LIVE | General Catalyst’s India Investment Can Double In 5 Years, Says CEO Hemant Taneja | N18L

Yeah, first of all, thanks for having me. Look, it has been peak ambiguity because you saw from a geopolitics perspective how relationships between countries, look at US India for example, how that was pretty volatile, and then there continues to be a lot of volatility in the capabilities of the technologies. So we started the year with a really clear view that we have to navigate a lot of ambiguity as we think about building the next set of businesses. Now, what I think about at the end of this year is I actually think we're going to look back and say 2025 is a year that diffusion of AI started. So if you go back to November 2022 when ChatGPT was launched and everybody all over the world, every CEO, every industry, every country was thinking about what to do with AI. All these companies got started in different industries. Vertical language models got started getting built. AI rollups, a lot of activity. Now what's happening is you're starting to see evidence of what AI can do in how it melts labor into productivity. And this is the year we're going to look back and say it's starting to show real capabilities in production.

Look, I think there's definitely disappointment because one of our core beliefs was given how strong the Indian diaspora is in the technology sector in the US, that there was naturally going to be a deep collaboration between US and India, especially on technology matters. And so there's disappointment that that hasn't yet happened. In fact, even when the tariff discussions started, the thought was India was actually going to be on the front of the line in resolving what those relationships are going to be like. Having said that, I do believe in the long term it just makes too much sense for these countries to be working closely together in the context of geopolitics, in the context of innovation. And I remain optimistic that we're going to get there.

Not really. We are very optimistic about the opportunity in India. I did a review with our team in Bangalore yesterday and just looking at the kinds of companies that are getting built, the traction they're having, it just speaks to the growth opportunity in India. Now, as we were mentioning earlier, we are actually trying to build resiliency in all the key sectors: healthcare, defense, financial services. And innovation is going to only flourish here. Given the fact that it's such a growth market and the entrepreneurial DNA is so strong, and you've got all these IPOs happening which is just motivating for the founders, I just think it's only going to accelerate.

First of all, it's just great to see that there is an IPO market. I think the other thing is it just encourages more capital into the sector. But what I see that's really interesting is think about the kinds of business models that are getting built. It reminds me of what happened in China 20 years ago. So you got these unique companies that got created that were especially for the growth opportunity in the country itself, and that's what's happening and that's really exciting to see. The first set of IPOs that we talked about were companies like Crunchworks which were really global software companies taking advantage of the fact that you can build them here cost effectively. But now it's about India's growth, India's quality of life, and the innovations that can make a difference for people. I think those are going to be some of the biggest outcomes, so we're very excited about what these companies are doing.

Look, there's a lot of conventional ways you look at the Indian market. The spend demographic isn't that strong and whatnot. You have to think forward. If you're growing at these kinds of rates for the next 10 years, what is that opportunity going to be? So what you're starting to see is these business models that are very robust. And if you look at them maybe in the context of today's TAM, perhaps they will seem small to you, but as the market is growing, such an expanding market, these are going to be really interesting companies. The idea that you'll have 30, 50, 100 billion dollar companies serving the consumer demographic, and over time in the other industries like healthcare, defense, and so on, that would have been very difficult to imagine. I could totally see that happening in the next 10 years in India.

Our view of the world is there are two big trends. Global resilience where every country is trying to figure out how to create strategic autonomy in key industries. AI would be one of them. Defense, industrials, healthcare, and so on. And the second is the AI capabilities. I think the global resilience trend is very strong in India, and so if you build the next generation healthcare companies and defense companies here and you make them viable and market leaders, they are going to be well positioned to be global companies. So that part is actually working super well. When you think about on the AI side, India has a lot of challenges in my view. One, we don't have the infrastructure here. You don't have semiconductor capabilities or cloud or models. If you were to start today, you would say it'll take you 15 years to build that. And you don't have 15 years. If Indian companies are going to be globally leading, they can't be waiting for 15 years for those capabilities. So I think that's an issue. But you do have a lot of open source capabilities that are there. So I think India in the short term has to lean into it while figuring out what to do in terms of developing local model capabilities. The other challenge that's very top of mind for me in India is we also have the youngest demographic here. So on one side you have to put all those people to work in interesting jobs that create upward mobility. On the other side, if your companies are going to be globally leading, they're actually going to be very efficient from a human capital standpoint just given the AI productivity. And that tension in thinking about what the workforce demographics need to be, what the opportunity needs to be for the emerging workforce, I think that is probably a really important topic for India to be thinking about uniquely.

