Episode summary
Why Investors Are Reducing AI Exposure
The Markets
· · Guests: Rich Privorotsky
Summary
Rich Privorotsky says the market’s crowded “long AI, short everything else” trade is unwinding as investors reassess three linked risks: higher capital costs, power and financing constraints for AI buildouts, and rising competition at the model layer. He argues that de-risking has pushed growth expectations lower and helped rally bonds, while the biggest pressure points are concentrated in semis, hyperscalers, and the more levered parts of the AI trade.
For third-quarter earnings, he says the key issue is not just whether mega-cap tech keeps spending heavily, but whether that spending is turning into cloud growth, backlog conversion, and revenues. The market is now focused on the quality of delivery, not just the size of CapEx, and he says the credit market will be sensitive to how quickly these companies approach free cash flow break-even.
He also frames the backdrop as a shift from a savings glut to a spending glut, with government deficits, AI CapEx, and high energy prices all lifting the cost of capital and lowering risk appetite. While he thinks the setup is messier and conviction is lower, he still prefers selected electrification, aerospace, and parts of transports, with some upside if energy conditions improve.
Key takeaways
- Privorotsky says the AI trade is de-risking as higher capital costs, power constraints, and model competition hit consensus positioning.
- He says investors will judge hyperscalers on whether roughly $1.1 trillion of expected next-year CapEx translates into cloud growth and revenue.
- He warns that credit markets are increasingly sensitive to how quickly AI-heavy companies reach free cash flow break-even.
- He describes the macro regime as a shift from a savings glut to a spending glut, which raises the cost of capital and pushes out lower-quality borrowers.
- He remains cautiously optimistic on selected electrification, aerospace, and transport names, especially if energy markets stabilize.
Notable quotes
“People were very concentrated within AI, within semis, within hyperscalers”
“we've had questions about the ability to actually energize and deliver gigawatts”
“it's not enough just to say that you're spending a lot of money, but you also need to demonstrate that backlog is converting into revenues”
“we've had a massive FCI tightening, and that has in a sense also pushed the Fed to do more”
How the episode opens
This is The Markets. I'm Chris Hussey, and today is Thursday, October 22nd. And I'm joined from the Goldman Sachs trading floor in London by Rich Privorotsky, who is head of European Equities Trading within FICC and Equities.
Privo, thanks so much for joining us. Thanks for having me, Hussey. All right.
Let's jump into it because I've been reading everything you've been writing about, and you made a great point, which was that earlier this summer, the pain trade, the trade that people were having to chase was long AI, short everything else. It had become a little bit of one big trade. Now that seems to be unwinding as we go into third quarter earnings season.
What's going on? How do you see it playing out from here? There's just been an immense amount of concentration in the equity market, and I got to say that the past few weeks have been particularly painful for those types of consensual trades.
People were very concentrated within AI, within semis, within hyperscalers. And I would say that there are probably three different issues the market is kind of grappling with right now. One is obviously we've had a spillover in terms of the cost of capital, and I think we're seeing that pretty much everywhere.
Whether it's triple C spreads, sovereign spreads in Europe, but also at the very pointy end within some of these more levered parts of the AI trade and the neoclouds really stand out. And so that's become a question of supply. You know, will those corporates have struggle to find financing to deliver all this AI spend?
The second point being on supply, that we've had questions about the ability to actually energize and deliver gigawatts, and the spread is kind of 20 at 40, 50 gigawatts for next year.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai trade
- capital costs
- tech infrastructure spending
- mega-cap earnings
- energy prices
Companies and tickers mentioned
- GS
- Goldman Sachs
Watch the episode
Watch “Why Investors Are Reducing AI Exposure” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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