OpenAI's deals are looking a little frothy

Summary

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Podcast Summary

The Indicator from Planet Money

Episode: OpenAI's deals are looking a little frothy
Date: October 16, 2025
Hosts: Darian Woods, Waylon Wong
Guest: Gil Luria (Head of Technology Research, DA Davidson)

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Overview

This episode delves into the eye-popping, multibillion-dollar deals taking place in the artificial intelligence sector, with a focus on OpenAI’s ambitious (and some say inflated) financial commitments. The hosts examine the AI data center construction boom, explore whether the market is entering bubble territory, and discuss what these moves could mean for the broader economy and for individual investors.

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Key Discussion Points & Insights

1. The AI Deal Frenzy

• Recent Mega-Deals:

  • OpenAI’s $300 billion commitment to Oracle for computing power
  • Nvidia's intent to invest up to $100 billion in OpenAI
  • The financial logic and realism of these pledges are questioned

  “It's all starting to get a little heady. $100 billion here, $300 billion there. Nvidia paying OpenAI who pays Oracle, who pays Nvidia? We're going to have to break it down.” — Darian Woods [00:48]

2. The Data Center Boom

• Unprecedented Growth:

  • Acres of data centers being built across the U.S.—from Las Vegas to Northern Virginia
  • Massive investment from tech giants like Amazon, Microsoft, Meta, and Google
  • Data center construction is now roughly 1.2% of the U.S. GDP, about $1,000 per American

  “According to the Financial Times, around 1.2% of America's economic output is going to Amazon, Microsoft, Meta and Google building data centers. That's roughly $1,000 for every American.” — Waylon Wong [02:31]

  “Microsoft, Amazon, Google, the largest companies in the land with almost infinite resources can't build data centers fast enough...they're doing that to catch up to how good all these AI tools are getting.” — Gil Luria [02:53]

3. Applications & Stakes

• AI models are surpassing new benchmarks every few weeks, with use cases ranging from coding and legal reviews to medical research and entertainment.

• The race echoes the early days of search engines, where one winner (Google) captured the market thanks to network effects. Investors and companies are moving as if AI is a similar winner-take-all market.

  “This winner takes all dynamic may or may not apply to AI, but companies are acting as if it does, trying to become the best AI company, as if the best AI system is going to get most of the cash.” — Darian Woods [04:18]

4. OpenAI’s Unique Position and Risks

• David vs. Goliaths:

  • OpenAI, though influential, is much smaller than the big tech powerhouses (Microsoft, Amazon, Google, Apple, Meta, Elon Musk)
  • To compete, they must raise dizzying sums quickly

  “They are a small scrappy upstart at competing in a sport of kings. In order to participate in the AI market, you need tens of billions, if not hundreds of billions of dollars.” — Gil Luria [04:32]

• Funding Tactics & Questions:

  • The guest points out much of OpenAI’s committed spend is “artificial”—commitments without actual capital to back them.
  • OpenAI is losing about $10 billion per year and would need to raise enormous debt to fulfill promises.

  “When OpenAI made a $300 billion commitment to Oracle, it didn't have that capital. It won't have that capital. That was artificial. It's not real. It's inflated.” — Gil Luria [06:20]

  “Right now they're losing $10 billion a year.” — Gil Luria [07:17]
  “I've heard Sam Altman say that making a profit is not even one of his top 10 concerns.” — Darian Woods [07:34]

5. Signs of a Bubble?

• The term "inflated demand environment" is used instead of "bubble," but the implications are clear.

• Gil Luria carefully avoids labeling the surge in deals as a full-fledged bubble—emphasizing it’s hard to identify a bubble while you’re in it, especially in a fast-evolving area.

• The “web of deals” between companies creates an ecosystem where their fates are intertwined.

  “Nvidia, Oracle, OpenAI, AMD are engaged in this exercise of funding each other that creates the impression of demand that's even greater than it really is.” — Gil Luria [06:20]

  “We're not using the word bubble.” — Waylon Wong [09:16]

6. Potential Risks to the Broader Economy

• Investor Exposure:

  • Many Americans, via their retirement funds, are exposed to these tech giants
  • Speculation: If OpenAI reneged, could it trigger cascading failures?

• Worst-Case Scenario:

  • Overbuilt, underused data centers sit idle
  • A possible chain reaction in tech stock declines and a broader economic slowdown

  “Would OpenAI reneging on its commitments bring down the rest of the economy?” — Darian Woods [08:29]

  “The glass half empty view is that AI won't be as transformative as promised, and that this could bring down companies and investors in some kind of chain reaction.” — Waylon Wong [08:50]

7. Reasons for Optimism

• Guest’s Perspective:

  • Gil Luria believes the AI buildout will persist, with the healthy parts driving productivity even if there are corrections.

