Markets Wrap: Trouble Ahead For The AI Money Machine?

Summary

Merryn Talks Money – Markets Wrap: Trouble Ahead For The AI Money Machine?

Date: July 31, 2026

Host: John Stevick (guest hosting for Merryn Somerset Webb)

Guest: Neil Callanan, Managing Editor (EMEA), Bloomberg Private Companies

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Episode Overview

This episode focuses on the current state of the AI industry, exploring how the so-called "AI money machine" is funded and whether recent turmoil signals deeper issues to come. Host John Stevick and guest Neil Callanan dissect the market’s recent roller coaster, the structure of the AI value chain, the risk of circular financing, and the growing concerns about the sustainability of AI’s explosive growth—especially as competition from China accelerates and new risks emerge in both equity and credit markets.

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Key Discussion Points & Insights

1. Recent Market Turbulence in AI-Exposed Stocks

• South Korea's Kospi Index:

  • The Kospi, heavily influenced by AI-related giants SK Hynix and Samsung, surged 35% YTD before falling 34% in just one month—a “proper roller coaster moment.” (02:54)
  • Retail investors piling into leveraged ETFs exacerbated swings.

  “It's actually still up 35% on the year, but in the last month it's fallen 34%. Okay, that's a proper roller coaster moment.”
  —John Stevick [02:54]

• Underlying Cause:

  • The “fear that China is catching up” in AI technology, especially with sudden leaps in memory chips and language models. (03:59)
  • The market is wrestling with the possibility of cheaper, competitive models from China threatening established Western leaders.

  “China's emergence in AI... is really concentrating minds at the moment.”
  —Neil Callanan [03:59]

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2. Demystifying the AI Value Chain

• Industry Structure:

  • Lithography machine makers (e.g., ASML)
  • Chip foundries (e.g., TSMC)
  • Chip designers (e.g., Nvidia)
  • Data center “AI hotels” (e.g., Amazon, hyperscalers)
  • AI model creators (e.g., OpenAI, Anthropic), who sell to enterprises and end-users

• Massive Scope: The chain now drives “massive boom in energy” and construction, affecting sectors far beyond just tech. (07:31)

  • For example, data center energy requirements may be equal to “powering 225 million homes for a year just for data centers by 2030.”

  “You're seeing a massive boom in energy... people are talking about needing up to 300 gigawatts... by 2030. That's enough to power 225 million homes for a year just for data centers.”
  —Neil Callanan [07:31]

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3. Funding Frenzy & Debt Dynamics

• Flood of Capital:

  • Hyperscalers have become the largest issuers of corporate investment-grade debt, eclipsing even banks (09:59).
  • Companies like Alphabet (Google) experiencing negative cash flow for the first time in their public histories.
  • Raising the question: Is the growth in spending outpacing actual revenue or demand, and creating structural market risks?

• Circular (Vendor) Financing & Systemic Risk:

  • Many deals involve companies buying from and selling to each other in a closed loop—raising the specter of “vendor financing” and potential market distortions reminiscent of the dot-com/fiber optic bubble (11:56).
  • Risks include mispricing assets, creating “false impression of demand,” and exposing the industry to regulatory and systemic shocks.

  “These circular deals can create a false impression of demand. And you may think that these companies are generating massive revenues, but if it's all just moving around... then if something falls out of bed, then there could be wider implications and that could become systemic.”
  —Neil Callanan [13:03]

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4. Credit Market Contagion and Lending Practices

• Diverse Sources of Capital:

  • Funding now taps everything from private credit to investment grade bonds to junk bonds, as the AI sector “has had to go to pretty much every corner of the credit market” (17:38).

• Parallels with 2008 Mortgage Market:

  • The packaging and slicing of debt for data centers is reminiscent of the mortgage-backed CDO market pre-2008, though not quite at the same level of risk—yet (18:23).

• Speculative Real Estate Risks:

  • “Speculative lending” for data centers (building before securing tenants) is expanding—prompting concern about future “white elephants” if evolution outpaces occupancy (18:53).