Look, the kids coming out of college, my daughter just graduated this year from college, finding a job is actually incredibly hard for them because she is in programming. And to your point about using AI models effectively, those entry-level jobs in AI are being done by Claude or, you know, pick your favorite coding agent. We're investors, big investors in Anthropic, so we're champions of Claude. That's why it naturally came out of my mouth. So I do think that's a challenge, but the key is how do you train these kids to use AI effectively? And if you think about what an enterprise is going to look like that truly effectively uses AI, those enterprises are going to be a workforce where humans are managing agents, agents are managing humans. So it's a very different kind of organization. And learning how to work with these agents and having those skills are actually going to be almost as important as how effectively you can code to be able to work in these technology companies. So I do think the pedagogy has to change in terms of what you're teaching students as well. The education sector moves slowly, but we have to figure this out relatively quickly to say how do you train kids that are getting out of college to be very effective at using and managing AI for the day-to-day jobs.

I'm very optimistic. I think there are a lot of companies that are thinking through going public. Frankly, the second half of this year would have been where a lot of IPOs happened, but given the uncertainty because of geopolitics, I think that got pushed. But I do think now there's a lot more stability in the markets. The issue never was are there enough companies to call companies into public, the issue was more when do those CEOs want to put those companies into the markets where they control their destiny as much as possible. I do think next year is a very exciting year for that.

I'll give you a nuanced answer to that. First, Anthropic raised at a $160 billion valuation. I would say on a multiples basis, that was probably the cheapest deal that got done. The number is not as big, but their revenue is also big, so it actually wasn't a crazy multiple in that regard. So these model companies are actually accruing valuation because they're just on this hyper growth trajectory. So I think we just have to get our arms around the fact that there's a handful of these companies that got built to be very, very large very, very fast because of AI, because AI compresses progress. But on the other side, what that does create obviously is FOMO. Now everybody wants to fund the next research out of OpenAI or Anthropic in the hopes that they can build the next model. There's a lot of money going in there at extraordinary valuations, and it's very unclear to me what happens to that. So that to me is where if you were to say is there a bubble, there's a dynamic there that's very hard to explain except that if one of those got to AGI, it would be worth it. And so smart investors are saying let's index them all and hopefully one of them works and it'll be a good return.

And then I think if you look on the applied AI on top of that, going back to my earlier comment that diffusion did start this year, I actually think real businesses are getting built. And then you're going right after the labor spend, and these companies are capturing value and scaling very, very fast compared to the way SaaS companies and software companies got built 10 years ago. So in that sense, it's actually the exuberance around will science lead to new models where I personally feel discomfort. A lot of the other places we're investing, I have a lot of confidence that there are just extraordinary businesses to build there. So discomfort about research models, that's where I struggle as to how do you fund these research teams with such large amounts being spent predominantly on compute, not really knowing, these are science projects, you don't really know if they're going to work, and then they have to go build a business on top. So how do you really think about allocating capital to companies like that? Very hard to figure out.

