# The Most Concerning AI Bubble Signals — Transcript (2026-10-23)

https://aidailybrief.ai/e/2026-10-23 · Listen: https://pod.link/1680633614

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[00:00:00] 

as the Anthropic IPO inches closer, discussions of an AI bubble are also getting a lot louder

the concerns range from GPUs sitting in Amazon warehouses unused to the quality of Neo Cloud debt

to the concentration of enterprise AI revenue. in this episode, we're going to go through all of those concerns, talking about which are in fact most concerning

And for those that aren't, what would make them more concerning in the future?



The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI

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Welcome back to the We're doing something we haven't done for a while, which is an AI bubble episode



Now, recently [00:01:00] the calls have been getting louder that the AI bubble has reached the end of the road

On Wednesday, Americans for Financial Reform produced a report warning that the bubble is, in their words, primed to pop. Senior policy analyst Maya Jenkins warned, " If nothing changes, working people will pay a high price for an AI crash. Policymakers should betaking urgent action to reduce the risks."

The bubble discourse has, of course, evolved quite a bit 

since its dominant place in the narrative last year

And there have been many things that people have been pointing to as warning signs over the past month. What we're gonna talk about today is which of these signs matter most

what the reasons for optimism or at least reduced fear are, and what things in each of those cases If we saw them happen

would make me more concerned

First, 

though, a bit of background. We're coming up on a three-week downtrend for tech stocks, with the Nasdaq losing three percent on Thursday following a relatively flat week. Some blamed Meta's Wednesday night earnings call, which made it clear that the next leg of their AI build-out would be partially funded by equity dilution This sell-off, though, has been happening for [00:02:00] weeks.

In their latest trading flow report, Goldman Sachs reported that hedge funds sold tech stocks at their most rapid pace in at least a decade last week

cha-- we also got an interesting change in behavior during the Thursday session. For the past few months, treasury bond rates have been surging, dragging up interest rates on commercial bonds and making data center financing more expensive

On Thursday, the ultra-long 30-year US Treasury bond dropped to a one-month low of 5.38%. Now this is early and none of the shorter dated bonds have seen falling rates so far. But this is indicative of a classic flight to safety reaction in the markets

in other words, more money flowing out of risky assets like the AI trade 

and into these safe havens of treasuries, 

which could spell more trouble ahead

Certainly the past few seen quite a bit of bearish analysis. One big example was Gartner, who latched onto stumbles in the NeoCloud sector

To claim that 80% of Neo clouds will go bankrupt by the end of 2030 Their report argued that three point five trillion in AI infrastructure spending would be subject to an impairment by [00:03:00] then

Due to a lack of demand Gartner's chief forecaster, John Lovelock, told CNBC on Monday, " At the moment, we have more compute capacity than we have demand, and we have a lot of the tokens and processing power being given away in freemium solutions. 

everyone in the AI race is running for a last man standing position.

Pretty much every market that Gartner is tracking in our AI race is likely to collapse down to a duopoly

To put some numbers around this, Gartner estimated that through 2030, the owners of these data centers would need to generate eight point five trillion in revenue To cover what they have announced around capital spending, financing costs, and a return on invested capital

On the other side of the equation, they argued, though

They believe that total enterprise andconsumer AI revenue is forecasted to not reach more than three point six trillion

quite a big gap if Gartner are right

That, meanwhile, kicked off a frenetic week-long news cycle around AI bubble fears. Citadel CEO Ken Griffin was one of many offering his opinion. At a Wall Street conference on Tuesday, he proclaimed that we are, quote, "Almost certainly in the middle of a bubble."

His [00:04:00] argument hinged on uncertain ROI causing a rethink on AI spending

Griffin commented, " Corporate America has been very uneven in its ability to extract value from its AI models. I think all of corporate America is looking at their bills from Anthropic and OpenAI and going, ' Okay, we're going to need to think about how we're sure we're getting productivity out of this.'"

