5 Reasons AI is a Bubble (And 5 It’s Not)

0:00Today on the AI Daily Brief, five reasons AI is a bubble and five it's not. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.

0:35engagements, etc., go to aidailybrief.ai. One of the things that I'm thinking about for next year are extensions to this core show. Nothing is changing about this core show, but there is so much more to explore out and around it that I'm exploring three different ways to expand the AIDB universe. The first is an enterprise edition that would basically take this show, repackage it, reorganize and restructure it as learning materials and discussion and strategic material for enterprise teams. The second is an operator's cut, which would be additional supplemental material that was a little bit more practical and focused, stuff that would help you apply AI more directly.

1:10And then the third, relevant for this particular episode, is an investor's edition, which would be a supplement more focused on big market themes. I would love to know if any of these interest you. So if you would be so kind, please go to aidailybrief.ai. There's a three question survey there, and I would be ever so appreciative if you would fill it out. Lastly today, we are talking about the big behemoth topic, is AI a bubble? And it got long and dominated the entire episode. So no headlines today. We'll be back with headlines tomorrow. And without any further ado, let's dive in. Welcome back to the AI Daily Brief.

1:42Today, we are once again exploring a theme that has been with us since the beginning and will be with us for a long time to come, I think. However, it has just gotten too loud, too unignorable. We have to dig in again because this is all anyone, at least in the mainstream media, is talking about right now. The question, of course, is AI bubble, and we are going to talk about this latest report from the Information and Oracle, which restarted this set of conversations, and look at a set of reasons why AI is or is not in a bubble right now. But just for a little bit of context, and to really reinforce the point that this has been with us since the beginning, ChatGPT came out at the very end of November of 2022.

2:19And already by February 7th, people like Josh Brown of Ritz-Holth Wealth Management were calling an AI bubble. It was loud enough that a few months later in September, Goldman Sachs had to come out and say that it wasn't a bubble. Despite the mega cap tech stocks rising by 60 % at that stage in 2023, their analysts were convinced that there was still plenty of room to run. But then by December, we get articles like this one from Crunchbase, the AI bubble will burst, here's how to limit your exposure. This article was more focused on startups with random AI SaaS companies being valued at the same multiples as OpenAI or Anthropic.

2:52Now, of course, we know what has happened since then, at least from a big market perspective. With the small exception of the tariff tantrum earlier this year, it has been just up and to the right. And in 2025 in particular, the sheer size of everything surrounding AI has just gotten absolutely enormous. This has led over the last couple of months to a renewed discussion of the bubble conversation. We had a big burst in this topic in August as we got the combined factors of initial disappointment with GPT-5 and the renewed arguments that we were hitting a wall, widely over-reported comments about Sam Altman saying there was a bubble, and of course that now infamous MIT study, which I put in air quotes, that argued that 95 % of AI pilots were failing and which whipped around Wall Street with incredible frenetic energy.

3:36Still, another interesting thing happened in early September when we got news of the$300 billion Oracle OpenAI deal that sent Oracle stock soaring by 35 % in the day. All of a sudden, people were seeing the financial consequences of missing out on this leg of the AI boom, and bubble talk quickly fell off the menu. In fact, Deutsche Bank published a report in late September that declared that the first bubble to burst was in fact discussion of the AI bubble. They found that the peak of the narrative was back on August 21st, with the number of web searches for AI bubble falling by 85 % over the following month.

4:09One of the things they pointed out is that, quote, identifying a bubble is almost impossible, not least because no one agrees exactly what it is. Typically, it's something like when asset prices rise significantly above intrinsic values, but they also don't agree what the correct intrinsic values are even after it bursts. What's more, they point out, concern about a bubble may act as a pressure valve, lowering valuations and encouraging a whole new round of bargain hunting. And yet, despite this report coming out on September 30th, just a little more than a week old, it already feels out of date.

4:38Searches for AI Bubble have tripled over the past two weeks as a wave of new news reignited the narrative. On Monday, we got news of OpenAI's deal with AMD, which was the subject of yesterday's show, which based on its non-traditional structure of OpenAI potentially owning 10 % of AMD if it hits milestones, felt very bubbly to some. Then on Tuesday, the information published an expose on Oracle's financials. The piece was titled, Internal Oracle Data Show Financial Challenge of Renting Out NVIDIA Chips. They write, Internal documents show the fast-growing cloud business has had razor-thin gross profit margins in the past year or so, lower than what many equity analysts have estimated.