I think the biggest amount of capital is going into these couple of models that have already sort of broken through and have escaped philosophy. So that I think is actually rational investing. If these companies were public, you wouldn't be questioning what's going on. So it's just public market behavior in the private markets. I just think valuations in the applied AI layer are aggressive, but they speak to the fact that these companies can create progress really fast. That doesn't really mean that's where the biggest issues are going to be in terms of capital loss and stuff. It really comes down to when FOMO sets in that everybody has to make decisions really fast because so many deals are happening and investors don't have time to properly think, you start to see undisciplined behavior. We just saw with crypto a few years ago, we seem to have forgotten about it and we're back onto that kind of behavior again.

It feels equally disciplined. In crypto, there was this huge sense that remote is the way to live, and so look, we're back right, so that was just a trend we started to bet on aggressively and see where that goes. With AI, it's different. It's more, are we just going to continue to have these incredible research breakthroughs? It's more like what happened with clean tech on the research side. And then on the application side, it's more like the internet where it was about distribution, now it's about transitioning labor into productivity. So it's like two bubbles in one almost. So one is around new modality and what it does to the labor productivity equation. The other is just science going and doing these breakthroughs, and that part is what scares me, and we've been very cautious about how you play in that.

Look, I think for ChatGPT, this is going to be the key challenge. Their cost structure and how you can effectively charge consumers for the service itself, how that's going to play out, and can you actually converge that over time? I think it's hard to see how that works now. But the market is so large that it's a very reasonable period to say you can grow into it, and there will be a very large company to build there. But they also have real competition from Google.

We're very optimistic about it. We're doing a lot in healthcare all over the world. In the US, it's a four plus trillion dollar market, and we can't afford to spend four plus trillion dollars on healthcare. So the question is how do you really build a proactive, variable, accessible system there that can get us off of filling up beds in hospitals, which is really what the business model is there today. In India, we think about how we not repeat what happened in the US. Can we actually from the beginning think about scaling the infrastructure in a way that's best for consumers first and foremost, which is their health, and invest in proactive care business models and then scale the infrastructure? You need more hospitals there. Money is another one that's on that journey, and so we did PB Health to create that kind of aligned peer provider relationship in healthcare. I think there's a lot to do there, and there's a whole workforce that needs to be created, and there's so much innovation happening in technology, especially in AI, that can be brought in to drive that proactive care. So I think India's got an opportunity to leapfrog in health just like they did in fintech. We're absolutely looking at more investments in that space in India.

We're very concerned. In fact, last year we launched the General Catalyst Institute. It's based in DC, focuses on Brussels and Delhi as well. And we are trying to be good thought partners to the administrations everywhere we do business to think about what these technology systems and these industry systems need to look like as we transform them for resilience and for AI. Because if you don't create a level playing field for startups, I think that has a lot of repercussions down the line.

Yes and no. My source of truth is I look at the companies we're backing right now. Companies that are trying to build the language models in healthcare or they're trying to transform services companies into AI companies. There are real businesses getting built, and I'm very confident that they will be interesting at scale public companies of the future. So I don't think that opportunity has gone away. I just think there's a scenario where the same thing could happen what happened the last 15 years where we create a few hundred billion dollars of value in the human venture entrepreneurial ecosystem and feel good about it, but then the big tech companies create a few trillion dollars of ecosystem. That could still happen again. And so a lot of our focus is how do we position these companies to scale? How do we give them real unfair advantages? So all of our own transformations so they have a chance to be relevant and at scale in their categories.

When N and I started talking about the strategy of how we make a difference in India over the next 10 years a couple years ago, one of the things we really leaned on was what we need is platforms in all the key industries. We're obviously very actively investing at seed stage for all the founders that we think are ambitious and have a good set of values and strategy. But on the other side of it, if we could build one or two platform defining companies in each of these industries that shape the arc of how they're going to be developed over the next 20 years, like Meesho, like Zepto, I think that would be really rewarding. Like Rafi in defense, that to me is where a lot of the value is going to be created, and we're going to feel very good about the fact that we helped create an ecosystem of innovation here that made a true difference.