Which Which is not to say that bubble calls have been consensus. On the other side of the argument, leaders 

from 

private equity firm Blackstone were out in force this week. Now the grain of salt here is, of course, that Blackstone has massive equity and debt positions in the NeoCloud sector, including extremely early involvement in CoreWeave and Firmus But last week, veteran executive Jas Kaira said that he isn't concerned about data center debt. Because hyperscalers are the tenants, Kaira claimed that this debt is ultimately backed 

By the most creditworthy companies in the world." His phrase

In a Bloomberg interview on Thursday Blackstone President Jon Gray spoke directly to Ken Griffin's bubble comments. Gray said, " When you think about a bubble, you think about building capacity and then hoping the demand comes. With AI, you're building capacity and you're [00:05:00] hoping you can keep up with demand."

Now, the thing to be skeptical here 

is that every talking head 

you see 

analyzing markets has a dog in the fight. 

I mentioned that Blackstone has positions in companies like CoreWeave and Firmus

But on the flip side, Ken Griffin profits most when there's volatility in the market



but there is a through line to this discourse

That as you'll see, I think is pretty much the only thing ultimately that will matter, which is the question of demand In many ways

Everything else is just a proxy fight

for the big question of how much AI demand is there going to be

and whether the value of that demand Is ultimately higher than the amount being spent on the infrastructure

Now now as we dig deeper into some of the big events that have shaped markets over the past couple of weeks and try to sort through the signals that matter from those that don't, I think it is worth being somewhat precise about our terms

When we use big apocalyptic terms like AI bubble, we lose nuance

and people who are talking about a bear market in stocks of the kind that takes stock markets down 20 or 30% are talking about something quite different than a generational bubble burst Like the dot-com crash, which [00:06:00] saw over 75% wiped off the Nasdaq across two years

Stock market crashes, in other words, are not the same as a credit or financial crisis

You can have one without the other. And of the two, a stock market crash is far less damaging

While absolutely painful, sometimes extremely so for those invested in the markets, and especially those who rely on their investments in markets like those living off fixed income retirement accounts 

if there's not a systemic problem for banks in the broader financial system, markets can recover naturally. A credit crisis, on the other hand, where mass defaults and contagion create impairments throughout the economy, is quite a different problem and one that can require central bank intervention

Now, if there's one segment of the AI trade that's been the locus of concern this month, it's the Neo clouds. We had the Firmus IPO in Australia getting canceled after investment banks 

couldn't find enough buyers at their desired price

Then a portion of CoreWeave debt traded down to distressed levels, implying a reasonable chance of default

Microsoft then pulled out of a planned data center in the UK 

because of power delays, leaving NScale [00:07:00] high and dry

And more recently, we're starting to see the big players in AI ride to the rescue. Anthropic is rumored to be in talks for a new forty-five billion dollar contract with Enscale. Goldman Sachs has upgraded CoreWeave stock to a buy, saying that some concerns over their debt are overblown and the stock has become oversold

And NVIDIA is rumored to be in talks to invest hundreds of millions into Firmus to help finance them after that failed IPO

It would certainly be going too far to say that the Neocloud jitters are overblown

It is absolutely an area of the market to watch, and investors are keeping a very close eye on it

But it's also important to keep the numbers we're talking about in perspective. Endscale is targeting a thirty billion dollar IPO 



in an industry where the key firms are worth around 10 trillion as a collective, a $30 billion company is a relative minnow

from strictly an economic perspective, it's likely the entire NeoCloud sector could go to zero without it having much of an effect

Other than, of course, the narrative effect, which would be gigantic. And that's why the big players are coming together to backstop the small guys. [00:08:00] According to the information, NVIDIA has already provided a hundred and seventy billion in support for the NeoClouds through credit guarantees and data center rental backstops.

The frontier labs and hyperscalers have also shown they're willing to put multi-billion dollar contracts in the headlines if anyone gets too shaky

The entire industry has a huge vested interest in making sure these companies survive and their data centers get built

the so so what then would be the most worrying concerns to watch for?