5:16This could raise questions about whether the AI cloud expansion undertaken by Oracle and its rivals will affect profitability and sustain investors' expectations. So the report states that in the three months that ended in August, Oracle generated around$900 million from renting out NVIDIA-powered AI compute. Gross profit was$125 million, or 14%. which, as the information points out, is lower than even many non-tech retail businesses. For some comparison, Walmart's gross margin was 25 % in the last fiscal year. And then on the other end of the spectrum, closer to Oracle's business, Microsoft's Azure division currently operates at a 69 % gross margin.

5:51Oracle stock actually dove 6.9 % on the news, but recovered much of the drawdown by the end of the day. The narrative was absolute catnip for headline writers, with FX leaders going with, Oracle stock dives on weak cloud profits. AI hype meets tough reality. Still, some thought something felt off about the whole thing. Amit is investing posted on Twitter, This doesn't seem like a demand issue, aka Oracle not finding customers for renting their GPUs, but rather seems like a margin issue. It seems like customers are asking for a really good deal, or they would just leave to an Iran, Nebius, or Corrive, and as a result, Oracle's margins on this business have not been as strong.

6:28Some people question the financial acumen in the article. Tay Kim, a veteran financial reporter and author of the NVIDIA Way, posted, Today I learned AI infrastructure biz has lower gross margins than software, and margins are bad when GPUs are getting installed and not yet generating customer revenue. This is basically an argument that the information and then consequently Wall Street investors were turning a molehill into a mountain by not understanding the natural life cycle of this particular type of product. Jensen Huang commented on something similar in an interview with Jim Cramer on Tuesday, stating, What Oracle does with our systems is not easy.

6:59We're talking about giant supercomputers. When you first ramp up a new technology, there's every possibility that you might not make money in the beginning, but over the life of the systems, Oracle is going to be wonderfully profitable. In fact, differences of opinion on the depreciation schedule for AI chips is one of the big factors going into bubble analysis. Most firms are depreciating their chips over five or six years before they need replacement, yet some of the loudest bears, like Jim Chanos, argue the depreciation schedule is much shorter, with data centers needing to upgrade to the latest and greatest from NVIDIA every two or three years to remain competitive.

7:31JT of LaCoya Capital picked up on an interesting comment from the information article on this front. The article stated,

7:51JT points out,

7:57useful life of NVIDIA Silicon I've seen anywhere, maybe ever. They're still printing it on Ampere. In other words, while the margin story shows how difficult it is to make money initially off of the state of the art, it is real lived evidence that chips from five years ago are still profitable, which has huge implications for how we think about the longevity of the value of this infrastructure that's being installed. A huge argument from those who think we are in a bubble is that the infrastructure is going to go out of date even faster than people think, and that unlike railroad track from centuries past or fiber optic cable from decades past, these chips are gonna be useless in two or three years.

8:32And this suggests that at least that life cycle might be a little bit longer than we thought. Now, the other big piece of news circulating on Tuesday that supercharged this bubble conversation once again was that XAI had raised$20 billion in an ongoing funding round. The fundraising is apparently a mixture of debt and equity and will be used to fund the expansion of XAI's Colossus II data center that's currently under construction in Memphis. The part that caught everyone's attention was that NVIDIA was investing$2 billion in the equity side of the round, a move that Bloomberg wrote was a, quote, strategy by the chipmaker that helps accelerate its customers' AI investments.

9:06Okay, so this brings us to the main thrust of this piece. Is this a bubble or not? Let's talk about five reasons this is a bubble and five reasons it's not. I think, by the way, I'm probably going to end up at six or seven reasons in each case. And to be clear, as you can probably imagine, I am very much in the boom, not bubble camp, but I am going to represent the reasons it is a bubble with as little snark as is manageable for me. By far, and without a shadow of a doubt, the number one reason that some people think this is a bubble is the notion of circular investment, with the XAI deal being the latest in a string of examples.

9:39You might have seen some version of this chart going around showing how interconnected all of these companies are, or maybe this one which shows the actual dollar amounts going between different companies. To take just example of that new NVIDIA XAI deal, NVIDIA will invest $2 billion into XAI, which will show up three months later as revenue on NVIDIA's balance sheet after XAI uses it to buy chips. OpenAI's deals with AMD and Oracle work similarly, with investment dollars and revenue getting passed between firms to boost everyone's bottom line. This is bringing up what are for some uncomfortable questions of vendor financing, and some think it's amplifying and overstating demand in the entire sector.

