AI-Native Companies Will Outperform Everyone Else | Harvard Business School, Rem Koning

I wrote this paper 3 years ago looking at whether chat GPT delivered over WhatsApp could help small business entrepreneurs in Kenya for 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, the 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 GPT52 claudis 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 tapel and Birkshshire Haway 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. Hi, my name is Rem Coning. I'm a professor at Harvard Business School and I study entrepreneurship and 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. 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 sprint 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 and maternal health in Africa. You're seeing people build new edte 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 firm 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 headcount 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 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 uh 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 were trying to make Gamma pregenerative 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 headcount. And I think it'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 and Birkshshire 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 McKenzie, 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 cuz I think all of us are struggling how to allocate our own intelligence. like what should I have TGPT 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 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 claude 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. Whether you're applying 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 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. I wrote this paper 3 years ago whether chat GPT delivered over WhatsApp could help small business entrepreneurs in Kenya improve their business's performance. And what we found was really surprising, which was that 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. It would have been better had we never given them the AI. And what we find is that the reason for them is that they ask the AI a lot of questions. They use it, they interact with it, but they get a lot of advice from the AI and they don't know how to pick the good advice from the bad advice. They don't have the judgment to separate what's good from bad, which might explain why they were low performing in the first place. Conversely, when we look at the people who are performing really well, their uh revenues and profits were above the median before our experiment, the better entrepreneurs, we find that they actually did better. And when we look at the chat logs, the reason we see is that they're asking kind of the same sorts of questions as the low performers, but they're then following up and following the advice that isn't the bad advice, it's the good advice. Unless you've developed the judgment, the mental models to actually know where to apply it, it can lead you down a road of slop. And that slop can actually lead you to make less money. And it's really interesting as we've been working on this paper, it's now almost 3 years old, how it might look different now than back then. I think if we took Claude Opus and we put it behind WhatsApp, we get exactly the same results. The issue is you still have the same problem, which is that the entrepreneur asks a question and the AI gives them four or five plausible things to do and you need to know which one's actually right for you. So that's the first thing. The second thing is I think if we were doing the study now, we probably wouldn't do it through a chatbot. I think a big mistake you're seeing entrepreneurs make is that we're still stuck in the chatbot world. Chad GPT launched, it was huge. It changed the way we thought about artificial intelligence, about how we use our computers. And it changed us and sort of locked us into this idea that there was a a chatbot for everything. We'll have a chatbot for Shopify. We'll have a chatbot for these entrepreneurs. Harvard Business School has internal chat bots. We'll just build chat bots everywhere. And it turns out we don't need more chatbots. So imagine you go to a chatbot and it says, "Oh, you need to update your website so you can get more sales." If I'm a Kenyan entrepreneur and I don't know how to code, how am I updating my website? So I think if I was doing this study today, the thing that would be really exciting is giving more agentic AI, right, to the entrepreneurs today. Could you give them the tools to build better websites or launch better marketing campaigns? A lot of these entrepreneurs, they're struggling. They don't have extra money. They don't have extra staff. They don't have extra people to do something for them. Could you build them virtual employees that help them run their business and expand the things that they're good at and get more done during the day? these are people who are working hard and often the constraint is just time. They don't have the time to do it. Could you use AI to help them do more in the time that they have? Um, so that's something we're exploring in some current work right now, which I'm really excited about. And I think the more we get in the mindset of it's not going to be we're going to having these conversations with the AI, but that we're going to be telling them and they're going to go take actions in the world on behalf of us, I think that's really exciting. It's going to open up a lot more modalities in terms of interfaces, right? and maybe that we're talking to them like how we're having a conversation right now. I think it's also a key unlock for startups all around the world. You're never going to build AI systems better than open AI or anthropics. Sorry, they're at the frontier. They've got billions of dollars in funding, but what you do have is better contextual knowledge of a workflow, of a situation, of how things work in different parts of the world. And I think that can give you a real edge because if you can get that right context into the AI, oh my god, what it can do is absolutely amazing. And I think you're seeing no better example of this right now than with skills in cloud code, right? So people are making these skills. What are these skills? They're kind of context. They're like little snippets of how to do a particular task where you've told the AI how to do it. You've given it the context for how to think about it. And then we can share these skills with everybody else in the world. And it's just wild to see how effective this is at making the models better. I think more people will be entrepreneurs, right? more people are going to go out and build their own businesses and I think more people in companies are going to behave like entrepreneurs partly because we can all build now right and I think that's one of the things that's always attracted me to entrepreneurs whether you're building a car wash or building a a software company it's like you have to create something from nothing I think increasingly all of us are going to do it so the world is going to look a lot more entrepreneurial and then you look at developing markets and I think there's a opportunity for them to leapfrog like they've done with fintech right if you go to India India's payment infrastructure uh this thing called the UPI is light years ahead of the United States. You can