If a Neocloud gets into trouble and nobody rides to the rescue 

that would be a more concerning signal 



if distress started to spread from CoreWeave's own bonds 

to project debt for data centers leased to Meta, Microsoft, or Google, that might suggest that the markets doubt the tenant, not just the Neocloud Finally, if a hyperscaler or lab walks away from capacity because it doesn't need it

That would be huge. Remember, Microsoft's UK exit was blamed very specifically on power delays. A cancellation blamed on demand would be a totally different story

One story that's getting a ton of attention from certain critics this week is that Amazon has a huge pile [00:09:00] of GPUs gathering dust in a warehouse. On Tuesday, Business Insider wrote, " Under a new early rack receipt process, AWS expects to receive roughly five billion dollars in Nvidia's GB300 server racks at US facilities before final deployment.

the company projected roughly three billion more inGB300 racks each month 

for the foreseeable future

GB300s are the current top-of-the-range AI chips, the latest in the Blackwell series. Sources said that Amazon has room for more racks, but they don't have the power to turn them on. according to emails viewed by Business Insider, at least one team at AWS did not have a, quote, "clear forecasted path" to getting the new racks installed An Amazon spokesperson said it's routine to stage hardware ahead of construction and that being prepared to plug in GPUs once the power is available 

is best business practice.

The article also noted that Amazon is attempting to secure scarce GPUs ahead of the competition

The critics' take here this week has been the idea that NVIDIA is somehow forcing hyperscalers to take delivery of GPUs even if they don't have the power to use [00:10:00] them for fear of losing allocation to future chips. There have been direct claims that NVIDIA is channel stuffing or forcing sales to realize revenue more quickly

Basically that the ruthless and powerful Jensen Huang has all the hyperscalers under his thumb

As the logic among those critics goes, this means that some amount of NVIDIA's revenue is fake, demand for GPUs and therefore AI is softer than it appears, and the whole bubble is getting ready to fall apart

I have a hard time coming to the same conclusion

There's no reason to doubt Business Insider's reporting. They're very well sourced at AWS, and this has clearly been a month-long investigative piece to find out how many GPUs are actually being installed. But the Occam's razor explanation here is not a lack of AI demand. It's that there's a lack of powered up data centers

Amazon, even if Jensen was a ruthless businessman, would not be ordering tens of billions of GPUs if the long-term plan is just to warehouse them indefinitely. more-- It would make much more sense that Amazon is genuinely concerned about future access to chips Currently, GPUs are still being priced at a [00:11:00] gigantic premium, with old hardware selling above its original price.

Meanwhile, old hardware is still in active use

Reducing the harm and storing GPUs for a few months. Frankly, among a lot of things that we'll talk about today, this is one story that feels like gasping at straws, looking for any possible sign that the AI infrastructure build-out is falling apart

It's leaning a bit too hard on the comparison to Dark Fiber during the dotcom era But that was an issue of too little demand for already installed infrastructure. This is too little infrastructure to service demand

There are plenty of implications and issues with the challenges of getting data centers built and power connected. but those issues don't have anything to say ultimately about the demand for GPUs or AI in general

Again, just going by the simplest available explanation, Occam's razor. If AWS has to warehouse GPUs, it seems more likely to be a positive sign that demand is sky high than a nefarious plot to boost NVIDIA earnings And frankly, even if that is the case, it just demonstrates that NVIDIA still has all the pricing power in the [00:12:00] world

Quietly bubbling away in the back of everyone's mind, though, is the question of where all the data center debt is sitting This gets back to that idea of the difference between a stock market crash 

and a more systemic issue

especially after the experience that people lived through in 2008. Every time there's any sort of market wobbles, the natural question is to ask

if and how contagion can flow. In this case, if the AI bubble bursts, is it going to blow up the pension system or major insurers like we saw during the GFC?

That is a notoriously difficult question to answer definitively And this is an area where we should absolutely tread with humility 

What we know for sure is that a significant amount of data center debt has been collateralized and sold to insurers and pension funds The Information reports that a collection of giant insurance firms bought more than seven hundred and forty million dollars worth of CoreWeave debt the last time they sold bonds.

