AI Bubble Debate Intensifies as Industry Weighs Investment Reality Against Hype

If the AI bubble bursts, what will it mean for research?

After years of hype and ballooning investment, the boom in artificial intelligence technology is beginning to show signs of strain. Many financial analysts now agree that there is an 'AI bubble', and some speculate it could finally burst in the next few months. In economic terms, the rise of AI is unlike any other tech boom in history -- there is now 17 times more investment in AI than in Internet companies before the dot-com crash of the early 2000s. And, valued at around US$4.6 trillion, the AI company NVIDIA was worth more than the economies of every nation except the United States, China and Germany. But AI is not living up the promise of revolutionizing multiple sectors -- nearly 80% of companies using AI found it had had no significant impact on their earnings, according to a report from management consulting firm McKinsey, and concerns over the basic architecture of chatbots is leading scientists to say that AI has the potential to harm their research. These doubts over the technology's utility, and financial viability, is leading analysts and investors to speculate that a crash is coming. Even tech chief executives such as Sam Altman of ChatGPT's parent company OpenAI in San Francisco, California, have admitted that parts of the field are "kind of bubbly right now". So, if a crash is imminent, how will it affect AI research and the scientists and engineers who make it happen? Some analysts say that an AI-market collapse would be even more catastrophic than the dot-com crash -- a shock that wiped out more than $5 trillion in stock-market value and led to hundreds of thousands of job losses in the tech industry alone. Like those of other tech bubbles before it, the dot-com crash had a lasting impact on computer-science research, says John Turner, an economist and historian at Queen's University Belfast, UK. "But it wasn't all bad," he adds. "In 2000, a lot of highly skilled electronic engineers and computer scientists lost their jobs" and demand for computer-science graduates plummeted, he says. This led to a drop in the numbers of computer-science graduates -- but despite this, research output didn't falter, and the average number of computer-science publications continued to rise each year during and after the dot-com crash (see Dot-com crash aftermath'). Similarly, the roll-out of telecommunication technologies such as mobile phones and the Internet continued unabated. Brent Goldfarb, an economist at University of Maryland in College Park, says similar lay-offs in AI researchers and developers would happen were the AI bubble to burst. The biggest impact "would be on the hoard of start-ups jumping on the AI bandwagon, like the tenth AI notetaking app or AI scientist", he says. OpenAI, Google, NVIDIA and other major AI companies "will likely survive", he says. "The last thing they'll do is get rid of their scientific core; that's the path to the future." In fact, crashes can have a silver lining: they can take innovation into other sectors when leading scientists change jobs, Turner says. Take, for instance the British bicycle crash of 1896. "Motorcycles, motorcars, the Wright brothers; all can trace their origins to the bicycle bubble," he says. "The railway 'manias' of the nineteenth century left the legacy of railways for the benefit of people, much like the dot-com bubble gave society the Internet." Currently, the tech industry eclipses academia when it comes to AI, in terms of both investment and publication output. Some researchers have called this an "AI brain drain", which sidelines exploratory science in favour of commercial interest. "If I'm an AI researcher working at OpenAI, why would I go to a university when I earn ten times the salary?" Goldfarb says. Could industry lay-offs after an AI crash have the opposite effect, and push more researchers into academic jobs? Possibly, says Goldfarb, adding that "AI researchers coming back to academia would be good to train future generations". But he doubts whether enough AI researchers would be drawn into academia to make universities a dominant centre of AI research. Tech lay-offs in 2022 and 2023 were the worst since the dot-com bubble, but there is little indication it has affected academic AI research -- industry has gained most of the PhD graduates in AI research, and 90% of the largest AI models topping benchmark rankings were developed in industry (see 'AI brain drain'). David Kirsch, a historian of modern technology at the University of Maryland, says that even if they go into academia, the "talent liberated from an AI bust" would go on to create tools that are much more valuable for society than for the companies that created the AI models. The protein-folding software AlphaFold, for example, is "super useful" for solving problems in biology. "I could imagine researchers solving other historically challenging things that need to combine AI and deep human knowledge to generate meaningful innovation," he says. There are already signs that this is happening. Top AI researchers left OpenAI, Meta and Google this year to found Periodic Labs, a start-up in San Francisco that aims to use AI to accelerate scientific discoveries in physics and chemistry. And Meta chief executive Mark Zuckerberg's plans to push for AI 'superintelligence' has led the company's chief scientist Yann LeCun to say he intends to leave the company and launch his own start-up, developing "world models" -- neural networks that understand the physical properties of the real world and can plan actions rather than just react to prompts. Whatever happens to the AI bubble, the money and human resources invested into it will spread innovation into other sectors outside the tech industry, says Turner. "The question is: what is that 'something else' in AI?"