  “The AI buildout will continue. It's just a matter of what parts of it are healthy and what parts of it are unhealthy...We just need to get through the unhealthy parts in order to focus on the great benefits that are going to accrue to us from artificial intelligence.” — Gil Luria [09:27]

• Historical Parallel:

  • Even after railroad busts in the 1800s, the infrastructure endured; likewise, today’s AI investments may leave lasting benefits.

  “Lots of railroad companies went under after the railroad booms and busts in the 1800s, yet we can still ride those tracks today. Exciting new technology can be a bumpy ride.” — Waylon Wong [09:57]

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Notable Quotes & Moments

• On AI's promise and profit focus:

  “I've heard Sam Altman say that making a profit is not even one of his top 10 concerns.” — Darian Woods [07:34]

• On the language of bubbles:

  “That sounds like a euphemism to me. An inflated demand environment.” — Darian Woods [05:38] “I'm trying to avoid using the word bubble.” — Gil Luria [05:42] “Why use one word when you can use three?” — Waylon Wong [05:45]

• On economic impact:

  “Like it or not, if you have a retirement account, a decent chunk of your money is invested in companies like Nvidia, Microsoft, Amazon, Google and Oracle.” — Darian Woods [08:29]

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Major Segments & Timestamps

• OpenAI & Mega-Deals Overview — [00:12-01:13]
• Data Center Construction Boom — [02:18-03:34]
• The Dominance Race & Winner-Take-All Logic — [03:51-04:29]
• OpenAI’s Position and Funding Moves — [04:32-05:22]
• Bubble Debate & Artificial Demand — [05:22-06:55]
• Potential Consequences for Markets — [07:04-08:29]
• Optimism & Historical Lessons — [09:27-09:57]

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Tone & Takeaways

• Tone: Witty, skeptical, and analytical, with analogies to previous tech booms and busts.
• Main Takeaway:
  While eye-watering deals and a buildout frenzy define today’s AI landscape, much of the headline money may be more notional than real. History suggests transformative technologies have always had booms and busts—but deliver long-term gains in the end.
  The episode urges listeners to balance excitement with caution and to note that while not every deal is sustainable, the technological progress is real and lasting.

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Transcript

[NPR Announcer]

NPR.

[Darian Woods]

There has been a whirlwind of gargantuan AI deals recently, often involving OpenAI.

[Waylon Wong]

Oh yes, the softly spoken wizard of ChatGPT, Sam Altman has been busy. There was this $300 billion deal with the database and cloud company Oracle. Basically, OpenAI said it would $300 billion worth of computing power from Oracle. But how would OpenAI pay for that? It's unclear.

[Darian Woods]

Yeah, we're going to get into that.

[Waylon Wong]

We'll also talk about Nvidia. It came in soon after saying it would invest up to $100 billion in OpenAI.

[Darian Woods]

It's all starting to get a little heady. $100 billion here, $300 billion there. Nvidia paying OpenAI who pays Oracle, who pays Nvidia? We're going to have to break it down. This is the indicator from Planet Money. I'm Darian Woods.

[Waylon Wong]

And I'm Waylon Wong. Today on the show OpenAI's deals, we look at the AI data center boom and how the world's most valuable startup is trying to win the AI race.

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[Darian Woods]

To untangle all the OpenAI deals, we're going to start from the ground floor and we're going to. What's happening on the ground floor is acres and acres and acres of data center construction from Las Vegas to Northern Virginia.

[Waylon Wong]

According to the financial times, around 1.2% of America's economic output is going to Amazon, Microsoft, Meta and Google building data centers. That's roughly $1,000 for every American.

[Gil Luria]

The data center buildout is happening at an incredible rate right now.

[Waylon Wong]

Gil Luria is the head of technology research at DA Davidson, an investment firm.

[Gil Luria]

Microsoft, Amazon, Google, the largest companies in the land with almost infinite resources can't build data centers fast enough. You need land, you need access to power, you need chips, you need electricians and H vac engineers. But they have the resources, they have the capital, they have the money. And so they're doing that to catch up to how good all these AI tools are getting. So we can all use Sora to create silly little 10 second clips of cats giving us advice or raccoons fighting with each other and driving away.

[Waylon Wong]

I can just see that in my alley IRL late at night. But more seriously, AI can be used for reviewing legal files, doing a lot of computer coding grunt work, or speeding up medical research. Every few weeks, the many AI models keep hitting new benchmarks.

[Darian Woods]

It feels kind of like the early days of search engines when we had AltaVista, ask Jeeves.

[Waylon Wong]

Do you remember any more Yahoo MSN search?

[Darian Woods]

Yeah, yeah, yeah, yeah. So eventually a search engine came out that was better than all the others. And it could stay better, at least partially because it had so many users giving it data. That was Google, of course. Now this winner takes all dynamic may or may not apply to AI, but but companies are acting as if it does, trying to become the best AI company, as if the best AI system is going to get most of the cash.

[Waylon Wong]

And that puts OpenAI in a tough situation.