10:14Stanfield Capital, for example, wrote, None of these circular AI deals would be happening if there were genuine cash demand for the chips at list price. It's obvious that the economics of this industry don't work unless the chips are hugely discounted, which means the chip makers are hugely overvalued. Alright, so circular investment, reason one that people think this is a bubble. Reason two is the risk that AI infrastructure will be overbuilt. Kip DeVere, the CEO of private equity group Aries Capital Management, told Bloomberg on Tuesday, if you look historically in areas like this over the past 20 or 30 years, typically when this much capital comes online, some of it at the end of the day has to be marginal.

10:50These trends tend to lead to overbuilds in certain places, so us being selective and measured in what we build is important. Now, at this stage, there are trillions of dollars worth of AI data center commitments over the next five years. And what's fascinating is that while this has financial professionals seeing ghosts of overbuilt telecom structure from the past, all of the hyperscalers and the big foundation labs continue to claim that their greatest risk remains to little compute rather than too much. JPMorgan reported this week that AI companies are now the largest segment of the investment-grade debt market, with$1.2 trillion in commercial bonds issued.

11:22They've reached 14 % of the market in total, overtaking U.S. banks for the first time. And although the numbers are getting big in absolute terms, the report was still positive, stating, debt tied to AI companies is growing fast, but it trades tight for good reasons. The report noted that AI companies tend to be cash-rich, not highly levered and highly regulated, which makes them very solid investment-grade bonds. But for those who think this is a bubble, that of course doesn't speak to the fate of the industry if AI demand fails to keep up with the supply of data. Last month, Bain and company forecast that$2 trillion of annual revenue would be required to fund AI Compute by 2030.

11:55Their analysis found that AI-related revenue would fall short by$800 billion. So that is bubble argument two, overbuilding. Bubble argument three is the echoes of dot-com. Many people feel like they've seen this movie before. It's important to note that most of the senior people currently on Wall Street had their seminal experience during the dot-com bubble, making and losing their first fortune in the space of a few years. To them, this bubble has lots of echoes, including overbuilt infrastructure and circular investment. During dot-com, millions of miles of fiber-optic cable was laid to power high-speed internet, but as much as 90 % of it lay dormant for years after the burst.

12:31Circular revenue was also a huge problem during dot-com, especially among the companies that were little more than a website and a ticker symbol. In addition to vendor financing of the build out. You also had the circularity of what little revenue there was going on in the web space, where most of the revenue was from banner ads, which were largely bought by other dot-com companies, essentially meaning that investment dollars float around the ecosystem, adding revenue to each company in turn and massively inflating financials. OpenAI chairman Brett Taylor recently said, I think there's a lot of parallels to the internet bubble.

12:58It is both true that AI will transform the economy, and I think it will, like the internet, create huge amounts of economic value in the future. I think we're also in a bubble and a lot of people will lose a lot of money. So bubble argument three echoes of dot com. Bubble argument four, stretched valuations. The Shiller price to earnings ratio, which is a standard metric to measure stock valuations, hit a high in September. The S &P 500 was valued at the highest level since, you guessed it, 2000. Now, most analysts are careful to note that there's no reason theoretically that richly valued stocks can't stretch even further.

13:30Russ Mold, an investment director at A.J. Bell, said the U.S. equity market looks expensive relative to its history pretty much any way you slice it. However, he added, valuation does not guarantee an imminent accident. Still, if you are looking for reasons a bubble might burst, incredibly high stock valuations is one of the core warning signs. On to argument five, part of the bubble logic is just the sheer size of what's happening, and the idea that this scale of activity simply isn't sustainable. On Monday, the Financial Times published an op-ed from Rockefeller International Chair Richie Sharma, entitled, America is now one big bet on AI.

14:03He claimed that AI investments have accounted for 40 % of US GDP growth and 80 % of the gains in US stocks so far this year. Sharma argued that AI is increasingly viewed as a magic fix for anything wrong with the economy. Backfiring tariffs, consumer debt defaults, and a deteriorating job market, AI productivity gains are the big bet to smooth everything over. Now, the view is more about the consequences of an AI bust rather than evidence of a bubble. The idea is that AI investment has become too big to fail, but is also wildly speculative. For Sharma and many other bubble concerned, it is of course nonsensical that producing tokens to the exclusion of anything else could be a sustainable premise for an economy the size of the US.

14:39Let's throw in one more argument for the bubble, which we might call speaking it into existence. Remember, in many ways, bubbles are about narratives, and they unwind when results fail to live up to expectations, when there is, in other words, a narrative fracture or a narrative disconnect. At the moment, expectations are sky high. AI is viewed as a technology that has the potential to change the world, a narrative that has been only applicable a few times in the past century. However, because the bubble is built on narratives, sometimes it only takes a few errant comments from leaders to make it burst.