Is the AI bubble about to burst? What to watch for as the markets wobble

SOAS, University of London provides funding as a member of The Conversation UK. The global investment frenzy around AI has seen companies valued at trillions of dollars and eye-watering projections of how it will boost economic productivity. But in recent weeks the mood has begun to shift. Investors and CEOs are now openly questioning whether the enormous costs of building and running AI systems can really be justified by future revenues. Google's CEO, Sundar Pichai, has spoken of "irrationality" in AI's growth, while others have said some projects are proving to be more complex and expensive than expected. Meanwhile, global stock markets have declined, with tech shares taking a particular hit, and the value of cryptocurrencies has dipped as investors appear increasingly nervous. So how should we view the health of the AI sector? Well, bubbles in technology are not new. There have been great rises and great falls in the dot-com world, and surges in popularity for certain tech platforms (during COVID for example) which have then flattened out. Each of these technological shifts was real, but they became bubbles when excitement about their potential ran far ahead of companies' ability to turn popularity into lasting profits. The surge in AI enthusiasm has a similar feel to it. Today's systems are genuinely impressive, and it's easy to imagine them generating significant economic value. The bigger challenge comes with how much of that value companies can actually keep hold of. Investors are assuming rapid and widespread AI adoption along with high-margin revenue. Yet the business models needed to deliver that outcome are still uncertain and often very expensive to operate. This creates a familiar gap between what the technology could do in theory, and what firms can profitably deliver in practice. Previous booms show how quickly things wobble when those ideas don't work out as planned. AI may well reshape entire sectors, but if the dazzling potential doesn't translate quickly into steady, profitable demand, the excitement can slip away surprisingly fast. Fit to burst? Investment bubbles rarely deflate on their own. They are usually popped by outside forces, which often involve the US Federal Reserve (the US's central bank) making moves to slow the economy by raising interest rates or limiting the supply of money, or a wider economic downturn suddenly draining confidence. For much of the 20th century, these were the classic triggers that ended long stretches of rising markets. But financial markets today are larger, more complex, and less tightly tied to any single lever such as interest rates. The current AI boom has unfolded despite the US keeping rates at their highest level in decades, suggesting that external pressures alone may not be enough to halt it. Instead, this cycle is more likely to end from within. A disappointment at one of the big AI players - such as weaker than expected earnings at Nvidia or Intel - could puncture the sense that growth is guaranteed. Alternatively, a mismatch between chip supply and demand could lead to falling prices. Or investors' expectations could quickly shift if progress in training ever larger models begins to slow, or if new AI models offer only modest improvements. Overall then, perhaps the most plausible end to this bubble is not a traditional external shock, but a realisation that the underlying economics are no longer keeping up with the hype, prompting a sharp revaluation across related stocks. Artificial maturity If the bubble did burst, the most visible shift would be a sharp correction in the valuations of chipmakers and the large cloud companies driving the current boom. These firms have been priced as if AI demand will rise almost without limit. So any sign that the market is smaller or slower than expected would hit financial markets hard. This kind of correction wouldn't mean AI disappears, but it would almost certainly push the industry into a more cautious, less speculative phase. The deepest consequence would be on investment. Goldman Sachs estimates that global spending on AI-related infrastructure could reach US$4 trillion by 2030. In 2025 alone, Microsoft, Amazon, Meta and Google's owner Alphabet have poured almost US$350 billion into data centres, hardware and model development. If confidence faltered, much of this planned expansion could be scaled back or delayed. That would ripple through the wider economy, slowing construction, dampening demand for specialised equipment, and dragging on growth at a time when inflation remains high. But a bursting AI bubble would not erase the technology's long-term importance. Instead, it would force a shift away from the "build it now, profits will follow" mindset which is driving much of the current exuberance. Companies would focus more on practical uses that genuinely save money or raise productivity, rather than speculative bets on transformative breakthroughs. The sector would mature. But it would probably do so only after a painful period of adjustment for investors, suppliers and governments who have tied their growth expectations to an uninterrupted AI boom.

