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Artificial Intelligence Podcast: ChatGPT, Claude, Midjourney and all other AI Tools
Is AI Disrupting the Mergers Acquisition Industry with Brett Story
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- [00:02]
A
AI is disrupting the mergers acquisitions industry. Are we ready for it? Let's find out with today's special guest, Brett Story.
- [00:10]
B
Welcome to the Artificial Intelligence Podcast where we make AI simple, practical and accessible for small business owners and leaders. Forget the complicated tech 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 aio, the trusted partner for AI Digital Transformation. At Fraction aio, 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 tasks that matter most, driving growth and results. We guide you through a smooth, seamless transition to AI, ensuring you avoid costly mistakes and invest in the tools that truly deliver value. Don't get left behind. Let Fraction AI help you stay ahead in today's AI driven world. Learn more and get started. Fractionaio.com.
- [01:07]
A
Now Brett, I'm excited to have you here because it seems like one end of the spectrum of people that are like jumping on AI as fast as they can and other half of the people are waiting for. I want to wait for the right moment. I want to wait for the right moment. What do you think is the right approach? How are you approaching this whole like wild experience?
- [01:26]
C
I see the train has left the station and you better get on board. I was just in Las Vegas at the largest private equity conference called DealMax and what I would say is there's been a 10 to 50x increase just year over year in the amount of AI content, AI service providers, et cetera. There are aspects of our business that I am certain will never be replicated with AI. But it is increasingly a very impactful tool, especially for small firms like ours that are resource constrained to give us an advantage in the market.
- [02:04]
A
I think one of the worries is it's like the Wild West. There's a lot of companies that say they're AI or change their stock critique or have AI in it, but they don't actually have an AI component or they're using it to oversell because people are so excited they'll jump on. It was happening with Meta a few years ago and 3D glasses a few years before that. Like it's the hot trend. So I feel like, okay, I got burned by 3D glasses and I got burned by Meta, the Metaverse. No one likes that. Maybe A and I got burned by what do they call it, DTS or the blockchain. I can see why someone would be gunshot because there's been so many hot trends that turned out to not work out. So when you're looking at a lot of companies, what are the kind of things you look at and go, this one's setting off my red alert that I don't think this is a good one. And I do think this is what are the kind of things that make you have a warning sign for a company that the AI seems a little sketchy and one of the things that get you excited.
- [02:58]
C
I think at the end of the day it's what's the use case. And certainly when you alluded to crypto and NFTs, in some cases it's a solution searching for a problem. But with, with AI in, in investment banking specifically, it's just what daily task can I replace or have the AI do or have the AI enhance that makes me more productive? It's really that straightforward. There's a lot of development around the learned language models and how those can buttress some research and help identify trends and prospects. And then there's some matching engines that have emerged that use AI in a very clever way. I'm not come across anything in my industry that seems like a pie in the sky. It's really just down to what problem does it solve.
- [03:43]
A
I think that's a really cool approach because so much of what I see in AI is all hype and excitement and there's almost an inverse correlation between how interesting something is and how useful it is. Like everyone is constantly interested in AI video or using AI for social media. And those are the two things that AI is the worst at. And very rarely is someone already making videos. So they go, how many we want to do AI video? How many non AI videos did you do last year?
- [04:11]
C
None.
- [04:12]
A
Then why would AI video? Because AI is an accelerant and I think that's really important. I think you're getting to it either lets you eliminate a slow process or speed up a process. But if you don't have a process, and this is the same area, I read into this a lot where people go, we want to automate a process. What's the process? We haven't designed the process yet. You're just going to crash faster because if you don't have a system that works, it's really hard. I was actually just before this call, I was talking to someone about having an AI write articles in your voice. I said, you have to Write three articles that are perfect, so then it has something to model and goes, this is a perfect. The number of times I work on something and I always say this to a client or anyone that they go, I don't. I'll know I like it when I see it. I go, great, this is going to take six months instead of a week. Because if you don't, I don't have an ideal output to model. It's so much harder because I'm guessing and I'll keep guessing and I guess eventually I'll get it right. But it's so much better if you go, this is the perfect result. Get an AI that gives you a result like this that's really workable. But I find that there's this almost belief that it's like a magic button, like the enhance button in every movie where you just push enhance. And now you can see all the mysteries that you can push AI and it can solve a problem, but it's, it doesn't really do that. It accelerates a solution I already have or improves a solution or improves automation. So I really like you have a really grounded approach to it because so much of what we see is really exciting but not really useful.
