233. How AI changed tech entrepreneurship and investing in 2024 and what’s to come

Think AI is just about adding chatbots to your business?

Think again.

In 2024, AI has completely transformed who can build tech companies and how they're funded - but there's also dangerous hype that's already landing companies in legal trouble.

We're in what economists call 'The Middle Times of AI' - a messy period where massive opportunity meets massive hype.

Some founders are building million-dollar businesses with lean teams, while others are getting fined by the SEC for false AI claims.

Listen to this episode to learn:

• Why prototypes that once cost $32,000 can now be built for free
• How the SEC is cracking down on fake AI companies
• Why technical co-founders are no longer essential for tech startups
• How to spot real AI opportunities in the middle of the hype
• Why new tech hubs are emerging far from Silicon Valley

Whether you're a founder saving thousands on development, a corporate innovator testing ideas without permission, or an investor avoiding AI washing, this episode will help you navigate the reality of AI in 2024.

Resources mentioned in this episode:

• Tech for Non-Techies episode 155. How generative AI is changing business and the economy
• Legal Drive: SEC fines companies $400,000 for false AI claims

Timestamps

02:42 AI’s Role in Product Development

05:05 The Middle Times of AI

07:26 Revolutionary Opportunities in AI

09:47 Jack Ma’s Prediction on AI

12:10 AI’s Impact on Start-up Teams

14:24 Global Opportunities in Tech

16:49 The Dangers of AI Hype

19:15 How AI Will Transform Start-ups

21:40 Actionable Steps for Founders and Investors

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Transcript

Sophia Matveeva (00:00.522)
AI has transformed tech entrepreneurship in 2024. Some changes have been revolutionary, and some have been utter nonsense. And in this episode, I'll help you separate the real opportunities from the hype and show you how to prepare for what's coming, whether you're a founder, corporate innovator, or investor.

Sophia Matveeva (00:23.822)
Welcome to the Tech for Non-Techies podcast. I'm your host, tech entrepreneur, executive coach at Chicago Booth MBA, Sophia Matveeva. My aim here is to help you have a great career in the digital age. In a time when even your coffee shop has an app, you simply have to speak tech. On this podcast, I share core technology concepts, help you relate them to business outcomes, and most importantly, share practical advice

on what you can do to become a digital leader today. If you want a great career in the digital age, this podcast is for you. Smart people, how are you today? You know, even though it is the middle of December, I'm actually about to wrap up my last Tech for Non-Technical Founders cohort for this year. But I have also just started teaching another programme on No-Code tools

in an accelerator that literally runs throughout Christmas and the New Year. And the demand for this knowledge is just insane. And there are people who have no intention of stopping, and they're my kind of people. So I love the kind of people who have no intention of stopping even for a minute if they see a great opportunity. And this got me thinking, why is there so much more demand now for these kinds of skills? And what does this mean for the future? Well, apart from obviously being very good for the Tech for Non-Techies business,

AI has really changed the game this year, both on the innovation and on the investing side. And that's what we're going to cover in this lesson. And in this episode, you're going to learn how to use AI to save a world of cash in product development. You're going to learn what regulators are doing about fake AI companies so you don't become one. And this is actually quite serious.

You're going to learn why we're in the middle times of AI and why this creates massive opportunities for those who really understand the AI adoption curve. And also we're going to cover practical steps for how to take advantage of the AI opportunity right now. So for founders, we'll cover how to use AI in your fundraising. For corporate innovators, we'll talk about how to test your ideas without asking for permission. And for investors, we're going to talk about how to spot real AI innovation.

Sophia Matveeva (02:42.658)
...versus hype. And before we dive in, if you're enjoying Tech for Non-Techies and learning something valuable, then please take a moment to rate and review the show because your reviews really do help me keep making this high-quality content for free for you. And also it helps other smart people discover the show. And you know what? Spotify listeners, you leave reviews way more often than Apple listeners. And I don't know why, but Spotify people, thank you. I see you, and I love you.