  “If you can get finance... from a bank or from a private credit lender, that says something about bubble territory, because they are taking a complete risk that you are building this thing... and you will find somebody to occupy.”
  —Neil Callanan [18:53]

• Tighter Lending Conditions:

  • The credit markets are becoming more discerning; terms are tightening and risk premiums are rising, especially after high-profile delays or market stresses.

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5. China’s Rise and the Price War Threat

• Competitive Pressure:
  • China’s “cheap electricity” gives it a major advantage, allowing AI model tokenization at much lower cost.
  • Western hyperscalers may see their anticipated profits squeezed if customers switch to cheaper Chinese alternatives—especially if internal use cases are trivial or inefficient (20:32).

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6. Retail Investor Risks & Market Psychology

• Retail “Hot Money”:

  • Retail investors, especially in Korea, have been highly exposed to leveraged products and high volatility, leading to heavy losses in the downturn (22:00).

  “If I had leveraged several times, I would be looking at that and going oh my God. So it's understandable in a way...”
  —Neil Callanan [20:32]

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7. Equity Issuance, Capacity, and the Next Shakeout

• Unusual Net Equity Issuance:

  • The AI boom may reverse decades of “de-equitization” (companies buying back or delisting shares), as capex needs drive new issuances (23:01).

• Investor Discrimination Will Grow:

  • Investors will become pickier about which stories to back. Short interest and corrections in recent tech IPOs (e.g., SpaceX) are signs of renewed skepticism (23:01).

• Liquidity and Capacity Warnings:

  • Credit capacity could be stretched just as everyone needs it—drawing on recent warnings from major fund managers (23:01).

  “[Credit] capacity is needed at its greatest extent just as people are pulling back. And that's something you have to be a bit fearful of, I think.”
  —Neil Callanan [23:01]

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Notable Quotes & Memorable Moments

• On AI as an Economic Driver:

  “In the US in particular, it's driving a lot of the economic growth. And any slowdown in this kind of spending will be negative for growth, not necessarily turn recessionary... but it would be negative for growth.”
  —Neil Callanan [07:31]

• On Market Timings:

  “Often we have taught these things and two weeks later the market has said, oh, oversold and it's popped right back up and often exceeding the previous highs, obviously. But at the moment it's definitely a moment. It's just the length that that moment takes.”
  —Neil Callanan [23:01]

• On Caution for Leveraged Investors:

  “…the market can remain excitable for longer than anyone can remain solvent, especially if you're invested in a leveraged ETF. So just be careful out there.”
  —John Stevick [24:42]

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Timestamps for Key Segments

• 02:54 – South Korea’s Kospi crash and AI stock volatility
• 03:59 – China’s rapid emergence in AI technology
• 05:45 – Mapping the AI value chain (hardware to end users)
• 07:31 – Energy and construction ripple effects; systemic capital risk
• 09:59 – AI hyperscalers’ record bond issuance, shift from cash-rich to highly leveraged
• 11:56 – Circular financing “bad word” origins and AI ecosystem implications
• 13:03 – Infrastructure parallels, misaligned incentives, and regulatory hazards
• 17:38 – The multiplicity of AI credit-market funding avenues
• 18:53 – Speculative risk in data center development
• 20:32 – China, cost pressures, and market panic among retail investors
• 23:01 – Outlook for equity issuance, market selectivity, and liquidity concerns
• 24:42 – Closing reminders about market volatility and leveraged products

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Episode Tone

Relaxed, conversational, and accessible for non-specialists, with clear analogies (“roller coaster,” “field of dreams,” “white elephant”) and a healthy dose of contemporary market skepticism. Both speakers use vivid language and historical comparisons to contextualize risks.

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Final Thoughts

• Market exuberance in the AI sector is real but carries deep systemic risks, from circular financing to speculative credit and potential oversupply.
• China’s technological progress and cost advantage could upend Western AI economics faster than many expect.
• Retail investors are highly vulnerable to volatility, especially through leveraged products.
• Both equity and credit markets are recalibrating how much exposure they’re willing to take on in the face of uncertainty and rapid innovation cycles.
• The key message: Be wary of hype cycles, understand where the real demand is coming from, and don’t overextend in frothy environments—especially in the AI gold rush.