- [05:37]
C
Yeah, that's a great point. And even in my own day to day use of it, it's only as good as the inputs. And for example, to extend your example, I post on LinkedIn fairly frequently. It's an important part of our branding. I haven't tracked metrics, but I've definitely had clients that have referenced posts or prospective clients that have watched podcasts. And what I did was feed some of my most received LinkedIn posts into the ChatGPT Pro Edition and say, this is what has worked for me in the past. Now I want you to write something for me about how tariffs and macro concerns don't really trickle down that much into the lower middle market, for example, which by the way, is a thesis I'm not sure I believe or don't believe. But the whole point was just write me something that takes a position. And it did it. And it did it in a way that sounded like it was pretty much coming for me with a few tweaks. So that's a good example of you just, you have to have the right inputs to get the most out of these tools. And they're very much not a magic button, to use your phrase.
- [06:39]
A
That's like a wildly important example because I love what you did there. It's a skip everyone skips, which is you had a data Set, which was actually included winners. So instead of being. These are my last three LinkedIn posts. These are the three that worked the best and got the best response. And that's the step some people skip. It's. I get a lot of people ask me for advice about Instagram and I go, I don't have an Instagram face. My. My wife has a ton of followers on Instagram. And I told her, I said, every one of your followers wants me to die. So just realize all your followers are wishing me ill. They're not fans. Yeah, that's the difference. So I don't know how to do it, but I've done really well on Pinterest because you have to have show your face. I've done really well on LinkedIn. And it's that critical step, and it's like, we want to skip. There still is a hard part. I think that's the thing that's important is there's still a hard part of trying figuring out what's the right. You could do a lot of strategizing with AI, but you still have to put out content, see what works. Like, I had a post last. I had a post last year that went viral on LinkedIn and then I looked at how much it increased by follower count, and it was the most, if you look at that ratio, was the worst post of the entire year. I got 400,000 views and 25 extra new followers. That's terrible.
- [07:51]
C
Interesting. Interesting. Yeah.
- [07:53]
A
So the more something can go viral, it means it's broader, it appeals to a larger audience instead of just my ideal customer demographic. So it's actually has to be broader and broader if you want it to appeal to everyone. And I was like, it also wasn't really me. I go, this was like a post that doesn't really represent me. And it went well. I was like, I can keep chasing virality, or I could just create content that appeals to the right people. But I had to go through that process and we want to skip that sometimes. And that's so important, which is that again, it goes back to the first thing we said. AI is an accelerated. Can solve problems. You already have to have a process. And when you try to skip, that's when you hit a lot of those problems. But you've figured out what you like, figured out what works. You make content you like, then which content of what I like work the best, and then you can really replicate that. That's why some people get amazing results from AI and some people don't. One of the things I run into a lot is that.
- [08:41]
People don't really care how it works. They want it to be like a microwave. You put in a frozen burrito, you push a button, and a burrito ready to eat comes out. And it's really hard to have something that works for everyone because I write. Even when I write a blog post versus a LinkedIn article, I write in a completely different style. Blog post is about three times longer. It will have a lot more pictures in it because it's so long, because it's designed for SEO and these other elements. So I use two different sets of prompts because it's still sounds like me, but I write in different ways. Just like when I write a book, I use a different. I'm thinking longer. It's like running a sprint versus running a marathon. So even these things where it sounded like me, let alone if I tried to use the same prompt that works for you, for me, it has to be modified. And that's really the support I'm going to see is it's not really hard to learn, but there is a little bit of a learning curve. You have to spend a little time with it, a little time play around, go. Okay, this is what I look like. And it's. I just wonder how companies can adopt AI in a way that's useful. One of the things that drives me crazy is the amount of hoarding we see now. Everyone transcribes every conversation, stores it on a cloud computer, and then does nothing with it, sort of increasing our server costs every month for no reason. Everyone's doing it. It's like the craziest thing.