They listed American General Life Insurance, Fidelity & and Guarantee Life, of Denver, all of which have portfolios managed by Blackstone

In the abstract, that seems like a big number. But realistically, seven hundred and forty [00:13:00] million dollars spread across these large portfolios is a rounding error

It is still meaningful that they're carrying data center debt, and it would leave a hole if that debt defaults. But it certainly so far doesn't look like the potential of a mass impairment we saw following the GFC

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Another pocket of risk to be aware of is the growing pairing of insurance firms with private equity

canonical, the [00:16:00] canonical example is Apollo Capital, which merged with an insurance firm called Athene in 2022. This is a classic financing strategy pioneered by Warren Buffett. The insurance company gets favorable tax treatment, and the investment firm gets a steady flow of capital

This is a complex corner of finance that is certainly beyond the scope of this show

But one important thing to understand is that these aren't major insurers like State Farm providing auto and home insurance.

Instead, they're offshore insurers that mostly sell life insurance and annuities. It's a real risk, and they could definitely become impaired during an AI credit default, but they're mostly a risk for the wealthy people who invest in annuities

Finally, there's the pension funds, which definitely have exposure to the AI sector. How could they not? Their job is to invest in stocks and bonds, and for the past four years, the bulk of the returns have come from AI The Wall Street Journal reports that AI drove $138 billion in gains across 13 public pension funds since 2022

Last week, a report from Americans for Financial Reform stated, " 

data 

center debt is being repackaged and sold to pension and retirement funds, university endowments, and [00:17:00] other institutional investors in a manner eerily reminiscent of the subprime bubble. e- private equity firms have purchased life insurers and loaded them up with risky debt, exposing policyholders and the public to losses and raising the threat of financial contagion."

That report was largely interested in arguing against an AI bailout

which many are certain the Trump administration will indulge in at the earliest opportunity

But understanding not just how it is similar to the subprime bubble, but how it is different is essential here

Everyone remembers the slices of mortgages chopped up and sold to pension funds as CLOs during subprime, depicted as a Jenga stack in The Big Short dis- there is less discussion about why that was actually a problem. It wasn't just about chopping up the debt and combining it into a CLO.

w- the problem was that those CLOs were rated investment grade debt. They were treated as being just as safe as treasury bonds

This time around, data center debt is being treated as corporate bonds, sometimes investment grade, sometimes not, and definitely nowhere near the same as treasury bonds. They're sitting on pension and insurer balance sheets just the same as thousands of [00:18:00] other bonds. During subprime, chopping up the debt was explicitly and intentionally used to obfuscate how risky it was.

This time around, no one is pretending that data center debt is as safe as houses

just, but again, I wanna not just focus on why things are maybe worth a little pause and the stress right now, but what could in the future be more cause for concern? One cause for concern would be that if we saw disclosed exposure jump by orders of magnitude or concentrating in a handful of PE-owned insurers 740 million spread across big portfolios is thin.

But if that jumps to tens of billions sitting in two or three insurers, that could be a different story Another concern would be if data center debt started to get repackaged into securities that were rated higher than the loans underneath them

And again, the point here is not that these things are impossible

It's that they're not the things that are happening yet

of, now now going back to the idea of a bailout

Another big topic of discussion of late is the idea that the large AI players are looking to make themselves too big to fail. This discussion came back with a vengeance after Anthropic and then Elon Musk said [00:19:00] that they would gift equity to the public through two very different mechanisms

Now, there is a whole very important policy discussion about whether this is actually appropriate in a democratic society

Whether it's a good way to redistribute gains or possibly a glaring sign that billionaires and mega cap companies need to be paying more in taxes

But that's not the particular can of worms that we're opening today

There is clearly a solid argument that giving the public a direct stake 

in the companies risks making them too big to fail. And to be clear, when we say too big to fail, we're using a specific term from the last 15 years that refers to institutions 

that the government feels obligated tocome in and protect regardless of what would otherwise happen to them in the free markets

This is an area where I am perhaps more cynical than some of you, and forgive me if so Realistically, I think if yourconcern is that we're going to get another group of too-big-to-fail companies, in my opinion, that ship has already sailed whether or not they give shares to the public.

in the r- at this stage in the history of the relationship between the US government and markets

It seems massively unlikely to me that the [00:20:00] government would just stand around while a trillion-dollar company blew a giant hole in their economy The government didn't let it happen with GM in 2008, and certainly the norms of how the government engages with markets have gotten a lot weirder since then

