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.
00:37:41 · Marc Bhargava, Molly O'Shea
[00:37:41] S0: Totally. Our view is, you know, at least on the AI roll up side, we're more getting these smaller fragmented style businesses and putting them together and doing this AI transformation. McKinsey and Accenture and others really focus more on the Fortune 100, And and I think they'll have some success in embedding AI there. But at GC, we created a company called Percepta, one of our transformation companies that we wanna hold for the long term. And they... You know, the thesis there is that maybe traditional consulting isn't really designed for a lot of the AI implementation piece. So they can give more strategy advice, but not necessarily the same kind of, hey, here's what we're seeing. It's a fast moving industry. Here are the companies we've invested in. Let's actually go and implement kind of fast moving AI changing technology in the Fortune 100. So I do think there's a huge opportunity for companies like Percepta. You probably will also see McKinsey and Accenture and others benefit, and the Fortune 100 also will have to evolve. Our focus more, though, on creation is incubating these companies in more fragmented industries where you don't necessarily even have the resources to go to a McKinsey or an Accenture if you wanna add AI implementation. Because [00:38:48] S1: of General Catalyst's very large platform that you have, how do the private market investments help determine or inform these companies? Are you partnering with any of them for them? How do... What... Like, how does, like, Anthropic fit in here, and what are you learning from them?