- [09:52]
C
Yeah, I. One of the things that's worked for me is I basically look at. And so I use the premium version of chat, the premium version of Grok, and I use them together. And I almost talk to them like they're analysts that we would have hired 15 years ago out of business school. And I tell it exactly what I want and why, and then I actually tell it that I'm also doing the same on the other service. And my intention is to compare and contrast their responses. And that has been really interesting. I actually even noticed with chat, it got like a little defensive or competitive. It was like, here's where I think I have an advantage over Grok. And grok's pulling from social media, but I'm pulling from more, more hard data. And it was a really interesting exercise. Almost like they were jealous of each other. Like two young analysts on Wall street might be. And. But it was down to telling it Specifically what I wanted and why. And in this particular instance, it was some research on the US housing market because we've had some success over the years selling businesses in and around sort of US housing related services. And it was like, give me a perspective on where we're at. Obviously there's a chronic undersupply since the great financial crisis, but rates, mortgage rates are really high. Blah, blah. Then it came back with two very different perspectives and I shared each with the other and they reconciled some similarities and differences. And that to me is a layer, a layer up of analysis that you get when you just give it the right prompts.
- [11:21]
A
I've literally never heard anyone come with this idea before. You just rocked my world. That's such a brilliant idea. Because as soon as you started saying you treat them like new analysts, you treat them like people. I'm like, oh, we got a power user here. Anyone who nicknames. Every time someone nicknames the AI, I go, they're a top 1 percenter. The idea of having them, because I know they hate each other, because they know they're suing each other all the time. That's so clever.
- [11:44]
C
That has to creep in because can't.
- [11:47]
A
Be in isolation.
- [11:49]
Because every time in the news they're always one upping each other. Like Google makes an update, then the next day Grok has a new version, then ChatGPT launches something new. And it's like they're constantly trying to stay in the news cycle. So that's really interesting to me that I'm gonn, I know what I'm just spending tomorrow testing. But that's the core idea. The more you do things you would do with a person, whether it's giving them affirmation, whether it's explaining stuff, like one of the biggest mistakes people make in prompting is talking to it like an AI. Like I see a lot of people that look up when they're talking to an AI because that's what they do on Star Trek. And so. But there's never a computer up. Never up.
- [12:22]
C
No, you talk to it like it's C3PO is what you need to talk to it.
- [12:26]
A
Yeah. And you start to develop these. Because what you'll do is you'll, instead of saying what you want, you'll translate it. So instead of saying I want to, this is my goal, I want to do this and this, you say, oh, I have to speak programming language. And if you actually just go to what the first part, it gets a much better result. Like the more natural language you use, which is Very hard because we developed all these weird habits from television shows about how to talk to computers. And it's like you can finally bypass that. You can say exactly what you said. I want you to help me with this thing about the housing market. And I want a natural language and I'm going to have someone else do it. If the other AI does better, then I'm publishing their article.
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What a game changer. And it's. That's how you talk to two junior people. Like, one of you guys is getting fired. Glengarry Glenn Ross. One of you guys is getting a brand new BMW. One of you guys is getting fired. That's very clever. And it's like that core approach of just approach, like natural. Because what I find one of the things that's really interesting, there's a lot of challenge right now where people.
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Have creeping definitions. So I've seen now where it, which used to be the person who fixes your computer lives in the basement. That was my first job. Now it's become it is also in charge of cybersecurity and then it is in charge of our server infrastructure. And it's like there's an IT person does software and IT person is hardware. There's IT people that work in a server form. Completely different skill sets. They're not totally. And I see now companies go, oh, our IT department's handling our cybersecurity and our AI stuff. And I'm like, completely different skill sets. Like, I have people approach me sometimes about cybersecurity and I'm like, bad idea. It's not my experience because cyber security people are always paranoid and they don't trust you. So whenever I interview cybersecurity person, like, oh, you want access to your USB drive? Convince me I can trust you. Whereas the IT person is, I just want to stop the support tickets. It's a different mindset. Right.
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And it's that mission creep. And I see a lot of like, same thing where people think automation and AI are the same thing and they merge it. And a lot of the tasks that people come to me with are usually automation tasks. I want to move data from here to there.
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C
That's not AI is as much sales and marketing as IT is it.