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This recap skips all advertisements, sponsor messages, and non-content interludes, covering only the substantive conversation between John Stevick and Neil Callanan.

Transcript

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[John Stevick]

Foreign. Welcome to the Merlin Talks Money Market Wrap, where we talk about the biggest moves in markets this week and what's been driving them. I'm John Stevick, senior reporter and author of the Money Distilled newsletter, and joining me in the studio today is Bloomberg's private company's managing editor, Neil Callanan. Neil covers hedge funds, asset management, and real estate in emea. So in today's show I basically wanted to talk about the AI industry. I wanted to give a structure of what it's actually about, lay it out so that you can understand it better who's producing the chips and who's producing the models, and then wanted to look at how that's funded and why. There are some concerns about perhaps the circularity of some of the deals in the industry, and Neil has written a lot about that. Thanks very much for being with us today, Neil. It's great to have you on the show.

[Neil Callanan]

Thanks for having me, John.

[John Stevick]

Not at all. We're recording this on Wednesday. And probably the biggest story so far this week has been the route in the South Korean Cosby Index. Basically, this is driven by the fact that cospi is. Half of it is comprised of two stocks that are related to the AI boom, and that's sk, Hynix and Samsung. Also, there is an element of retail investors getting in over their heads because they've been able to buy all these leveraged ETFs. And so the cost went up a lot and then down a lot. One of the stats that really jumped out at me is that it's actually still up 35% on the year, but in the last month it's fallen 34%. Okay, that's a proper roller coaster moment. But does this tell us or what does this suggest is about the overarching AI story? Because it's not just about Korean leverage. There's other stuff going on too, isn't there?

[Neil Callanan]

Absolutely. And Korea, in a way, is a special case because Korea has almost gamified the finance industry and the stock market. And you mentioned the leverage ETFs, but they've been big on crypto and tether and things like that, stablecoins for a long time. And a lot of those investors in retail have grown up very accepting of those levels of risk. And in many cases, it has paid off. So, as you said, the cost is still up this year, despite the rout in recent weeks. But what is driving a lot of the change at the moment is the fear that China is catching up. And China's emergence in AI, which was always going to happen, but perhaps faster than people thought, is really concentrating minds at the moment. And we have seen in the past when deepsea came out of nowhere and released its models, the market disruption that that caused. And now we're going through a kind of second bout of that, where in the space of just over a week, you've seen massive progress in terms of memory chips, in terms of language models. And so China is definitely emerging. And one of the things around all the spending that we're seeing in AI is the assumption is that people are willing to pay for it and we pay a for it going forward. And then suddenly if you have these cheaper models coming out of China and people start switching to that, then what happens with the names we're all familiar with, like OpenAI and anthropic. And so there's definitely fears in the market about that at the moment. And I think People are definitely taking pause globally as a result of that. At the same time, a lot of this money is going to be spent. There is an investment case for it. It's whether it' getting ahead of itself at the moment. And certainly in terms of valuations, it did seem to be getting steamy at one point this year.

[John Stevick]

Yeah, I mean, I thought we'd just kind of lay out roughly the AI industry and the business model because I think a lot of the time we sort of talk about AI and it's quite an amorphous kind of blob. And a lot of time we're thinking about ChatGPT and we know Nvidia is in there somewhere and all the rest of these things. But so I always kind of looking at it and actually I was talking to AI about it and getting a sense of what the kind of value chain is. So you've got the machines that make the. So you've got the companies that make the machines that make the chips. And that's like your SML that makes the kind of lithography machines. And then you get the chip foundries themselves. And that's like the Taiwanese company tsmc, you've got chip designers and that's Nvidia. So they're the ones that basically do the kind of value add element, isn't it? It's like they're making the brains for these things. Then all of these chips go into big AI hotels, the kind of data centers, and they're run by the same people that run what we used to call Internet hotels, the kind of data servers like the Amazons and all the rest of this world. And then you've got the people who actually make the AI models. And the AI models, the brains of the AI live on the data centers. And that's like your OpenAI. And then they're selling them to companies, either big enterprise providers who can garnish their existing offerings with AI, or end users like me and you, or smaller companies. Is that about the size of it? Does that kind of sound about right in terms of what the AI value chain is and who all the companies are involved in this?

