AI just take that? And people would fake it so it doesn't tell us anything. I'm like, okay, let's try it. So I pull up chat GPT and showed them live that it can't take it, that it was having, the way it's structured, the way it's it. Needs to be answered. And then I talked through also the point of using a leadership assessment like ours is that we can figure it for your fund. And we do, we engage with information and someone would have to be able to figure out not just what the AI should tell them about themselves, but the rest of the team. And there are too many points of information that the AI can't predict and therefore can't know. Could it come up with a reasonable score, even if it could take it? Yeah, probably, but not anything that's gonna be compelling. And so when I walked through that with someone, they were like, oh, okay, I get it now. Fantastic. And I think it's really getting back to what can AI do and what can't it do? What does your business do? What does that problem you're solving and what isn't that problem? And so people still wanna buy from people. People still wanna talk to people. People wanna feel heard. It's why everyone gets annoyed when you have to go through those automated systems in, on the phone or when you're at a kiosk at McDonald's trying to enter things. I understand the average ticket is higher, but just sit down and watch. People still go to the counter all the time. They don't go to the kiosk if they have a problem. They don't want to interact with that interface. It becomes interesting to balance that. How do we leverage the technologies and also provide that point of connection? Because, and I say this with the sociological background, if you create too many silos in our world where we're interacting not with each other, but with machines, with programs, with things that don't exist, we're not a society. We become very isolated and very sad, and so I think humans inherently know that we need each other and therefore we want to want each other and be a part of that in a tangible way, both for commercial purposes and social purposes. Yeah, I think that's something that's really important. Sometimes companies seem like they're trying to solve human connection. It's like nobody, there's nobody out there going, oh, now that there's dating apps, I'm so much happier. Now that we've removed the human to human part, nobody is saying that. Nobody says, oh, I go on Facebook for an hour and I'm happier. It's very interesting how I see this more and more, and this is why I'm really against AI voice phone calls and they're like, people only hang up when they figure out it's an ai. I'm like, yeah, that means a core, the core element of success is deception, which is like, why I don't work on this project. I get by those all the time. I go, I have a moral problem with tricking people. As like a core thing.'cause once you, once someone figures out they don't just become an audit customer, now you have an enemy for life. Like you have a, you've created a vendetta and it's so unnecessary. And it's like there's nothing wrong with giving people jobs and like having actual human protection on the phone and like the human contact, like talking to people on social media, get your support emails, says how you find out something is broken early or that people want and the customers will say, oh, I really wish had this feature, I'd pay more for it. I wanna get that message. I don't want that to get lost in the shuffle. So I think that's really important that we remember that the purpose of AI is not to decrease human and replace human connection. It's allow us to do more my favorite thing, I was building a piece of software the other week while I was swimming with two of my daughters. I'd go over and give it a command and program for 30 minutes while I was swimming. Then I'd come back and do the next command. To me, that's the future I want. Yes. Not the one. I have the laptop, swim with my daughters, and I'm inside programming. That's the wrong direction that we're seeing. So I really love that. So for people who are trying to figure out the investing space and wanna learn more about their leadership team, and by the way, I love that you're answer to that question. I didn't mean to skip past it. Like I was thinking, I would wanna know if I, was they investing in a company, the leadership team use chat GPT to answer their questions. That tells me right away, okay, I don't wanna work with these people. Like I was trying to hire a programmer recently and I could see chat g PT reflected in his glasses while he was doing answers. I was like, if you're gonna cheat this is so insulting to me and it's like we, you develop systems, right? I, one of the most, I'm very good at chat g pt, I can tell when you've used a chat GPT word, I recognize its accent. It's gonna be a giveaway, right? As soon as I say like in the ever-changing digital landscape, that's not a hu, nobody says that. Humans don't ponder, we never say pondering. It always uses these certain words that are giveaways, so it's I really love that. But for people who are realizing that you need to be objective with the leadership because it's, yeah, charisma is very powerful. Like you get yes, soul pulled into someone's charisma. We saw this with Theranos. Everyone's there was no blood test. There was never a blood test, but people kept doing it. We've seen it now with other companies. I love what you're doing. How can people find out more about what you're doing? See the Crucible, see your other projects. Where can they find you online? What's the best place to connect with you and see the amazing things that you're doing. Yeah. The crucible.com is probably the easiest place to come find us. The, my email's on there. It's justLindsay@thecrucible.com. I am, I'm very accessible, as my husband would say. I answer everything and it's probably to a problematic degree, but I think that there's always connections that can be made and insights that we garner when we're open to engaging with others, which again, doesn't happen if you're doing everything through. AI agents, so yeah please reach out and excited to share both what we're doing and chat about the future of how we can all improve the investing landscape and make better companies. I love it. Put all the links to the show notes are below the YouTube video. Thank you again so much for being here today, Lindsay, for an amazing episode of the Artificial Intelligence Podcast. Thank you for listening to this week's episode of the Artificial Intelligence Podcast. Make sure to subscribe so you never miss another episode. We'll be back next Monday with more tips and strategies on how to leverage AI to grow your business and achieve better results. 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