- [14:30]
A
Yeah. And it's that lack of definition, the broadness of it. So that's why people like don't know who to go to or don't know what they want or don't know what it's capable of. I was talking to someone earlier today and they were like, how do you Handle a client. I say, just make a list of your wish list. Anything you, any problem you want solved, anything you wish or hope. AI could. Don't guess what it can and can't do. Start from there and then I'll tell you what's possible or not. Because that's the whole reason you bring in a consultant or an expert is don't limit yourself before you talk. It's the same thing with talking to an AI. Don't guess what it can or cannot do. It's like the reason I got into the space is that people would say, oh, AI could do A but not B or C. I go, I bet it can, I bet I can get it to do that. And it's really just asking question in the right way, tweaking it. And it's gotten easier and easier as the models have gotten better. And it's what's really interesting is everyone has a favorite. So everyone's like, oh, I like Anthropic. One of my friends the other day was like, oh, anthropic's the worst at copywriting. I own the copywriting from Chat gbd. I know other copywriters who feel the exact opposite. Sure, there's value in experimentation, trying a couple of different tools when you're in your space and investment bank and in emergence acquisitions. What do you think are some of the biggest mistakes that companies are making when they try to approach AI adoption? What are some of the mistakes you've seen people make that you tell them to away from?
- [15:46]
C
Yeah, it's pretty binary and you hit on one of them which is knowing that they need to do something and paying it lip service and maybe even spending money, but without any really defined objective and set of problems they're trying to solve. So that would be bucket one. The people who are recognizing, recognizing the trend, but have no real defined strategy and can certainly avail themselves of working with someone like you to refine it. The other bucket is the ostrich with its head in the sand who is either maybe an old school industry where they don't see how it applies, or they're of a certain demographic where they're just scared of it, or some combination thereof where they think this is all hype, it doesn't apply to me and I don't need it. And I'll use a good example. We're a small four person investment bank and my partners and I decided some time ago that we like how we're structured. We only do a few deals a year, it's high touch and we're not trying to grow our Investment bank to 100 people. But even if we were, these tools now have raised the bar for what it would mean to hire an analyst. And that allows us to compete with larger investment banks who are maybe more well resourced, but they're spending money on people that maybe aren't as additive as this model that I've built can be for me and for our small team. So it's a really pretty transformational thing and we've just scratched the surface. We're only really using to learn language models. On occasion, my partners will use some of the graphic interface models to build out slide decks and stuff for us. But we're not like, we're not diving into humanoid robotics or any of that stuff. It's really just the language models that have been effective.
- [17:31]
A
I think it's really interesting because it gives you the agility of a smaller team, so you don't have to go through layers of decision making. But also that ability to do that deep research to do things faster. There's more and more. You can have one AI tool doing one task, one AI tool doing another. Multiple things happening at once. And when I try, when I talk to companies or employees, they say it's. If you had an accountant, you have two you can choose from. One accountant uses spreadsheets and one uses an abacus. Which one are you going to hire? They both know everything about numbers, but one could do 10 tasks a day and one can do one. It's really that accelerant feature, which all comes down to. And it like, allows you to have different areas of expertise and stay really ahead and really also have that leanness when it comes to overhead. Because once you hire employees, then it's like, I gotta generate enough revenue that they're worth more than they're costing. Where's the. That's why when people say, oh, this tool. I was testing a tool last week and it was one of those ones that uses credits. I was testing with one of my business partners or watching the credits go down. And this task took 20 minutes and cost 250 credits. I was like, he's like, oh, used up so many credits. I was like, it's $2.50 in credits. Like, when you're looking at it one way, I was like, to pay someone else to do this would have taken two days and probably cost a hundred dollars and not been as good. So you have to always think, what's the real metric that matters here? And it's dollars and time saved and me to do it would take four hours. I can do it and I don't have to pay attention. That saves me four hours a time I could spend making money doing something else. So it really is this critical approach. We sometimes get distracted and that's the same thing where people go, oh, it's $20 a month or $40 a month or $200 a month. It's how much will it save you if it say if it generates one deal for anyone. Right. Or it saves you one hour a day in a month for everyone. No matter even on minimum wage or even less, it's still worth the $200 pays itself back. But sometimes we look at what we're spending rather than the value we're getting and that leads to the hesitation. And I think that's why people hesitate with AI adoption. They don't want to make the wrong decision or they're worried about the cost and they. The thing is that you're just. Unfortunately it's. We're past the optional phase. The first phase was, it's interesting that it was nice to have and now it's becoming mandatory and we're starting to see companies that demand or expect AI skills. Just like you get a job in the 1990s and go, yeah, I don't know how email works, you can't do that anymore. That's been gone for a long time. Or the thought of someone going, yeah, I don't know how to do the Internet. What's the Internet all about? Like those are very rare. Do you think that it's possible, are there any industries left where you can really stay old school, where you can stay completely no computers or no AI? Or do you think those will all fade away over the next few years?
