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.

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

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.

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.

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.

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.

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.

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.

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.