[Neil Callanan]

100%. But this is so massive now, that encompasses everything else as well. So they need energy. And so we're seeing a massive boom in energy. And people are talking about needing up to 300 gigawatts of additional energy power by 2030. That's enough to power 225 million homes for a year just for data centers. Now those things have to be built as well. You have to get people to build the data centers and build the energy infrastructure, et cetera. So construction firms are taking off as well. And so in the US in particular, it's driving a lot of the economic growth. And any slowdown in this kind of spending will be negative for growth, not necessarily turn recessionary, anything. But it would be negative for growth in the US but this goes back your point about in the end, it comes back to the end users, goes back to my point about China in a way, which is that we need people at the end to be paying for these services in order to justify these investments. When you look at the amount of money that are being spent by some of the hyperscalers in particular, which are these Internet hotels originally, as you described them, if you look at Alphabet's recent filing, forward spending commitments rose $500 billion essentially in three months. Now, future revenue growth grew, but not by anything close to that. And that goes back to the fears people have about this entire ecosystem that is sucking up so much in, so much capital at the moment that people are going, well, I don't know whether I want to have as much exposure as I could have to this. And you're starting to see that in the credit markets as well, where people are becoming much more discriminating about the deals they invest in and the price they're willing to pay. And they're also hedging a bit more this week. Core Weave's cds, which is a form of hedging against default risk that's risen to almost a record. Core Weave is one of these companies that is like a rework of the GPU world is the chips and they basically rent out to other people what they're doing. People have become much more cynical in the last few weeks about deals, partly because they know so much of this stuff is coming to the credit markets that they don't have to buy everything. The question is whether people in the AI industry, as a wider thing, have become too complacent about the idea that the credit markets will be there and be supportive of them. And that's not necessarily always going to be the case.

[John Stevick]

Well, I think that this is fascinating from that point of view in that there really has been a deluge. Bond issuance hasn't. I mean, we're talking about, by some measures now, the hyperscalers are the biggest issuers of corporate investment grade debt. And you're used to it being the banks. And the other point about hyperscalers is that before all this, they were basically running on their own cash generation, they were deemed as being essentially impregnable balance sheets. While it's not negative that they've started raising or not started, they've now got a lot of debt. For example, Alphabet, its latest quarter was its first negative free cash flow quarter. Ever since it listed. It's just a sort of saying that how much is out there and how these businesses are fundamentally being changed by this. And then you throw in China, maybe turning around and doing it all much, much cheaper and suddenly you're kind of like, oh, wait a minute, your earnings are going to be crushed or, sorry, the earnings that we're hoping that you get might get crushed by this. And one thing I thought was really interesting going back to the debt point is you were involved in putting together this very complicated and now famous in a sort of local way chart about how this is all being financed. And one of the big things that's I think, slightly worrying people as well is that a lot of the money seems to be coming from the people who raised the money in the first place. Almost a form of vendor financing where you've got companies that kind of make the chips, paying the people who buy the chips or who are going to rent the data centers that use the chips. Can you talk to us a bit more about that and how that's kind of pan in?

[Neil Callanan]

Yeah. What happened late last year was I was sitting there reading story after story about these deals where companies were doing deals with other companies in the AI universe. Nvidia has always been at the center of this, but the likes of Google and Anthropic and OpenAI were doing all these as well. And I literally couldn't keep up. And so we just had the idea that maybe we need to do a visual here and kind of show the levels of circular deals that are happening. And this became something of a bad word in the 1990s with fiber optic. And when there was a big rollout of that and lots of spending and there was vendor financing and there was capacity sharing and various other things, and then a lot of those companies went bust when the demand wasn't there at the end, having invested in all that money. Now, of course, the irony of course, is that long term the economy benefited massively from that level of spending. It's just the companies involved in Norway, so many of them ended up going bankrupt.