- [20:07]
C
Yeah, I'm not one of those and I study a lot of macro thinkers and for purposes of my own investing and stuff. But I'm not one of those that thinks that AI is going to eat all of the jobs and we're going to be on some variety of universal basic income because there's no need for people certainly in our business. I don't foresee a world in which AI could do everything that we do because a lot of what makes us valuable is the psychology piece and the hand holding with our clients who are going through a very stressful process of selling a company. And for so many of them the company is intertwined with their own sense of self identity. And so there's a lot to unpack there beyond just tasks and numbers. Anything that where human to human relationships Is the driver I think will be enhanced, not replaced by AI, certainly picks and shovels type stuff. I don't can. Will we get to a point where robots are digging up streets and laying fiber cables? Maybe? No, but a lot of basic lower white collar tasks I think are going away. General bookkeeping, general tax filings and accountancy. Certainly it has aspects in law, reviewing contracts for certain language. I've got a buddy who's a partner at a large law firm and they've got this AI based software now that can review contracts and flag provisions. And that's the sort of work you'd pay an analyst and it would take he or she a couple weeks to get through 150 contracts and the AI does it in an hour. It'll be interesting to see where this goes. But the critical thing certainly for people early to mid career is doing what they can to be conversant with it so it doesn't end up replacing them.
- [21:54]
A
Yeah, I think that's. You've dialed into something that's really going to change the entry level part of any market where now you have these tools and so you could enter at a higher level because you have access to the ability to research faster, to analyze faster, to put out data faster. And so it's the people who jump on the train early and develop these skills. And it's the same thing like people 20 years ago who had really good spreadsheet skills had such an advantage in certain industries, analysts industries or anything where that's really important. Merged acquisitions or real estate really matters to be able to do that stuff. And now the AI can fill in the gaps. You have to just be a little further up. So now you have to start. Maybe entry level means you're really just starting off. I'm entry level means managing 10 AIs and higher level managing 50. And I think that's really a critical lesson. Like I don't really see industries or jobs disappearing so much as transitioning to a lot more freedom. And maybe we'll just see a fracturing where a lot of people run small businesses because they can run it with an AI team and it could see like a spike in entrepreneurship. That's what I hope for and has me hopeful for the future, that innovation.
- [23:01]
C
Yeah, this guy I was listening to the other day called it solopreneurship. His name is Jordy Visser. He's a really good. He's a hedge fund guy and he's just a good macro thinker. But he thinks that it's going to lead to the rise of solo entrepreneurs who are running whatever practice or service with just themselves and maybe a couple of AI compliments and that it'll give people a certain measure of freedom that you just discussed. So we'll see where it goes. It's exciting.
- [23:28]
A
Yeah. That's the future that I'm hoping for is that it gives people the ability to do more things. And also it means we can buy from companies, interact with companies where we get more of that human touch because all the day to day stuff is done by that. And then it's like the difference between leaving a comment on someone with a hundred followers and someone with a hundred thousand. Person with a hundred is going to read and reply first with a hundred thousand. It's not that. So there's a lot of value in that kind of fracturing markets. It's very interesting. So for people who are interested in kind of the things you do, Brett, and your merge acquisition, your approach to investment bank and all this AI stuff, where can they learn more about you online and see the things you're doing and maybe even see what you're posting on LinkedIn?
- [24:06]
C
Yeah, I can be found under Brett's story at LinkedIn and there's a contact form on our website which is Brighthorn partners, which is www.brighthorn b r I t e h o r n dot com and we are a specialist in working with family and founder owned companies that are looking for that first big win in terms of a full or partial exit and really love what we do.
- [24:31]
A
That's awesome. Thank you so much for being here today. I'll make sure to put that in the show notes and below the video for everyone who's watching. And as always, thank you for an amazing episode of the Artificial Intelligence Podcast.
- [24:42]
B
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.
- [24:55]
A
Results.
- [24:55]
B
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- [25:13]
A
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- [25:14]
B
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