We Asked the Man Who Mapped the AI Economy If the Boom Is Real — And Who Keeps the Money

**SPEAKER_1** (0:00)
We are excited to announce the launch of a new podcast, The Intangible Economy with Kai Wu. AI and the broader technology revolution are changing how we live, work and create value. In each episode, Kai will sit down with investors, researchers and other experts to discuss how innovation and intangible forces such as brands, human capital and network effects are transforming markets and investment outcomes. In this episode, Kai is joined by exponential view founder Azeem Azhar. They discuss the economics of the AI boom, whether demand can justify the massive investment, where value may accrue across the AI stack, and a lot more. To continue receiving new episodes of The Intangible Economy, subscribe on all major podcast platforms using the links in this episode description. Thank you for listening. We hope you enjoy the new show.

**Kai Wu** (0:35)
Over the past few episodes, a central topic of discussion has been the multi-trillion dollar AI investment boom.
Massive capital spending has helped propel markets higher, while leaving stock indices increasingly concentrated in companies tied to the AI buildout. Some of the biggest questions facing investors today concern the sustainability of AI demand, the pace of technological progress, and where, importantly, economic value will ultimately accrue across the AI stack. To help answer these questions, I'm glad to introduce my friend Azeem Azhar, a technologist, investor, author, and entrepreneur, who has been thinking deeply about the impact of frontier technologies for many years. Azeem is the author of The Exponential Age, How Accelerating Technology is Transforming Business, Politics, and Society, and the founder of the excellent Exponential View newsletter. Azeem, thanks for coming and welcome to The Intangible Economy.

**Azeem Azhar** (1:25)
I'm so excited to have this conversation with you, Kai. I've learned so much from your essays over the last couple of years, so I'm looking forward to it.

**Kai Wu** (1:34)
Me too. Let's start with the report on The State of the AI Economy, which you just released a couple of weeks ago. Congratulations. By the way, it was excellent. Thank you. The idea is this, that the supply side of the AI boom is relatively visible. We can observe chip sales, capital spending, and data to get into reconstruction. But really the demand side is much harder to see. You attempted to reconstruct that demand from the bottoms up.
What did you find?

**Azeem Azhar** (2:01)
Well, we found that there was a real economy underneath all of this, underneath all of those orders that are improving Jensen's collection of leather jackets.
It's a company spending real money, and our model, our estimates came in at, to the year, to the June 2026, $110 billion for the previous 12 months, absolutely China being spent on generative AI. And that includes, you know, Main Street firms buying from OpenAI or Anthropic, or from Cursor, or from 11 Labs, through to consumers spending on their consumer products, whether it's big ones that we're familiar with, or some of the more niche products. And it also includes where OpenAI, and Anthropic, and other Labs are spending on training capacity through the cloud companies, the Hyperscalers and the Neon Clouds. And that $110 billion, just to put it in subcontext, was the trading 12 months. But if we annualize the June number, we got to $175 billion annualized. And what that implies, of course, is that the growth rate has stayed high. And roughly speaking, the growth rate is about as high in the summer of 2026 as it was in December 2025 That surprised us, by the way. Kind of when we went into the work, we thought the growth rate was going to slow down.
And I think the other thing, just to put it in subcontext for your listeners, is that it's about three times faster than the previous sort of internet-oriented way. It takes the internet itself, mobile apps and ads and Klanos. So it feels real. You can slice off a little bit here and there for, if you want to, but ultimately, there's this not bad. It's north of the $100 million.

**Kai Wu** (4:01)
And so obviously, there's different components of AI demand. How did you go about deduplicating and avoiding double accounting? So a dollar of the end user demand that goes to an application, how does that kind of filter through all the way to the bottom?

**Azeem Azhar** (4:17)
Yeah, so we used a number of different approaches. I think in that the deck is 65 pages long, there are five pages of methodology slides. It felt a little bit like a physics PhD in that sense.
So we approach this in a number of different ways. One is that we do bottom up assessments of a thousand or so companies that claim to be in the generative AI space, and some of those are more well-sourced than others. So when you see confirmed precedence, you can do something with that.