I really appreciate you. And Apple people – hello, what are you doing? This is high-quality free education from somebody who has taught at Oxford University and written for the Harvard Business Review. So be nice. Be nice. Give this show a rating. Thank you in advance.

Anyway, I think I told you before that when I first made a prototype for my first-ever tech start-up, for my first-ever app, it was about eight to ten years ago now.

I worked with a professional design team to whom I paid £24,000, which is about $32,000. And we took two weeks to make two prototypes and test them with our users. And this is basically just what we had to do before starting to work with developers.

And today – literally this month – founders in my Tech for Non-Technical Founders class create prototypes using AI tools in a day. And then they get feedback from their target market the day after.

And most of them use free versions of the existing AI tools. And you know, some splash out 20 bucks for a monthly subscription, but that is definitely less than $32,000. And this isn't just about saving time, and this isn't just about a shedload of cash. And also, it's not about not working with professionals later on, because I do believe you have to work with professional designers and professional developers later on.

But there is a fundamental shift in the early stages for innovators and for investors. And the early stages are where a lot of great opportunities die. This is why I think it's really, really important to understand.

But you know, these good things – these good parts of AI innovation – are not the only thing that I wanted to talk to you about today, because there are great results, but there are also some dangerous and illegal results. And my aim is for you to be discerning and use your own brain

Sophia Matveeva (05:05.152)
and common sense in this age of AI hype. Because I don't want you to only see the good things without knowing about the bad things. Without knowing about the bad things.

And in this episode, I'm going to share four ways in which AI has changed tech entrepreneurship and investing. And then we'll talk about predictions, about what's to come, and what you can do better.

Okay, so to understand what's really happening with AI and entrepreneurship, let's talk about where we are in the AI revolution as a whole.

So there are three economists whose work I really appreciate. They are AJ Agrawal, Joshua Gans, and Avi Goldfarb. And they have a great book called Power and Production: The Disruptive Economics of Artificial Intelligence. And in this book, they talk about three phases of tech adoption.

So the first phase is simple. In the AI context, companies use AI to make better predictions in their existing processes.

So that's like using AI to predict which customers might leave or which products might sell best. And companies have been doing this for ages. If you've been shopping on Amazon or watching Netflix, you already know.

And so the second phase is where we are now. And this is what the authors of the book call The Middle Times of AI. This is when companies completely redesign their systems around artificial intelligence. And this is messy, and it's complicated.

Because you're not just adding a bit of AI to an existing process, you are reimagining your entire business, and you're reimagining how your entire business could work.

And the third phase is when these new AI-first systems become the norm. And we're definitely not there yet. And I'm going to show you what I mean with a technology that we all know and use – and that's electricity.

So let's think about the early days of electricity. So first, factories just added electric motors to their old steam-powered machines. And this was fine. But the real revolution came when factories were redesigned around electrical power. Because suddenly you could put machines anywhere, not just near the steam engines.

And that's exactly where we are with AI, because some founders are just adding AI chatbots to their websites or using AI to write better emails. And this is great. You should definitely do this.

Sophia Matveeva (07:26.488)
But that's like adding an electric motor to a steam engine. Do you see what I mean? But there are also some founders who are asking: if we built this business from scratch today with AI, what would that look like? What would our business model look like? What would our costs look like? What would our reach look like?

And this transformation characterises the middle times. And this is a great opportunity for founders, investors, and corporate innovators because the thing is, when AI is fully adopted, when we are in that third stage, it's going to be really hard to actually make money out of it. Because, well, think about this: the first industrialists to have factories powered by electricity became super rich. They're like the robber barons we think of, right? They're the people who have wings in the Metropolitan Museum of Art named after them.

But if you start a factory today and said that your factory is powered by electricity, literally people would be like, "Yeah, of course it is." Right?