pay with everything on your phone. It's unlocked billions of dollars in value, maybe even more. Um there's been a huge number of startups around it. They have these amazing financial g gateways. I think there's an opportunity with AI around this and sort of knowledge work around the world. But I think to do that, we need to make sure the AI systems have context from emerging markets. Do they know enough about the Kenyan entrepreneurs to guide them? I think thinking about what are the big knowledge problems in these places, particularly education, I think AI could have a profound effect there. I'm really excited to see more of the application layer come to emerging markets and I think there's reason to be optimistic, right? We've all familiar with the inference cost curves, right? The cost of, you know, calling a GPT4 quality model just keeps going down exponentially, you know, to a year from now, two years from now, it's going to be basically free. when things become basically free, I think it opens up a lot of opportunity to work in markets where people just have less money to spend. I think to get like really concrete on the business side, I think it can give people labor that they couldn't hire otherwise. There's often a lack of experts. Like you just can't find someone to help you with marketing. They're not there. They didn't get that college training. If I can hire a virtual agent who's as good as a marketer in New York or Silicon Valley and I'm in Nairobi, holy moly, is that amazing. I think that'd be a really concrete one. help them do their marketing, help them export more, help them skill their workforce potentially. When we sort of step back, then there's even a bigger question. How is AI going to transform the economy? And the flip side of more entrepreneurship is that I think we're going to see a proliferation of software tackling problems that we never even imagined it could tackle. Some of these are going to be really deep, like AlphaFold. That's going to be awesome. Some of these though are going to be much more mundane. So, I'm in Thailand and there isn't a CRM for my restaurant business. Well, now somebody's going to take Lovable or Codeex or whatever it is and they're going to make the world's best CRM for Thai restaurant owners and that's going to solve this person's problem and help that business grow. And I think there's probably millions if not billions of other problems that software could start to solve. And I'm really excited about that because software is awesome. Marginal costs are low. It's incredibly scalable. It can turn knowledge into something that can help millions if not billions of people. And so I think what we're going to see is a world that looks more like the software economy. I think there's a downside to that. If we look at the past 20, 30, 40 years, software has also led to potentially a concentration in wealth. We have these sort of, you know, mega billionaires at the top who have these marketplace platform and network effects businesses like Facebook that really h have controlled a lot of the digital ecosystem. And so I think there's a big question on the policy side of how we prevent that from happening again. I think one thing that's really exciting about vibe coding and how it might change the economy is that I don't think we're in a world of network effects. I think we're in a world of small like kind of SAS applications. I think we're in a world of uh bootstrapping businesses that don't need that VC investment. And so I am a little bit hopeful that this might be something that's going to spread prosperity more broadly. Though I do think we need to think about uh what it might do to the concentration of wealth if more of the world starts looking like software and tech. The most dangerous assumption they make is that by building with AI, they have made something people want. And that is just not true. Just like traditional software, you can build with AI and nobody can want it. I'm seeing this basically loop where people get stuck cuz the AI tools are so fun. So you're like, Claude, make me something. Codeex, make me something. And then you're like, let's add this other feature. And then like, let's do another one. And a month goes by and you've built the most beautiful piece of software. It's crazy overengineered. And then you launch and nobody wants it. And so I think some of the traditional stuff around building software still holds. Get it in front of users, have users play with it, see what they want. I think a correlary of that is a little bit of AI goes a long way. Going back to the example of Gamma, really the core of their AI at the beginning was let's just have people write a couple of sentences and then we'll generate a deck. Everything else was traditional software. That one unlock, oh my gosh, led to an amazing business. Can you find that one place in someone's workflow where you can apply a little bit of AI, just a drop or two, and that unlocks how they can do something, changes a problem that was really hard for them, that's what you really want to find. So, I think finding the smallest point where you can use these AI systems is really valuable. Somehow, it's going to give them an insight without them having the earned insight, right? I think it's more important than ever for founders to have a real earned insight, to have the judgment, to have the taste, to know how and where to apply these tools. I think that's the thing you need to spend your time on, not thinking about how do you get access to the next foundation model, whatever it is. Use last generation's model. It's probably fine for the purposes of what you're building. What matters is can you figure out where and how to apply it? And that's a different skill set than necessarily just cranking through the AI engineering. >> There are two things that are changing. how we're learning is changing and those who are really going to accelerate are going to be those who just realize you can be learning way more than you were before and you just need to unlock that. My name is Drew Bent. I lead education at Anthropic. One of the things that I think holds us all back is we give AI tools pretty simple problems when we could be giving them much more complex problems. We are not elevating our ambition with what we can do with these AI tools. As the AI tools get smarter, where could I push you further? Where could you have pushed me further? And eventually, if we're looking ahead, there will be in some cases, I think, this inversion of control where actually the AI model is doing some of the highest level strategic thinking and then delegating to you, the human for the areas that require human taste, human agency.

Rembrand M. Koning, Associate Professor at Harvard Business School, explains how AI is reshaping the playing field for entrepreneurs around the world. 00:00 Intro 1:30 Lesson 1: Your Organization isn't AI native yet 05:05 Allocate Intelligence 07:05 Lesson 2: Equalizer or Amplifier? - Why some thrive while others fall behind 11:57 Lesson 3: The Next Trillion Dollar Businesses - The playing field is shifting 17:16 Next episode 'The Thinking Mode' is EO's interview series exploring how the world's sharpest minds are navigating the age of AI. EO stands for Entrepreneur& Opportunities. As we're looking to feature more inspiring stories of entrepreneurs all over the world, don't hesitate to contact us at partner@eoeoeo.net LinkedIn | @EO STUDIO X | @eostudi0