If AI Models Have No Moat, What Are Investors Buying? with Benedict Evans

**Benedict Evans** (0:00)
When you automate away work, you can always see the jobs that are going to go away because they're right there, and you don't know what the new jobs are going to be. Human needs are infinite. How many people are earning a living from making podcasts now? Imagine predicting that 10 years ago. There's a stage in the evolution of the market where, like, if you're still arguing about that, you're an idiot. But there's a stage at the beginning where you might have opinions about some of these questions.
You're probably not even asking the right questions. That, I think, is where we are with this stuff today.

**Bernard Leong** (0:32)
Welcome to Analyse Podcast, the premier podcast dedicated to dissecting the pulse of business, technology and media globally. I'm Bernard Leong, and the AI cycle is no longer about just better models. It is becoming a capital markets test of infrastructure, distribution and energy.
Anthropic and OpenAI are moving towards public markets. SpaceX is preparing one of the most consequential listings in technology.
Anthropic's launch this morning of Cloud Faber 5 shows how front-end capability now becomes bundled with safety, access and governance questions. These headlines point to the same deeper story. Massive capex, increasing commoditized models, shallow but enormous user reach, and a new battle over who controls the curation layer over infinite intelligence. Today, we test whether the model layer becomes a utility, where durable value actually accrues, and how AI reshapes work and competition globally. With me today, recurring guest, Benedict Evans, independent technology analyst behind AI Eats the World. Benedict, welcome back.

**Benedict Evans** (1:36)
Thanks for having me.

**Bernard Leong** (1:37)
So, since our last conversation, what have you been up to recently?

**Benedict Evans** (1:41)
I've been on lots of airplanes. People want to know about this AI thing you may have heard about.

**Bernard Leong** (1:47)
Yeah, I guess when we talk about AI, right? I just want to go straight to the question. I guess early this year, you have started updating your presentation every six months now. Yeah. And AI is eating the world. Probably now is in the 2026 edition. So, I think I want to start off first with the biggest question, which is OpenAI, Entropic and the public market test. So, one article that I really enjoy reading, since I'm a subscriber of your newsletter, is how will OpenAI compete? It's that the frontier models are pretty much near what we call commoditization with no network effects.
And now, everybody is trying to buy compute time and this is not a mode. So, both OpenAI and Entropic are now heading towards a public near trillions dollars capital market cap. So, what is the public investor actually buying, if not a mode?

**Benedict Evans** (2:40)
Well, so, there are several different questions embedded in that. The first of them is like at the moment, there's no apparent winner takes all effect in models. There's not, and this is a kind of a subtle but important distinction.
There's a difference, there are things that you're doing that no one else can do, no matter how hard they try, that they won't be able to do because of the nature of their business, that they won't be able to catch up no matter how much money you spend. Because that's where Google is in search. It doesn't matter how much money Microsoft spends, they can't catch up. And that's what happened with YouTube and with iOS and Windows and Instagram, that there are kind of inherent structural reasons why it's really difficult for them to lose their position. And we don't see equivalents of those in large language models yet. Now, the big challenge, of course, is we don't know how this market is going to evolve.
And some people have a problem with that statement, too. But at the very early stage of this market, you don't know how it's going to evolve. We also don't know how the science works, and we don't know how the science will change. So stuff may happen that means there are network effects. But right now, there aren't. And so you're in the situation where you've got, pick a number of sort of three to six companies spending a lot of money, and then maybe anything up to a dozen companies that are willing to be three to six months behind. But there's not some mechanic that means that if one of them gets ahead, they'll get further ahead.
And so what we see now is, you know, Anthropic got Claude working and we got product market fit, and you got got coding working, product market fit. There's not some inherent reason why it's just impossible for Google and OpenAI to catch up with that and to get their own things working. They may do, they may fail to execute, but there's not, you can't kind of predict that. And so that's a sort of a base observation. The models are all kind of the same, with the same kind of benchmark scores, the same kinds of evals.