So this is why the opportunity is now, and now is the messy time – but opportunities come out of messy times. When everything is already working, and everybody knows what to expect, it's generally really hard to find opportunities. It's actually true in politics as well, but that's another story.

Anyway, if you want to know more about the theoretical framework of AI adoption, listen to episode 155 called How Generative AI is Changing Business and the Economy, where I interviewed Professor Avi Goldfarb. The link to this episode is in the show notes.

And you know, I really like it when successful non-technical founders make predictions because they are the people that I'm most inspired by. So Jack Ma, the billionaire founder of Alibaba, who is a non-technical founder,

he recently said that the great changes brought by the AI era in the next 20 years will exceed everyone's imagination.

Now, honestly, when tech billionaires make grand predictions about AI, I usually roll my eyes. But this time, I do think that there's substance behind the hype, and it's worth listening to Jack Ma.

So first, Jack Ma is extra special. He did not see his first computer until the age of 30, and he began his career as an English teacher.

Sophia Matveeva (09:47.64)
So to me, he's like the patron saint of non-technical founders. Because honestly, if he was just a tech bro saying that technology is going to change everything, well, that wouldn't be this surprising. But somebody who essentially looks at opportunity first and technology second – that's the kind of person we want to listen to.

Anyway, now I promise you these four points about how AI is changing tech and investing.

So point one: the first area where AI has changed tech entrepreneurship and investing is in product development and market testing. We had a full episode on that a few episodes ago, so just go back and listen to it if you haven't yet.

So there's this Google Ventures method of bringing new ideas to life, which they describe in their book called Sprint. I've used that method – it's really good. But anyway, according to that method, it basically says that if you want to create a new app,

for example, you need to first create a prototype. That’s basically something that doesn't have any code in it – it's essentially a bunch of pictures that look like an app. Then you need to test this prototype with five people to get meaningful feedback.

As I said earlier, with AI tools, you can now create this prototype in days – not weeks – and for free, not for thousands of pounds. And for corporate innovators, this is revolutionary.

Because you no longer need to write a 50-page business case and wait for the finance director's approval or for IT approval. You can go rogue – wonderful! You can build a quick prototype yourself, with your hands, and test it with five people.

Then you can go to your boss with actual evidence that people want this thing. And then, yes, you will have to submit yourself to the approval process. But when you have evidence, it is hopefully going to be much easier.

Okay, the second point about how AI is changing tech entrepreneurship and investing is about start-up team structures. Because you really don't need a technical co-founder to get started – you really don't.

You also just don't need as many expensive people at the start. Previously, before No-Code tools and AI became what they are today, you needed full-time developers plus a designer plus somebody to handle business development and product management.

Sophia Matveeva (12:10.622)
And that person – the product manager and business development person – that's basically going to be you. So as a founder, you’ll be managing the product, bringing in the money, and setting the vision. It's a lot of work. Anyway, you also need to manage and pay expensive developers. Usually, you need a back-end developer, a front-end developer, a designer, and maybe a community manager. Right? So basically, you have to pay for developers and a designer before you even know if anybody wants your product. So it’s risky, right?

But now I’m seeing non-technical founders get much further with a lean, flexible team because you can use AI to handle initial product development, and you can also get freelance developers to step in for specific technical challenges. So you can create a minimum viable product – basically a coded thing, which is not going to be super amazing – but you can create something that is going to be used by customers, and maybe you’ll even get some early revenue for it.

Then you can actually either raise money or say, “Okay, maybe we can get our first big customer and get that big customer to prepay for a year.” With that prepayment, you can hire a proper full-time team. One of my students has done this, and it’s really working out well for her. She literally just created a simple MVP with some freelancers. Then she got one of her corporate clients to pay, I think, $120,000 upfront for a year. She basically used that money to cover development. Super genius.

Anyway, so instead of hiring a full-time tech team immediately, you can build your first product with a combination of AI tools, no-code platforms, and part-time technical talent. This means you can validate your tech business at a fraction of the previous cost.