On the other hand, as for the argument that these companies are engineering a bailout ahead of a market crash

That's something I just don't buy Regardless of what anyone wants to say about Anthropic, it's pretty clear at this point that they have a genuine belief in their mission. and the simplest explanation once again, is that they want to establish a giant public benefit fund to further that mission

As for Elon Musk



you have the convergence of the fact That it would be entirely consistent if he did believe that this sort of giving is the best way to impact public benefit

But also there's the fact that more cynically, he might be reading the room that some sort of redistribution is going to happen, and he thinks if he gets out ahead of it, he might be able to control it rather than be subject to it



and there's also the more armchair psychologist assessment that the man loves being loved and there's no easier way to being loved than to give $11 billion to the American public 

This is one that at the moment I don't think is worth spending a ton of additional time on. but for the sake of completeness in terms [00:21:00] of what to watch for

If you start to see AI companies begin to ask for explicit federal guarantees Or loan programs or financing backstops before there's a crisis

that could cause, let's say, a different conversation here

I think of all the warning signs that people are bringing up, the one that is most interesting 

and deserving of deep consideration is the question of revenue quality

Although even within this

there's a bunch of different versions of it that I think have very different dynamics

On the one hand, you have Nvidia, 

who reported that just two customers made up thirty nine percent of their Q2 revenue

On the other is The Wall Street Journal's recent leak of Anthropic's IPO prospectus, 

which noted that a fifth of Anthropic's revenue in the first half came from their top two customers da-- relatedly, Ramp data hasshown that the top one percent of businesses account for eighty percent of spending volume for OpenAI and Anthropic through Ramp's platform

So how are these different? 

Well, 

NVIDIA has ahighly concentrated customer base because there's only a handful of companies in the world that are building multi-billion dollar data centers

And some of this might even apply to the Anthropic story. A large chunk [00:22:00] of their revenue is likely coming from the hyperscalers because that relationship is that of a wholesaler and a distributor rather than a vendor and customer

revenue quality becomes an issue when there's a big risk that one of your largest customers could pull the plug



for hyperscalers reselling Claude tokens, that seems very unlikely to happen in the short term



a much bigger concern, I think, is this narrow distribution of power users making up the bulk of enterprise AI use

As always, we need to contextualize ramp data recognizing that they service a 

very, 

very slim part of the market, extremely forward-looking companies, extremely tech-advanced companies many of them from the tech sector And yet it's still worth noting that Ramp found that 80% of the top 1% of AI customers are VC-backed startups

Some amount of that volume is wrapping Frontier tokens in a service and providing a VC-subsidized discount, which is of course the business model for some of the agent startups. And we can also presume that a lot of the token volume is for internal use, which is also funded by VC dollars Where this becomes a problem is if VC money dries up and these startups hit the end of their [00:23:00] runway

At the moment, AI venture is still a raging bull market, but that can always change

The bigger risk, and really the big question here

is how much of AI spending is permanently going to be subject to power laws without broadening out?

in other words, is this incredible concentration 

likely to hold as the demand profile for the entire AI industry, 

even as buyers mature? Or is it simply an indicator of the difference between companies at different stages in their adoption cycle?

If the startup spending around $9,000 per employee per month are the top of the chart now At some point in a decade, are all enterprises spending $9,000 per employee per month? And if not, how close to those sort of numbers are they going to get?

Ramp has seen businesses across all cohorts triple their spend per employee since the summer

Businesses not in the 1% but in the 10% went from around spending $200 per employee to around $800 per employee, growing faster than the median

That suggests an adoption curve that is expanding out across the economy, but there's certainly no guarantee there

[00:24:00] Another curveball 

which gets into our next and final line of discussion is that this particular risk gets far more tangible after

the major labs go public.

At the moment, this risk is based on data from Ramp, the often misunderstood Silicon Data Token Index, and various other unofficial sources that have a tiny sliver of the full picture. Once Anthropic and OpenAI go public, 

they'll have nowhere to hide. Their fully audited financials will be reported quarterly, and their CEOs will be grilled by equity researchers on earnings calls.

