"The Cognitive Revolution"
00:09:27 · Marc Bhargava
[00:09:27] S1: Yeah. That's the hardest part of what we do. So if we look at an opportunity and say something like, you know, customer support and call centers, we're seeing through our company, Crescendo, that 50 to 70% of call center workflows can now be automated with agents and LLMs. Or you look at something like MSP and IT. We're seeing through one of our investments there, 38% automation or bookkeeping with one of our companies kick 80% automation. So we're seeing this massive automation every three to six months. It gets more and more in these different industries. And that's one big part of it, but second part is our founding teams have to have m and a, private equity kind of industry experience as well. And so that's why this is a perfect project for creation which is all about incubating companies, putting people together who might not naturally know each other. And so in many of these cases, what we've done is we've found people who have led Applied AI teams at places like Rippling or RAM or Scale AI. We're kind of combining them with industry experts who have done m and a before, done roll ups before. We're putting together both of those legs. And so that's a really important part of where GC fits into this is identifying which industries have high potential for automation, but then also putting together a founding team that can do the automation, has experience in Applied AI, and has experience in the industry, in m and a, in private equity, and doing the buyout part as well. So it is really important to have both. I will say that technology companies have done a pretty good job at m and a if you look at the track record. Like with Facebook, for example, the acquisition of Instagram, I think we'd all agree is absolutely instrumental to Facebook and what it is today. If you look at something like Google, the acquisition of YouTube and and even Android is extremely instrumental. If you look in our own portfolio like Anduril, it's done over a dozen acquisitions as it's become the best overall platform for defense tech. And so sometimes I think also tech gets a bad rap, but has actually been very successful in creating public value through their own compounder stories as well.
00:11:20 · Marc Bhargava
And now some hedge fund analysts would put companies like Microsoft and Amazon in that compounder bucket of making great acquisitions, improving those companies, cross selling them, and have become amazing free cash flow stories as well. So I think the AI world is no different. There's an opportunity now in many industries to have a high level of automation. If you can now go and buy companies, improve them with that automation, you're freeing up cash flow to buy even more and you can have an inorganic story that can also complement an organic story of naturally growing the product suite and getting more customers as well. So at GC and at Creation, we're really thinking what are the ways to get the most tools in the hands of founders? How can we put together these unique teams and how can we help them get to market quickly and also have the data they need to fine tune and train their models and have a really fast feedback loop? So we think this hybrid services plus software AI enabled with the capabilities to also go buy your distribution, buy your data, this ends up creating the best companies and the best products. And we're seeing it in the HOA management space with Long Lake or in you know, at the MSP space, Crescendo in the call center. So we've placed now eight of these AI enabled roll up bets. In five of them we helped incubate the company, was the first check-in, and it's a strategy that's certainly now catching on with the market and having other investors come in and a lot of excitement, but probably most importantly, having a lot of founders say, hey, I get it. Especially second time founders. The hardest part is getting proprietary data. The hardest part is go to market. And I'm good at building and operating and running companies and maybe even did m and a myself. I sold my last company. And so we're really attracting these second time founders and experienced operators who could go work with any venture firm, is choosing to work with us with creation because we have this specific thesis and strategy.
00:13:05 · Nathan Labenz
[00:13:05] S0: How much of this is about... And I do wanna go into, you know, each one of the portfolio companies in a little more detail and kind of understand the the story and the nuances. But at a high level, how much of this is about the fact that, you know, it's it's been obviously said many times in the, you know, AI era thus far, software can now enter the services market. Right? There's this sort of blurring between software and labor. And in a sense, that's, like, the greatest opportunity ever for software. In a sense, though, it also creates a more challenging, let's say, relationship or, you know, the people buying the software are also currently selling labor. And so, you know, if you're selling billable hours at a law firm and you're like, geez, you know, this thing might make me more efficient, but that also directly cuts into my billable hours. How do I think about this? How much of this is about saying basically what once was a sensible model of we are selling compliments to labor is now that we are selling substitutes to labor, and so we need to sort of rebundle or restructure the market to bundle those things together in one company with one sort of set of shared interest because it just doesn't work as well as it used to given that switch from... Or not not... Obviously, full switch, but at least partial switch from complement to substitute.