Then you can scale up to a full tech team when you actually have evidence – and maybe even some money – that what you have is a proper business innovation and a tech innovation as well.

Okay, now let’s move on to point three. The third massive change is about going global because AI is redrawing the map of where successful tech companies can be built.

Sophia Matveeva (14:24.942)
So remember how everyone used to say that you have to be in Silicon Valley to build a successful tech company? Well, thankfully, that is wrong. It’s wrong in 2024, and it’s going to be even more wrong in 2025. And I am rejoicing.

When you can use AI to build your first product, test it with users, and handle customer service, what really matters is understanding your local market and your industry deeply.

This is why we’re seeing tech hubs pop up everywhere, from Detroit to Chicago to Berlin to Bahrain. These hubs are not trying to be the next Silicon Valley. Instead, these places are playing to their unique strengths. Because if you understand the shipping industry in Dubai, for example, or the energy sector in Houston, or the banking sector in London, then you can build and scale a tech company right there, where your expertise and your customers actually are.

And also, you don’t have to pay insane Silicon Valley prices, you know. I am normally based in London. London is literally one of the most expensive cities in the world. But honestly, every time I go to Silicon Valley, I feel like I need to bring my own sandwiches. It is that expensive.

OK, now I’ve given you three points so far, and they were all good points. So I told you the good stuff about AI. And now I’m going to move on to the fourth point, which is about the nonsense, the hype, and the exciting illegality.

All right. I’m seeing too many start-ups slapping “AI-powered” on their pitch decks when they’re basically using the same technology as your coffee shop loyalty app. There’s also just way too much stupid money chasing anything with “AI” in the name.

And if you’re an investor listening to this podcast, you’re just not allowed to do this because you’re better than that. You have a brain.

You have common sense. So listen to this: In March 2024, the Securities and Exchange Commission in the US fined two investment firms $400,000 for false AI claims. I mean, 400 grand for investment firms – that’s not that much. But the fact that we’re about to make fun of them – you know, the loss of reputation – that’s important.

Because these companies were telling clients they used AI algorithms for investment decisions.

Sophia Matveeva (16:49.836)
…when they actually didn’t. I’m going to post a link to this report in the show notes because one of the companies even claimed to be the first regulated AI financial advisor, but they had no evidence to back this up. And so, essentially, when they were fined, SEC chairman Gary Gensler even went on the record saying: “We’ve seen time and again that when new technologies come along, they can create buzz.

Those purporting to use those new technologies should not mislead the public by saying they’re using an AI model when they’re not.”

So the SEC is taking this seriously, and they will issue press releases basically calling you a liar. That is not good for business.

So here’s what you need to know: just using ChatGPT to write your emails does not make you an AI company. Using basic automation does not make you AI-powered, and using AI tools to build your product does not mean your product itself uses AI.

I totally recommend you do all of these things, but just be honest about what you’re doing. Be honest about the kind of company you’re building. If you’re an investor, really examine any kind of AI claims properly.

Because, yes, AI is transforming business, but not every company needs AI. Not every AI company is going to be the next big thing. That’s just a basic truth of capitalism.

And this kind of messiness is what I talked to you about in the middle times of AI, because there’s massive opportunity, but there’s also massive hype, and there’s just disruption and messiness – people lying about what they’re doing, but then also real innovations being dismissed. This is where the opportunity is.

Okay. Now let’s talk about predictions. Let’s talk about what’s coming next.

So first of all, start-up teams. In this theory about the middle times of AI, let’s kind of go back to that factory example. In the olden days, factories were built around a central steam engine with complex systems of belts and pulleys powering every machine. Everything had to be arranged around this power source.

And that’s exactly like traditional start-ups, where everything has to flow through the technical team. So if you want to change a button on your app, you have to ask a developer. If you need to update a pricing page, you need a technical ticket.