I am actually, we were talking about this the other day. I'm very optimistic it's going to increase. First of all, not just in dollars, it's going to increase anyways because we're growing. But I actually think in terms of the percentage of what we're doing, it also could increase because you just look at the size of what these opportunities are, and you look at these IPOs that are happening, and you look at the kinds of companies that we're building now. They're as good as what we're doing anywhere else. And so it'll naturally just happen. I think that our allocation could go higher. It could be what happens to two times that when you look back in 5 years.

Look, I think that you will see one of the AI models go public at least. I think I know which one. Or a couple. I think we're going to look at workforce transformation will become a much more important topic. I think we're going to start to feel the effects of what these companies are doing, and that's what I think is important. And I think for India and in general actually, the IPO market is going to be very vibrant. I'm very optimistic we're going to see some great overall market activity.

I think so. After a bit of a lull and a break.

Great. Thanks for having me.

Very fast compared to the way the SaaS companies or software companies got built 10 years ago. So I think in that sense it's actually really the exuberance around will science lead to new models where I personally feel discomfort. A lot of the other places we're investing, I have a lot of confidence that there are just some extraordinary businesses to build. So discomfort about research models, that's where I struggle as to how do you fund these research teams with such large amounts being spent predominantly on compute, not really knowing these are science projects. You don't really know if they're going to work and then they have to go build a business on top. So how do you really think about allocating capital to companies like that? Very, very hard to figure out.

Well, I think the biggest amount of capital is going into these couple of models that have already sort of broken through and have escaped lastly. So that I think is actually rational investing. If these companies were public, you wouldn't be saying what's going on. So it's just public market behavior in the private markets. I just think valuations in the applied AI layer are aggressive, but they speak to the fact that these companies can create progress really fast. That doesn't really... I actually think that's not going to be where the biggest issues are going to be in terms of capital loss and stuff. It really comes down to when FOMO sets in and everybody has to make decisions really fast because so many deals are happening and investors don't have time to properly think, then you start to see undisciplined behavior. We just saw it with crypto right after crypto a few years ago. We seem to have forgotten about it and we're back onto that kind of behavior again.

Well, it feels equally disciplined. I think in crypto there was this huge sense that remote is the way to live and so all these... look, we're back, right? So that was just sort of a trend we started to bet on aggressively and see where that goes. With AI it's different. It's more: are we just going to continue to have these incredible research breakthroughs? It's more like what happened with clean tech on the research side, and then on the application side it's more like the internet where it was about distribution. Now it's about sort of transitioning labor into productivity. So it's like two bubbles in one almost. So sort of one is around a new modality and what it does to the labor productivity equation. The other is just science going and doing these breakthroughs, and that part is what scares me and we've been very cautious about how you play in that.

Look, I think for ChatGPT this is going to be the key challenge, which is their cost structure. And you can effectively charge consumers for the service itself. How's that going to play out and can you actually converge that over time? I think it's hard to see how that works. Now the market is so large that it's a very reasonable area to say you can grow into it and there will be a very large company to build there, but they also have real competition from Google.

We're very optimistic about it. So we're doing a lot in healthcare all over the world. In the US, it's a four-plus trillion dollar market and we can't afford to spend four-plus trillion dollars on healthcare. So the question is how do you really build a proactive, variable, accessible system there that can get us off of filling up beds in hospitals, which is really what the business model is there today. In India, a lot of what we think about is how we not repeat what happened in the US. Can we actually from the beginning think about scaling the infrastructure in a way that's best for consumers first and foremost, which is their health, and invest in proactive care business models and then scale the infrastructure? You need more hospitals there. Money is another one that's sort of on that journey. So we did P.B. Health to create that kind of aligned payer-provider relationship in healthcare. I think there's a lot to do there. There's a whole workforce that needs to be created and there's so much innovation happening in technology, especially in AI, that can be brought in to drive that proactive care. So I think India's got an opportunity to leapfrog in health just like they did in fintech. And more investments in that space in India, you talked about P.B. Health, but we're absolutely looking at more.