If they're not growing and improving their revenue quality, everyone is going to know about it

And of course, clearly the rapidly approaching Anthropic IPO is a big part of the reason that the AI bubble is back in the discourse

Frothy 

markets often top on a catalyst that breaks the suspension of disbelief. And for many, the Anthropic IPO seems likely to fit that bill

What we've learned so far about Anthropic's financials 

have compared to at least what many people were thinking looked less than stellar

The headline that Anthropic made an $80 billion loss in the first half went viral on social media, even though this was an accounting loss and their true [00:25:00] cash loss was $8.7 billion

Still, we're seeing valuations soften as Anthropic enters the final stretch

OpenAI's fundraising is expected to close soon, and the information reports that the valuation will come in at one point two five trillion. at-- earlier reporting had it at one point four trillion Now, I don't know if you can consider

The difference in an early leaked reported number

And the actual factual final number

as being clearly a valuation downgrade as opposed to just misreporting. 

but that's certainly how investors are looking at it

While some Anthropic investors 

were originally pushing for a $2 trillion valuation in the press, more recently there's been reporting that another group is pushing for 1.5 trillion

Meanwhile, the rest of the IPO market is completely frozen, with less than six hundred million raised so far this month.

West Riggs, the head of equity capital markets at Truist Financial said, " People are truly paralyzed. The market has to sort itself out."

The US Capital Markets transaction leader at Deloitte & Touche said, " There is a stalemate on valuation and rationalizing that gap is what needs to happen before the broader market can move forward."

Essentially, companies looking to IPO are [00:26:00] asking for more than investment banks will give them

This could mean Neo clouds are unable to go public 

and consequently unable to access their next tranche of funding, leaving private equity holding the bag

But ultimately, 

as with any market or market psychology issue This one is only resolved by the next thing happening. 

Bloomberg,

in Bloomberg Opinion this week, Chris Hughes wrote about the long list of problems with the AI trade, but concluded, " Some of the questions currently weighing on the market will be resolved over time.

But if Anthropic could just get on with its IPO, that would give everyone one less thing to worry about

And I think that there is real risk here. 

not for some sort of systemic contagion or anything like that But from the standpoint of confidence in the AI trade, if Anthropic prices their IPO at one point five trillion after investors splashed around the two trillion dollar number for months

That's not great, 

but ultimately probably not all that concerning If on the other hand, Anthropic prices at one point five trillion and we still see a weak reception in the market

That will confirm a lot of people's worst fears about the state of the AI trade

Point of today's episode

is neither to definitively try [00:27:00] to deny any causes for market concern

nor to surprise you and come out 

saying that some AI bubble burst is inevitable what I'm, instead what I've tried to do is look at each of the different subcomponents of the narrative in turn and talk about where I think they are today and what would make me more concerned going forward

One thing One thing that's undeniable is that the narrative that the AI bubble is about to burst has been a recurring feature of this market cycle, going back all the way to the beginning 

of the generative AI era

For whatever reason, it seems to come up around this time of year. In 2024, we saw massive concern about AI scaling hitting a wall after reports that multiple labs were seeing a slowdown in model improvement

But then just shortly after that, we got the first reasoning models

and farther after that

Advances in chips with more memory that allowed multi-trillion parameter models to be trained in then of course last year, there was a concern that enterprises weren't seeing returns from AI and wouldn't continue paying This of course embodied in the bane of my existence, the MIT report about the 95% of generative AI pilots failing

spoiler alert, enterprise spend didn't dry up. Instead, it boomed and is still growing at around 50% a [00:28:00] quarter

previous,

now previous bubble calls being wrong does not mean that all bubble calls in the future will be wrong as well

we'd all, it just means we'd all be better served carrying around bags of salt at this point 

to take with all of these big bombastic headlines

With the Anthropic IPO coming up, we will get a much more definitive answer soon

whatever, the impacts of whatever that shows

remain tantalizingly and frustratingly in the future

And for now, all we can do is speculate and debate. for, Hopefully you've got a bit more fodder for that now And that's gonna do it for today's AI Daily Brief. Appreciate you listening or watching as always, and until next time, peace. 

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