00:14:29 · Marc Bhargava
[00:14:29] S1: Yeah. It really now is about selling work. So I think a great example of this in the public market is Palantir, which has done incredibly well, of course, and sells work. There's forward deploys engineers and, you know, that services, but ultimately, they're selling an AI platform and system and a technology. And so it's a combination of software and services and ultimately, Palantir would say we're just selling you an end result or work. I think that is becoming true in more and more industries. You mentioned legal for example. Most legal spend is really on third party law firms. It's not really on the software component compared to the spend on lawyers. And so, you know, an approach that one of our portfolio companies, Udia, is taking is they are going after Fortune 100, General Counsels, in house law firms, and they're selling to them a mix of services and software, all AI enabled so that, you know, these Fortune 100 brands can spend less on third party lawyers and instead do more in house with the toolset UD is giving them, which is a mix of software to do things like NDAs and contracts, but also services. And so they recently bought a company called Johnson Hannah that does a lot of kind of services as well, more manual things. And so I think, and it's been reported of course, that this hybrid services plus software is getting more and more interesting because the margin profile is changing in services. So globally, services is a 16,000,000,000,000 a year revenue opportunity. Software is actually only a 1,000,000,000,000 global revenue opportunity. So services is much much larger. But historically, services have been quite low margin and especially free cash flow margin. And so a lot of venture firms and even private equity and others have been less interested in the space. Now if you're automating 30 to 70% of the workflows in some of these services industries, you can AI enable the workforce and take a lot more clients. And doing that really changes the margin profile. And so now these businesses are getting more interesting to venture investors because ultimately this hybrid services software can have pretty high margin profiles. So instead of something like five to 10 EBITDA margins, 30 to 40% in certain cases, if you flow through the level of automation at, you know, 50% plus.
00:16:37 · Marc Bhargava, Nathan Labenz
And so it's getting very, interesting what you can do with an AI enabled workforce. Udia being a great example of coming in and helping these large corporations have their in house legal teams be AI enabled and take on more work with, you know, the same number of people and outsource less to these third party law firms. [00:16:55] S0: I wanted to double click on the numbers there. So we got 1,000,000,000,000 software, 16,000,000,000,000 services. Obviously, that's the best opportunity. Margin traditionally in services is low. I think you said five to 10%. But if you can automate 50% plus, then you can bring those margins up a lot. One of my long standing, beliefs about AI has been, I don't know what to expect on most things, but I do expect high consumer surplus. And so I guess I wonder how do those before and after offers look today to customers, and how do you think that's gonna evolve over time? You know, or is a company... And we could go into, you know, specific ones here and it probably varies. But is a company going and saying, okay. Don't buy services the old way. Buy our new hybrid service. It's gonna cost you 20% less and then under the hood the cost structure is 50% less and then that... That's how they get to a higher margin. And is that margin like sustainable long term?
00:17:59 · Marc Bhargava
[00:17:59] S1: Yeah. Absolutely. I think it is quite sustainable because the offering is generally we're gonna charge you around the same we do today, but we can do a lot more with AI. And so if you're already using a product and you're enjoying using it, if suddenly, you know, you can have two or three times as much output and they're keeping the price the same, that's unlikely to be a client that churns. So we view this less as a cost cutting game. Like when we AI enable a workforce in IT or in legal or in call centers, it's less about letting people go. We're automating people. We're automating tasks. So automating maybe 30% or 30... 50% of the tasks that they're doing which enables them to do harder tasks which generally are higher margin and to cross sell as well. And so that is our thesis that this will really allow for a lot more growth. If you go in and you AI AI enable a workforce, you can now take on twice as much work with the same team because they have more tools and they're automating away the easier tasks. So that is the thesis. For the end client, what that means is you're getting even more of the high margin tasks done for you without a change in price. And so you're getting more at a similar price. And so we do think that is quite sticky. A really good example of this is in Ramp where I'm an angel investor and GC is also a large investor where, you know, they went in and they AI enabled a lot of the sales and marketing team and, you know, folks were two to three times more effective. And they got the question of, oh, so we can, like, now cut our sales or marketing team. But it's actually the exact opposite. If people are now two or three times more effective, you actually wanna hire a lot more of them. It's higher ROI. So I overall expect this AI opportunity to continue to grow the global economy. It's a tech innovation like the internet or like cloud. And ultimately will create more jobs, more productivity. And I don't see a pricing margin compression because the offering is actually getting more and more output. And so overall, I think that it's gonna create a lot of opportunity that way.