Sophia Matveeva (19:15.552)
If you want to test a new feature, you have to get in line for engineering resources. And so, what happened in factories? Factories started adding electric motors to old machines, and this helped, but it wasn’t transformative, as we discussed earlier.

Start-ups today are using AI tools but keeping their old way of working. Okay. We already discussed that. So, if you’re using ChatGPT for content or MidJourney for design, you’re basically operating a traditional company where technical talent is still the bottleneck.

So that’s the middle times. But the real revolution came when factories were redesigned around electricity, remember? Because suddenly you could put machines anywhere, you could create assembly lines, you could work around the clock, and the whole concept of manufacturing changed.

And this is where we’re heading with start-up teams. Just like electricity freed machines from the steam engine, AI will free start-up functions from being held hostage by technical talent.

I mean, we obviously still need engineers. I know there are some engineers listening to this – we need you. We love you. Because, after all, somebody needs to write these AI algorithms in the first place, right?

But for start-ups, especially in the early testing phase, the dynamics of building and testing products will be fundamentally different. Just like the assembly line transformed manufacturing workflows, AI will transform how we build and validate business ideas.

AI is also going to help us by allowing non-technical people to do things that were previously only done by developers. Imagine a start-up team where AI doesn’t just help with tasks but actively coordinates work around the team. Maybe it spots market opportunities, suggests product features based on user feedback, and helps make strategic decisions.

I’m already teaching founders to use AI for these functions, and I can see how much more they’re getting done.

We are in the early stages of this right now. As adoption improves and as the tools get better, we’ll see entirely new business models emerge with high margins when AI is built into companies from the start.

But this is crucial: it has to be real adoption and not the AI-washing that Gary Gensler from the SEC is talking about.

This brings me to my next point. Now you know what’s happened, and now you can expect what’s to come. What can you do about it?

Sophia Matveeva (21:40.482)
So if you’re a founder, here is an action step: take your last investor pitch deck and create a new version using AI as your thought partner. Then ask ChatGPT or Claude what questions investors are most likely to ask you about your pitch deck. Then ask it to help you with the answers.

So you can actually rehearse your presentation with AI. You can ask it to help you generate questions. You can ask it to help you generate answers. By the time you actually have a conversation with an investor, you’ve rehearsed this.

I recently taught a session on fundraising for an accelerator run by Deezer. I literally taught founders how to do this. A lot of them had been using AI already, but they kind of never realised that actually they could have AI help them create a pitch deck and prepare to pitch – really like a thought partner.

As a result, the founders’ presentations were so much better, so much more thoughtful, and they were basically so much more prepared.

If you’re a corporate innovator, here’s my tip for you: find a project that got rejected this year for being too expensive to test. Then just create a quick prototype using AI tools like Galileo and UI Wizard and show your boss how you could test your idea for free. Maybe even do the test yourself.

Create this product, and then just run the test with five potential customers. That validates your idea.

And finally, if you’re an investor, look at your portfolio or look at your deal flow and do this exercise: literally remove AI from every pitch deck, and then ask yourself what value remains in this company. If it wasn’t going forward with “We’re an AI company; we’re using AI to do X, Z”, is there still an opportunity?

This will help you spot the difference between genuine innovation and AI-washing.

Because you do not want Gary Gensler to come for one of the start-ups you’re investing in, right? That would be embarrassing for them, but it would be really embarrassing for you – and a loss of money. And I don’t want that for you.

So, my dear smart person, this is all for today’s episode. We’ve had quite a lot today. Well done for listening, and well done for investing in yourself with this episode.

If you found this lesson helpful – which I assume you did because you are still here –

Sophia Matveeva (24:01.196)
please leave this show a rating and a review because it really does help other smart people find this show, and it makes me happy. So make me happy.

Anyway, on that note, have a wonderful day, and I’ll be back in your delightful ears next week. Ciao.