00:30:05 · Marc Bhargava
[00:30:05] S0: We haven't seen a lot of people implement AI effectively to date. And we're generally in the view along with that MIT study that maybe 95% of these Fortune one hundreds have tried, and they said it's kind of a waste, and it didn't really work, and it was janky, and that kind of stuff. So we are of a view that it is really hard to actually turn AI native. And so our worldview is let's create an AI native team. Maybe they were head of applied AI at Rippling or Scale or Stripe or they worked at these places or Figma, they've really seen kind of AI applied within the enterprise setting. Let's put together these teams. Let's incubate AI native teams, AI native software, and then let's go out and buy these companies because we've found when traditional companies are trying to implement AI, they get some benefits for sure, but they'll... There's a lot left to be desired, basically, in terms of the amount of automation they can achieve. So at least for us, we think that it's pretty difficult to just take models out of the box and implement them. You need a lot of context. You need an AI native team. You need a team that knows how to build software around the models. All of that is kind of difficult, which model to use. And so we kind of agree with the MIT study that says, yeah, AI is kind of a buzzword that's hard to implement right now. And we don't necessarily think that the world is going straight to AGI where AI agents will immediately be able to do everything. So I think we sit at least in the creation strategy somewhere in the middle where if you have an AI native team, but you also have the traditional clients, customer base, services folks, and you mix it together, that's where you can have kind of the best outcome, the best revenue growth, the best margin profile. So we really believe in this hybrid approach where AI in the right hands will be able to automate a good deal of work in many industries, but you'll also need people for tasks. And kind of this mix of people, software, agents is gonna be unique to each industry, and we can create the category defining company in each industry to go after that opportunity with the full tool set in the toolkit.
00:32:02 · Molly O'Shea, Marc Bhargava
[00:32:02] S1: I recently had Michael Barton, who's a sector head at CodeTwo on the podcast. And he he framed this out as there's two camps. There's AI will drive... And this has to do with layoffs. AI will drive efficiencies for teams and teams will be smaller. [00:32:19] S0: Right. [00:32:19] S1: Then there's another camp that says, no. This will make your teams much more powerful, and you'll be able to build bigger teams that are just much more effective. Where do you sit between these two camps?
00:32:30 · Marc Bhargava
[00:32:30] S0: We're pretty squarely in the second camp. I'll give you an example, but we incubated a company Hippocratic AI, which is an AI nurse. It's AI nurse software. And, you know, there's just such a massive shortage of nurses in this country and in the hospital systems. And so our view is AI is not coming in to replace nurses, but now one nurse could manage a team of five AIs that can do a lot of the basic tasks, like checking in on a patient or getting information. So for us, we kind of think that AI will create a lot of volume in the economy. There'll be a lot more new jobs. And so every time this happens in technology, is the Internet coming in and replacing jobs or is locomotives coming in and replacing jobs? The truth is it's very granular. Sadly, yes, some jobs might not be there anymore. But at the same time, it's creating a lot of economic opportunity and new types of jobs or even letting one person now do a lot more work. So that's what we see the most in the services industry is if someone can now do three times the amount of work because they have orchestrated AI agents and they use LLM software, are you getting rid of someone who's now three times as efficient, who only needs a slight salary increase? You're probably not. You probably are hiring three or four more of them. And so that's kind of what we see on the ground, which is in many of these spaces, there's a huge shortage of nurses, accountants, and yes, even lawyers. It would be nice if everyone could have a lawyer in their phone. Right? So many of these industries, more and more people would love to have it. We believe in this idea of abundance. And abundance is gonna come from that mix of people and AI services. It won't be purely AI. It won't necessarily be purely replacing people. We do think that there'll be a transition part, but there's some happy medium. And then the second nuance is kind of the first things to go is a lot of the outsourcing businesses. So there's a lot of outsourcing in legal. There was a lot of outsourcing in call centers. There's a lot of outsourcing in insurance, like looking over claims. What we're seeing a lot of is you add AI technology to American companies, they're now much more efficient. They don't need to outsource a lot of these more repetitive tasks.
00:34:27 · Marc Bhargava, Molly O'Shea
So I think the area that will be hit the hardest is probably abroad in places like India, Philippines, places like that, even Mexico. So here at GC, we are committed to trying to figure out ways to how do you retrain and reskill, and can we invest in companies that are training people in in new fields? And we think it'll be most felt actually outside of The United States. [00:34:47] S1: After surveying all these different shifts and this transition period that you talk about, I think there's definitely gonna be one too. Like, you know, you don't know what the future of jobs will be. Right. Kalshi had a market that it hit up to, like, 86%. I haven't checked it recently on layoffs in tech. And that there's gonna be an 86% chance that there's gonna be more layoffs this year than in 2024. But I do think... I don't I don't know if that one's true or not, so you'd have to check the data. But you would think that because of all this mix, new industries might pop up. What are you thinking might... Like, what could come next?
00:35:29 · Marc Bhargava, Molly O'Shea
[00:35:29] S0: Yeah. I think it'll be a lot more of things that right now are really limited to people with resources. So I think there'll be a lot more legal use cases and way more representation in legal. I think, like, a real time understanding of your company, your balance sheets, accounting, it'll... There'll be a lot more there. So I think there'll be industries that already exist but much more abundance. On the nursing side right now, if you're dispatched from a hospital, maybe they follow-up with you for three months or six months, but it just doesn't make economic sense to follow-up with patients nine months, a year out. But if you were truly doing the best thing for your patient, you would follow-up with them in nine months and in twelve months. So, I think a lot of these industries like health care, insurance, legal, where people have resources but then are tapped out, there'll be just a lot more around that. And so I think you'll have way more sophisticated markets in all of these places. [00:36:17] S1: So to be as biased as possible and objective, do you think AI roll ups are underrated or overrated?
00:36:17 · Molly O'Shea, Marc Bhargava
[00:36:17] S1: So to be as biased as possible and objective, do you think AI roll ups are underrated or overrated? [00:36:24] S0: I I think they're underrated right now. I mean, most people you talk to don't... Haven't really heard of them. So we're just getting started on on this part. I think right now people think, oh, it's a way to maybe put more money to work or something. Because obviously, as you buy companies, you can move quickly. You can put more money to work. But I think folks don't fundamentally understand that in a $16,000,000,000,000 services industry, we could have companies growing faster than software companies and at higher margin than software companies. And so this pool of 1,000,000,000,000 that VC has been fishing in has actually expanded now, maybe not to the full 16,000,000,000,000, but to multiple trillion. I think very few folks really grasp that. And so I definitely think that for now, they're underrated. [00:37:07] S1: Yeah. I brought that up because I'm just thinking about all the numbers that you've been mentioning throughout this and, like, increasing EBITDA and the growth and the headcount and all of it. It seems a much more lucrative, and so I'm happy that we're we're diving deep into it. So when we look at this industry and, like, the different players that go into it, how much of a role do consulting services play in this? And what do you think happens to the McKinsey where you used to work or like Accenture? And how effective are they in this process? Because it's really difficult.