15:08And those comments seem to be coming more frequently. Last week, while on a press tour of their Texas facility, Sam Altman said, Between the 10 years we've already been operating and the many decades ahead of us, there will be booms and busts. People will over-invest and lose money and under-invest and lose a lot of revenue. We'll make some dumb capital allocations. However, he assured the press, Over the arc that we have to plan over, we are confident that this technology will drive a new wave of unprecedented economic growth. Altman has made a string of comments like this over recent months, and seems far less disciplined, frankly, in his messaging than the veteran CEOs like Jensen Huang or Larry Ellison.

15:41At Monday's Dev Day, he acknowledged that stocks jumping when they were mentioned on stage was, quote, weird and something they're getting used to. Altman's bubble talk might not be enough to pop the bubble all on its own, but it is certainly contributing to market nerves at the moment. Small, nimble teams beat bloated consulting every time. Robots and Pencils partners with organizations on intelligent, cloud-native systems powered by AI. They cover human needs, design AI solutions, and cut through complexity to deliver meaningful impact without the layers of bureaucracy. As an AWS-certified partner, Robots and Pencils combines the reach of a large firm with the focus of a trusted partner.

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18:32All customized for you. Instead of shopping for hype, you get to deploy with confidence. Visit bsuper.ai and book your AI planning demo today. Okay, so those are five, actually six, arguments for why it's a bubble. Certainly, the ones that are at the very top of people's lists are the questions of circular investment, which is related to the concern of overbuilding, and more recently, the Shiller price-to-earnings ratio and stretch valuations is really starting to weigh on people's minds as well. But let's move over now into the top five reasons that bubble talk is overblown. The first is, of course, that revenues in this case are real.

19:07You might have seen some version of this chart circulating on X or wherever you hang out on social media, comparing AI revenues to the dot-com bubble. It shows a chart demonstrating that Cisco valuations completely detached from earnings growth starting in about 1998. By comparison, NVIDIA's stock price has been on an incredibly steep climb, but right alongside it has been an incredible streak of earnings growth. Roan Paul shared this chart and said, this is not a bubble. Cisco was a valuation story, price inflated while earnings lag, then the multiples deflated. Nvidia is an earnings story, price climbs alongside surging earnings.

19:41Luxalgo recently posted a 90s Time magazine cover that asked, is the boom over? They wrote, Reminder that the dot-com bubble didn't top for another 18 months after the September 1998 cover. And that was with companies like Pets.com doing$9 million in peak annual revenue. Nvidia did$46 billion in sales last quarter. It is different this time. The same is true in private markets. OpenAI's revenue growth forecasts have frequently been dismissed as a fantasy, but they've managed to outperform every year since the release of ChatShitBT. What's more, thanks to the AI coding boom, Anthropic has come into its own this year and is now growing even faster than OpenAI.

20:16Long-tail startups are seeing the same thing. Stripe's most recent report on startup revenue found that the top 100 AI companies were hitting a million in ARR in 11.5 months compared to 15 months for non-AI SaaS startups. Now, of course, these companies are not profitable yet. This is revenue growth, not profit growth. But still, revenue growth is significantly faster than previous startup booms. Keep in mind, OpenAI and Anthropics revenue is not based on advertising or strange structured deals. Close to$20 billion is now coming in from people to purchase a product for themselves or their employees that did not exist three years ago.

20:56Full stop, we have never seen anything like that. The second argument for why AI bubble talk is overblown is low leverage. We heard about that$1.2 trillion in commercial debt tied to AI infrastructure, and anytime you get a number with a T, it starts to sound scary, but that debt is backed by very solid companies concentrated in Meta and Oracle. At this stage, Google and Amazon seem to be funding their data center construction entirely off their own balance sheet, and Microsoft has a very conservative debt capital strategy. And so far as NVIDIA's circular investments go, a big part of the reason that they are offering vendor financing and equity for GPU swaps is that they have an absolute boatload of cash.

21:34They can't move the needle by reinvesting into the business, so they need to take bets on the AI ecosystem to set up the next leg of growth. In a recent appearance on TBPN, Doug O 'Loughlin, the president of SemiAnalysis, wrote, None of the hyperscalers are levered. Microsoft has net cash and has become more creditworthy than the U.S. government. And what's really crazy is that Microsoft has a 5 bps premium to the treasury. The real issue is how much liquidity the private credit market can handle. They're sitting on an ungodly amount of capital and they have to deploy it. The traditional wisdom is that bull markets don't die of old age.