[John Stevick]

Well, that's the infrastructure story, isn't it? The railways are still here and we still have trains, but a lot of companies have built them, went bust. And same with dot com.

[Neil Callanan]

And that happens with Most new technologies. And again, that goes back to why investors are being somewhat skeptical at the moment about that. But these circular deals, they can create misaligned incentives around things like, are you making the decision in the best interest of the company? Are you making it in the best interest of the company that invested in you is one of your biggest customers, et cetera. And does that mean you're not devoting resources to something else when perhaps you should be? It also raises the question of whether there might be misaligned values. So, yeah, the deal is being done at, let's just say 7 billion valuation. But if that was with somebody else, might have been a 4 billion deal. You're also creating customers for you who are beholden by those contracts. And then that, like, essentially creates regulatory risk as well. But regulators may come along and go, actually, we don't like that. We're not sure whether that's the best deal for the consumer. And so all these risks are emerging that perhaps we didn't have before. But the biggest one probably of all is that these circular deals can create a false impression of demand. And you may think that these companies are generating massive revenues, but if it's all just moving around and sloshing around, then if something falls out of bed, then there could be wider implications and that could become systemic.

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[John Stevick]

The other thing I thought was interesting this week is that although Cosby's fallen out of bed, the NASDAQ took a bit of a bump, but not a big one. It so far seems to be restricted largely to the AI and the tech sector and actually plenty of other stocks are doing fine. The equal weighted S and P is doing fine. That's the S and P that's not wholly invested in the tech sector. Also, the FTSE 100 is almost back at a record high, the laggard of the global stock markets. But is this issue of how much does this spread? Or could it spread beyond the tech sector? Who else is involved in lending to these companies? And if something did break down there sort of where are the contagion vectors?

[Neil Callanan]

The demand means that the AI industry has had to go to pretty much every corner of the credit market and hand out the bull and kind of say give us a few quid to fund what we need going forward. And so you're seeing everything from direct lending, which is private credit, usually for infrastructure. So like just to build a data center, you're seeing investment grade. You're also seeing these neo clouds like Core Weave, who I mentioned, who are sub investment grade. Sometimes not all of them, but some of them are sub investment grade. So that's the high yield market, the junk bonds that people might know they're in the structured credit markets. These are basically taking bond payments that are due and slicing them up by risk and selling them off to people.

[John Stevick]

Yeah, that reminds me, didn't something like that happen in the mortgage market? What was it 20 years ago?

[Neil Callanan]

We haven't got to kind of of the CDO level or CDO squared level. Where I would be concerned around that. Lending in particular is around what in real estate is called speculative lending, which means something else to many people but in real estate, it's basically building the stuff before you have a tenant.

[John Stevick]

Yes.

[Neil Callanan]

And if you can get finance from that, from a bank or from a private credit lender, that says something about bubble territory, because they are taking a complete risk that you are building this thing over the course of five years and you will find somebody to occupy. And if not, or if the industry moves on and technology moves on, you can end up with a very expensive elephant at the end, which may not have much residual value for people.

[John Stevick]

Yeah. If you build it, they will come. It only works in the field of dreams, doesn't it?

[Neil Callanan]

I mean, there can be a first mover thing where you can get away with it, but if you're spending 5 billion quid, it's building a data center. I certainly would want to be more certain of that. But we are beginning to see elements of that. And we're also beginning to see terms being pushed within those deals for lending that maybe are too generous to the hyperscalers. That is the point of view of the credit markets. You're starting to hear things like after a certain amount of time, if the project is delayed, then the hyperscaler come back up. Now, if you've invested five years and spent, as I say, $5 billion in building a data center and it gets a bit delayed because let's just say something got stuck in the streets of Hormuz at the moment, that's a very big risk. Again, that's part of what's happening with the credit markets and the pullback. They're reconsidering some of the levels of risk that they're accepting at the moment.

