00:23:34 · David Flickinger
So it's a a micro example of how when you have this architecture embedded in a business at enterprise scale, the AI should be directing the humans to the most critical items, thus allowing them to be more productive, more efficient, and automating work streams that should be automated, but make the human judgment element that much better in those businesses. And that I think is a competitive advantage. If you can make your human element of judgment better because you're directing your humans faster to those areas which need their attention, that's a win using AI. That I think is a great AI implementation. It's not always just let me automate everything. In fact, I think that that could prove to be a mistake. Over time, you see even this silly little thing of automated emails where you clearly get an email. We've all gotten them now. It's totally written by AI. There's not a human touch in it, and you're just like, throw this away. This was this was written by an AI that gave... Whoever sent this gave no individual human thought to what they were sending. So, again, these micro examples we start to see, but I think at a 30,000 foot view, thematically, what we wanna do is, again, start to streamline what can be automated and what should be delivered to a human so that you can run a business better. Because at the end of the day, a lot of these businesses are still people businesses. It's still human to human interaction. And, of course, people and and we'll build systems for these agent to agent interactions. But the human human interaction element, if you can use AI to make that better, I think it's really a tremendous force multiplier.
00:25:27 · Mikk
[00:25:27] S0: Now in the roofing business, what about the junior estimators as the senior ones are so more efficient now? What's gonna happen with the junior ones?
00:25:41 · David Flickinger
[00:25:41] S1: So they get up to speed faster. That's for sure. They can do more complex estimates earlier on than they otherwise would have. And so if you wanna use them in that way, that's great. I could tell you one area where I think we've seen that instance you just described and my prior answer align really well is maybe the junior estimators are able to spend more time with the customer, with the decision maker because they're not spending so many hours as an inexperienced junior estimator in front of their computer screen. They're spending more time with the customer. They're spending more time on a roof. They're spending more time doing the things that help them win jobs because the answer that really was the answer to a math problem has largely been automated. Their review was directed to these specific areas. Now there's a high degree of confidence that they're getting to the right answer. The chief estimator, while he may have had to spend a lot of time reviewing a junior estimator's proposal before he approved it to be sent, now maybe has to spend a minute or two because that person has the confidence as well that this proposal was generated with sound logic. It was using the context of the business, the correct rules, pricing, rates for materials and labor, etcetera, and that the junior estimator was focused in the right areas. And then the senior review of that is is again much more efficient. So I think the promise is twofold. One, that you are just more efficient with the workforce that you have. If you have junior employees, what can they do faster and above and beyond their current skill set with less training and less time in the role? But two, can those junior employees focus again their time and effort on things that win business, win jobs, help customer retention, help improve a customer experience versus spending more time in front of a screen.
00:27:44 · Mikk
[00:27:44] S0: Okay. And last one here, are you now able to make and send more proposals to potential clients as previously for the senior estimator, it took two weeks to create it. Now it's, like, twenty to thirty minutes and, obviously, some additional time to review and double check. So are you now able to just simply send more offers to to win more jobs?
00:28:07 · David Flickinger
[00:28:07] S1: The short answer is yes. And this example is a lot of fun because this engagement was predicated on a request from the roofing business' customers that they respond to more proposals. In other words, they work with these general contractors that have a a wide net that they cast in terms of the jobs that they're trying to win, and so they want their roofing subcontractor who they really like working with to bid all these. But, of course, in the absence of AI, that's almost impossible without hiring a big team, which doesn't make sense ahead of winning that work. And so the idea was, hey. Can you send out more proposals? Thus, more jobs, but also satisfy a customer request by using AI. And I would tell you, absolutely, they've been able to send out more proposals. But beyond just the volume of proposals out the door, the amount of one business has been tremendous. This company has doubled the size of their commercial contract win rate, and this business will be double the size next year. And I think you directly attribute that to an AI tool that was well architected and well implemented, and they haven't hired any additional people. And that's that's really, I think, one of the promises of AI too is not that you replace a workforce, but you're able to grow productivity in a way that doesn't bloat your overhead. I think that's what so many small business owners, mid sized business owners are looking for. Because as I... Aside from AI, when I talk to business owners and in my own businesses, you always reach these inflection points where you really believe, and you're right. You could grow here. But you reach this inflection point where, okay, to grow there, I've gotta hire all this additional overhead infrastructure staff. And so you end up staying and topping out at a certain size, and that is different for everybody based on their individual market, their vertical. But almost every business runs into this problem. And I think the beauty of these AI implementations is that you can blow through that ceiling that previously to blow through it, you would have to hire a bunch of people ahead of doing that. You can now drive that growth without additional overhead. Will you never have to hire another person? Of course not. But as you grow, now you can justify it.
00:30:39 · David Flickinger
And I think growing from a place of efficiency where you're an AI first business growing in to a new revenue category or threshold is very different from where you see a lot of businesses that are at this massive threshold. They've already got a lot of overhead, and now they're implementing AI as a means to reduce headcount. That that story exists out there. We hear it in the news. But the much more interesting story that I think we'll start to see in this lower middle market space is companies grow with an AI first infrastructure. Because they had the AI layer that empowered their growth, that empowered productivity and efficiency in their business, they were able to jump to a new revenue threshold that otherwise wouldn't have been possible without bloating the overhead. And so to do that with an AI first mentality and infrastructure, you can then hire in a very smart, efficient way that, of course, supports that new revenue threshold or tier that you're in, but you haven't had to bloat your overhead in a way that, well, now you have to do layoffs in a year or something like that. But it's really interesting. We're starting to see that happen in businesses with whom we're engaged, and it's really fun to see them grow just to these total new revenue categories that even they didn't think was possible, but now they're doing without adding a headcount. Or maybe they're adding one or two, but it's after they've already grown 40, 50, 60% year over year.