Episode summary
Not Once in 18,900 Tries | Michael Mauboussin on What History Says About AI Growth
Excess Returns
· · 1 hr 1 min · Hosts: Kai Wu · Guests: Michael Mauboussin
Summary
Michael Mauboussin argues that the current AI boom should be judged against history, and history is skeptical of the growth rates now being priced in. Using a base-rate framework, he says OpenAI’s implied path from $3.7 billion of 2024 revenue to $145 billion in 2029, later revised to $185 billion, would represent a growth pattern he could not find in roughly 18,900 firm-year observations since 1950. That does not make the outcome impossible, but it makes it an extraordinary outlier rather than a reasonable base case.
He extends the same logic to the infrastructure buildout behind AI. Large projects are notoriously hard to execute, and the data center race combines modularity with major risks around permitting, energy, cooling, and timing. The key strategic question is who captures the value if AI proves transformative: Mauboussin thinks much of it should flow to consumers through competition, while companies will differ sharply in how well they deploy the technology.
The conversation broadens into intangible assets, which Mauboussin says now dominate corporate investment and help explain why large firms can scale faster than in the past. But intangibles also create fatter tails: more winners, more failures, and more uncertainty. For investors, his central message is to focus less on labels like “asset light” and more on how much a company is investing, what return it earns, and how much capital it must raise to sustain that return.
Key takeaways
- Mauboussin says OpenAI’s implied 2029 revenue growth would be unprecedented in about 18,900 firm years of U.S. data since 1950.
- He argues AI data-center buildouts should be judged with base rates from large projects, where on-budget, on-time delivery is rare.
- He thinks AI’s value may mostly accrue to consumers unless firms can sustain differentiation or operational advantages.
- He says intangible-intensive businesses have similar average returns to other firms, but much larger standard deviations and fatter tails.
- He warns that investors should focus on ROI and capital intensity, not the “asset light” label, because the investment is often just shifted off the balance sheet.
Notable quotes
“the answer is no company had ever done it before, right”
“you have more really great businesses and more businesses that go bust, right”
“I think the high level my assumption is a bunch of that value should probably acrue to we should ultimately assume it's going to be consumer surplus right”
“the devil's in the details here. So there are a lot of there are a lot of judgments that go along with this”
How the episode opens
Just to give you a sense of the uh OpenAI um numbers specifically in 2024 they did revenues of $3.7 billion and they are forecasting for 2029 $145 billion. Right? So that's a 108% compound annual growth rate.
It turns out when you do that 75 years of data you have about 18,900 you know firm years or like you know things you can examine and the answer is no company had ever done it before. When you think about intangible intensive businesses versus non-intangible intensive businesses, it turns out the average that the means and medians are not that different for those distributions returns on capital or growth. But what is what is very substantial is that it's just a much larger standard deviation.
So you have more really great businesses and more businesses that go bust, right? So the on average you're seeing about the same thing, but you get more much fatter tails. Welcome to the first episode of the intangible economy with Kaioo, where we explore how intangible assets, innovation, and technological change are reshaping investing.
I can't think of a better guest to kick this off than Michael Moesin. Michael, welcome.
Thanks, Kai. And by the way, I'm I'm just super honored to be one of your first guests and uh I'm a huge fan of the work that you do. So, I'm really really looking forward to our conversation today.
Me, me, too. It's a lot of my my research has been inspired by the work you've done over the years. I think this will be a lot of fun. Um, okay. So, let's kick it off. Um, dive right in. Um, one of the biggest questions today, of course, is how investors should be thinking about navigating the current AI boom.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai growth expectations
- base rates and forecasting
- intangible assets and moats
- ai capital cycles
- value capture in ai
Companies and tickers mentioned
- MS
- OpenAI
- Morgan Stanley
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Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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