[John Stevick]

From that point of view, this, arguably, as long as it's not already going too far, may be a good thing. As in maybe it gets everyone to rein end or horns a bit before it does go properly pear shaped.

[Neil Callanan]

Yeah. And I think it was always going to happen. And to be fair, like you look at something like the Cosby and it's still up. Many of the companies in it are still up over 100% year to date. In some cases, AI adjacent companies are up 300% for the year. So there was a natural moment for a pause anyway. And while we are seeing in terms of the Chinese evolution, is that that was always going to happen as well. And China's big advantage is it has cheap electricity, so the tokenization is cheaper. So if you're a company that's also been spending loads of money on AI and your staff, it turns out, are using it to convert Excel files into PDFs rather than actually using a much cheaper technology for that, you're going to be scouting around for cheaper prices. And so, you know, China and the Chinese LLMs become a natural kind of success story from that. And you know, that was all to be expected I think, within a certain reason. And it's just all happened very quickly and all at once as it does these days in markets. And there's a bit of panic in certain areas, particularly when it comes to retail money. You and I have spent years writing about retail money being hot money and how people can panic. And to be fair, if I had leveraged several times, I would be looking at that and going oh my God. So it's understandable in a way, but if people are sensible about how they invest, there's still major opportunities there.

[John Stevick]

Yeah, I mean my heart goes out to the various rookie retail investors in South Korea who are now looking at some really nasty losses. I'm hoping that they were all young enough to bounce back from it. Thanks very much for this, Neil. It's really helpful. The one other thing I would ask you about is on the the debt side. So we've flood the debt market if you like. And we have also seen a bit of equity issuance. And I suppose the other thing I'm wondering about is how much can the market take whenever we've had decades of de equitization. So companies buying back all their shares or getting bought off the market. I know we're going to get quite unusually net equity issuance quite possibly this year. What does that say to you about what might happen regarding the tightness of my overall as in just not going to be enough to go around for

[Neil Callanan]

all the hungry mouths I think investors will be discerning. I mean you can tell an equity story that people will follow. I mean just think within AI, how many of these companies we had heard of three years ago? Very few of any. And yeah, they may not have very much revenue, but people are willing to bet on a deal. But there's also a thing of like it can go wrong quite quickly and SpaceX is probably a good example of that. Not necessarily went wrong, but there was so much hype and now it's obviously down. Since its IPO price, which was ambitious in the first place, I looked recently and the short interest on the stock was at near 40%. People are being very bearish on the future for it and that's probably the big question for investors at the moment. SpaceX being partially an AI story with data centers in space et cetera is has that and what happened to that stock closed the IPO window for a while in that sense. Then the focus would shift back to the equity markets. Sorry, to the credit markets and the credit markets sculptor I think it was put an investor letter out recently and they talked about how credit capacity is needed at its greatest extent just as people are pulling back. And that's something you have to be a bit fearful of, I think. Now often we have taught these things and two weeks later the market has said, oh, oversold and it's popped right back up and often exceeding the previous highs, obviously. But at the moment it's definitely a moment. It's just the length that that moment takes.

[John Stevick]

Great. Well, look, thanks a lot Neil. I think that was really helpful. I hope the main point here was to try and explain to people what's going on and I think you've done that excellently. And obviously the market can remain excitable for longer than anyone can remain solvent, especially if you're invested in a leveraged etf. So just be careful out there. Thanks again Neil.

[Neil Callanan]

Thank you.

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[John Stevick]

Thanks for listening. This week's Merton Talks Money Markets wrap if you like our show, rate, review and subscribe wherever you listen to podcasts and also be sure to follow me on x or Twitter at jonstepic. This episode was produced by Summer Saadi and Moses Andam. Questions and comments on the show are always welcome. Our show email is merrinmoneyloomburg.net Special thanks to Neil Callan.

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