[0:00]I wrote this paper three years ago, looking at whether chat GPT delivered over WhatsApp, could help small business entrepreneurs in Kenya. Four entrepreneurs who before our study were struggling, they had lower baseline profits and revenues. They saw a 10% decline in their profits and revenues from talking to the AI. Conversely, when we look at the people who were performing really well, revenues and profits were above the median before our experiment. We find that they actually did better. How it might look different now, I think if we took GPT-5.2, Clad Opus, and we put it behind WhatsApp, we get exactly the same results. Why would we get the same results if we got these better models? I think there's a really interesting thing when we look at the history of business. One way that you could get an edge was better at allocating stuff. The classic one is like allocating capital. Warren Buffett is better at allocating capital in Berkshire Hathaway than anyone else. Other companies are really good at allocating talent. I think we're in a world where increasingly what matters is your ability to allocate intelligence. If you can work that out better than other people, I think you've got an edge in the market.
[0:59]Hi, my name is Rem Koning. I'm a professor at Harvard Business School and I study entrepreneurship in AI. And I just like helping entrepreneurs do better. It could be a mogul in Silicon Valley, it could be someone selling coconuts in Indonesia. How do we help entrepreneurs bring new products to markets, compete better, grow their firms, and most recently thinking about the role of AI as something that's just going to unlock a crazy amount of entrepreneurial potential?
[1:35]How AI is changing the way we build firms? Right, we hear a lot about AI native firms and I think there are big questions about who can build them, uh how we scale them, how it changes strategy. So the AI Founder Sprints is an initiative that came out of InSEAD. We got over 500 entrepreneurs from all over the world, a quarter from Africa, a quarter from Asia, a quarter from the Americas and a quarter from Europe. All building around AI. You're seeing people building stuff for AI in maternal health in Africa. You're seeing people build new EdTech startups in uh India. You're seeing stuff come out of Kenya, you're seeing awesome startups uh coming out of Europe in the United States, and really what we did was we tracked how all these founders were using AI. I'll give you guys a little bit of a preview of the results, which is that when you teach founders to be AI native, when you tell them to really think about where they can apply generative AI, not just Chat GPT and like Claude, but the vibe coding tools, multimodal tools, all the agents that people are really excited about now. When you tell them to really think about where to use that in their firm to move it forward, it helps entrepreneurs everywhere do better. So if you're building in Nigeria, you are able to get more done every week, about 20% more, you're more likely to get customers, you're more likely to launch a product, you're more likely to have more revenue. And what's really crazy is, even though you're more successful, right, you're growing faster, what we see is that these same founders say that they want to raise less capital. So their demand for raising funds drops by 250,000. We're seeing folks really reimagine the workflows in their farm and build custom AI solutions. So maybe the bottleneck for you is getting customers. How can you build new AI systems that automatically build out a marketing strategy and a go-to market plan? And not just build the plan, but then execute it. And so that was one of the things that was most exciting I think from the sprint was seeing how people were taking whatever the bottleneck for their firm was, it could be marketing, maybe it was product development, and they were using the off-the-shelf tools, but then building basically their own agents if you will. Right? So instead of head count, suddenly we're scaling just with on-demand compute and that completely changes the economics of a business and what's possible, particularly for founders outside of Silicon Valley. I think a great example of it is Gamma. I think the first thing that's really important when you're thinking about AI native is to understand that the value comes from two places. One is the process. You use AI in your coding, you use AI to do customer support tickets. And I think that's what we're all really familiar with, which is that we're sort of using AI to make our work go faster or make our work better. And that gives Gamma an edge, it helps. But really the key to Gamma is the way they've embedded AI into their product. And I think the key for AI native is that you're not just using it to do the work, you're embedding it in the product so that the AI can directly do the work with the customer. You want to take you as the human out of the loop. I love humans. We're amazing. It's great being on this call. It's great talking to people. I love sharing stories. But the problem with humans is we don't scale particularly well. And so if you're trying to make Gamma pre-generative AI, they'd probably have to employ, I don't know, tens of thousands, hundreds of thousands of graphic designers. The economics of the company would collapse, but instead by putting AI into the product, what Gamma is able to do is scale with compute rather than head count. And I think that's a really exciting thing that if you're trying to be an AI native founder, that's what you need to find. Where are those places you can create loops where the AI is working with a user or another AI or something on the website where your team doesn't even need to be involved? That's the key to building AI native organizations. Allocating intelligence. I think there's a really interesting thing when we look at the history of business. One way that you could get an edge was better at allocating stuff. The classic one is like allocating capital. So you have uh Warren Buffett is better at allocating capital in Berkshire Hathaway than anyone else. He knew where to put his money and that made amazing, amazing returns. Other companies are really good at allocating talent. So if you look at a company like McKinsey, big consulting company, they're really good at working out who should become partners, who should they hire at the base of the pyramid, matching that talent with the right clients, what they're really good at. I think we're in a world where increasingly what matters is your ability to allocate intelligence. And what that means is you need to allocate what is done by different models, what are you going to have Claude do? What are you going to have lovable do? What are you going to have Grock or DeepSeek do? Right, thinking about how you blend, how you orchestrate, how you allocate your product to these different sorts of intelligences is just incredibly important. But I think this is the the key, which is that you also need to work out how to allocate what's being done by the AI and what's being done by humans. Because at the end of the day, we still have some edge over some of these models. And even if they're better or faster at thinking, often we think differently. And when you're thinking about strategy and you're thinking about how to gain an edge in the market, it's not about necessarily doing something better. It's about doing something different, doing something in a way nobody else can. And so if you can work out how you bring your human intelligence and you allocate jobs in the company to humans and the places where they can add value over and above the models or do things differently than the models can, and then you work out how to blend those together, I think that's a place where we're going to see a source of advantage moving forward. And it's a really exciting time to play because I think all of us are struggling how to allocate our own intelligence. Like what should I have Chat GPT do, and what should I do is a thing I know I struggle with every day, but increasingly this is going to be a question at the strategic level for firms. Like what should you as an entrepreneur do, right? And what should you give to an AI and which AI should you give it to? If you can work that out better than other people, I think you've got an edge in the market. Is AI an equalizer or an amplifier? I'm going to say the standard professor answer, which is it depends or maybe it's both. Um but let's get a little bit deeper. We all now can code with lovable. We can all build amazing decks with Gamma. All of us can use Chat GPT and Clad to get rid of typos and have a copy editor in our pocket. Wow, it is an equalizer. Right, it is amazing, it moves everybody up. Right, we can all do so much more. But here's the problem, right? I think that's for the existing work that we do. Weather you're playing AI over an existing task that you have, or you're building a new sort of business. When you're building a new sort of business, a new sort of product, when you're thinking about how AI is going to change your firm, be it a small business or a tech startup, the returns to thinking about how AI can do this are going to be greatest for those who have the ability to do that. And those are going to be people who are already pretty good. Those are going to be people who've developed the judgment, maybe they started a company before, they probably have a stronger technical background. Those are the people are going to be able to imagine the really big wins and get those huge returns. They're going to see their judgment, their agency amplified.