[Gil Luria]

They are a small scrappy upstart at competing in a sport of kings. In order to participate in the AI market, you need tens of billions, if not hundreds of billions of dollars.

[Waylon Wong]

Gil says that Microsoft has that money. So does Amazon, Google, Apple, Meta and Elon musk.

[Gil Luria]

And so OpenAI needs to raise a lot of capital very fast in order to have access to the compute that will keep it competitive.

[Waylon Wong]

And that brings us to all those weird seeming deals that OpenAI has been making. The $300 billion promise to Oracle, the $100 billion Nvidia is investing in OpenAI. And to think about whether these kinds of deals make sense, Giloria says to make a distinction with all the AI data center investment.

[Gil Luria]

There's a lot of stuff that's real. The AI tools are fantastic. There's a lot of companies willing to pay for access to those AI tools. There is also a part that is an inflated demand environment.

[Darian Woods]

That sounds like a euphemism to me. An inflated demand environment.

[Gil Luria]

I'm trying to avoid using the word bubble.

[Waylon Wong]

Why use one word when you can use three?

[Darian Woods]

He's not getting paid by the word to Be clear.

[Waylon Wong]

But seriously, the word bubble is kind of a loaded term in economics. It's a situation where the price of an asset is way above what it's really worth, and it's followed by a panic and a crash. But there's a debate over whether you can truly identify a bubble while it's happening, especially when the future is so unclear, like in technology. Galuria isn't using the B word, but he does think the companies might be pumping up more excitement than is warranted.

[Gil Luria]

Nvidia, Oracle, OpenAI, AMD are engaged in this exercise of funding each other that creates the impression of demand that's even greater than it really is. When OpenAI made a $300 billion commitment to Oracle, it didn't have that capital. It won't have that capital. That was artificial. It's not real. It's inflated. That's not to say OpenAI is inflated. OpenAI has phenomenal success and great products and great product design. It's just that it's writing a lot of checks that it really can't cover anytime soon.

[Darian Woods]

Yeah. Where would it get that $300 billion from?

[Gil Luria]

Well, good point. They're going to have to raise all this capital, mostly in the debt markets, so they're going to have to get hundreds of billions of dollars of debt to finance a startup. That's never happened, and it's unlikely to happen at that scale again. OpenAI will be successful. They have great products, they'll continue to grow, but right now they're losing $10 billion a year.

[Darian Woods]

I've heard Sam Altman say that making a profit is not even one of his top 10 concerns.

[Gil Luria]

Yes, and that's understandable, because startup companies rarely focus on profits first. They focus on getting as many users as they can, and that's the mode OpenAI's in. So, yes, they'll continue to grow, but they just need to continue to fund their losses. They can't make the type of commitments they're making and then live up to them. So that part of the story is inflated.

[Waylon Wong]

If Gil is right and the recent Open AI deals are inflated.

[Darian Woods]

I mean, even Sam Altman told the Verge in August that he thought investors were getting overexcited.

[Waylon Wong]

Right. And it does raise the question about what could happen to the rest of the economy. These kinds of deals are not just limited to OpenAI. Meta Xai anthropic. These are other companies raising money in atypical ways right now.

[Darian Woods]

And like it or not, if you have a retirement account, a decent chunk of your money is invested in companies like Nvidia, Microsoft, Amazon, Google and Oracle. And this web of deals ties their fates together to some extent. So the question is, would OpenAI reneging on its commitments bring down the rest of the economy?

[Waylon Wong]

The glass half empty view is that AI won't be as transformative as promised, and that this could bring down companies and investors in some kind of chain reaction which just be left with these unused data centers humming all around the country to the chagrin of locals who are already pushing back at all this construction. It would vanquish the one clear bright spot in an economy suffering from slow jobs growth and tariff uncertainty.

[Darian Woods]

It'd be the inflated demand bursting.

[Waylon Wong]

We're not using the word bubble.

[Darian Woods]

Yes, and that burst demand could trigger a recession.

[Waylon Wong]

No, don't say recession.

[Darian Woods]

Well, there's good news. Giluria doesn't actually share those concerns.

[Gil Luria]

The AI buildout will continue. It's just a matter of what parts of it are healthy and what parts of it are unhealthy. The healthy part will continue. The chats and the video generation and the voice interaction will make us all more productive. We just need to get through the unhealthy parts in order to focus on the great benefits that are going to accrue to us from artificial intelligence.

[Waylon Wong]

Lots of railroad companies went under after the railroad booms and busts in the 1800s, yet we can still ride those tracks today. Exciting new technology can be a bumpy ride.

[Darian Woods]

And if you want to hear more about those fights between locals and AI data center construction, we have an episode coming out soon on that very topic. Stay tuned. This episode was produced by Angel Carreras with engineering by Jimmy Keeley. It was fact checked by Sarah Juarez. Kate Concannon edits the show and the indicator is a production of npr.

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