AI bubble trouble talk is overblown

Stock market veterans often say that it's impossible to tell when you're living inside a bubble. Truly irrational behaviour only becomes clear in hindsight, when sanity has returned. So why, suddenly, has talk of an AI bubble become so prevalent? Expectations are certainly running well ahead of current reality. That is the nature of any new technology, as investors try to predict the scale of a market that is still taking shape. But even if valuations are stretched, it doesn't mean AI investment is facing the kind of general implosion that happens when bubbles collapse in on themselves, rather than with the sort of severe corrections that often follow tech stock booms. The bubble theorists are grappling with two interrelated issues. One is an overbuilding of data centres that could leave a massive overhang of stranded assets. The other is the risk that some stock market valuations have completely lost touch with reality. Start with the boom in data centre construction. Most of this still lies in the future. Bubble talk really took off around the time OpenAI started disclosing the long-term deals it has put in place to support $1.4tn of planned investments. Much of this is notional, though: So far, OpenAI and Nvidia have firmly committed to building only a tenth of the potential capacity covered by their giant, $100bn deal. The rest will only follow if demand lives up to the companies' hopes, and if other investors can be found to foot the bill. For the foreseeable future, the AI market is facing a shortage of capacity -- hardly the kind of conditions that spell imminent disaster. It's certainly true that, on current projections of new construction, supply is set to catch up well before the AI companies are able to monetise their extra capacity. In a post on X last week, OpenAI chief executive Sam Altman pinned his company's hopes for hitting its revenue targets on initiatives it hasn't even launched yet, from a new push to sell AI to business customers, to potentially entering markets like cloud computing and robotics. Even if this points to a yawning gulf between the costs of building new data centres and the AI revenue they are expected to generate, it's too early to tell how big the gap will be, or how long the revenue lag will last. Handicapping the rate of growth is different from concluding that the technology, in its current form, will never be able to support the investments that are planned. The real bubble risk is that inherent weaknesses in large language models -- like their tendency to hallucinate -- will limit their usefulness, or that the costs of running them will make them chronically uneconomic for many purposes. It won't be clear for some time whether this will become a serious barrier to growth. Investors, of course, may get spooked even before that moment comes. Cutting off capital would become a self-fulfilling prophecy, hitting companies tied to the build-out. Yet that kind of dislocation, while hammering a company like OpenAI, would leave companies with stronger balance sheets, like Google and Microsoft, well placed to take more share in an AI market they have pinned their companies' futures on. If expectations are reset or delayed, then tech stock valuations would certainly take a bashing -- though, again, it need not lead to the kind of severe, lasting collapse that is characteristic of a bubble bursting. After the dotcom bust, it took the Nasdaq 16 years to make a lasting break back above its previous peak. Some tech stocks caught up in the AI boom could face that kind of prolonged winter. Palantir, valued at around 250 times this year's earnings, is benefiting from AI demand but could take many years to grow into its current valuation. But the price/earnings multiples of the biggest tech companies, though higher than their long-term averages, are not above levels they have seen at other points during the long tech boom. The demand for AI chips, meanwhile, continues to soar, prompting AMD this week to predict an annual market of $1tr by 2030. Nvidia is widely expected to underline the boom when it reports its latest earnings next week. Chip stocks are usually deeply cyclical, and a pullback in data centre spending would cause a serious dent, but that moment is not yet in sight. All of this suggests that companies riding the AI boom could be vulnerable to an across-the-board retreat that in some cases would be severe. But that doesn't necessarily mean that AI has a case of bubble trouble.

A simple reason why the biggest investors say they aren't worried about AI bubble, tech stock selling

Bill Ford (L) Chairman and CEO of General Atlantic, and Philippe Laffont (R) founder and portfolio manager of Coatue Management, speak during CNBC's Delivering Alpha event in New York City on Nov. 13, 2025. The biggest investors in the world often have a greater focus on the private than public markets, but with the artificial intelligence boom set to reshape the economy for decades to come, they can't afford to not pay close attention to what's taking place with the largest publicly traded tech stocks, and they are not worried. Amid fears about risky over-concentration in the so-called "Magnificent Seven" stocks that dominate the S&P 500, and related fears of an AI bubble, two managers overseeing tens of billions of dollars from investors told CNBC at its Delivering Alpha conference last week they remain bullish on what's taking place in the U.S. tech sector and the huge sums being invested in AI. Coatue Management founder and portfolio manager Philippe Laffont, whose fund manages roughly $70 billion in assets, according to a Securities and Exchange Commission filing, said at Delivering Alpha that there is an important difference between now and the dotcom bubble, what he called the "hyper-scaler advantage," a reference to the ability of companies including Alphabet, Microsoft and Amazon to invest what Wall Street estimates may reach over $500 billion in AI bets next year. General Atlantic Chairman and CEO Bill Ford, whose firm manages $118 billion in assets, agreed that the dollar signs currently being discussed in the market are a reason for conviction about the biggest public tech stocks rather than doubts. "The people driving change in AI are the large public companies and the incumbents, they have the advantage," he said. Even as Ford said his firm remains focused on the private market opportunities and how AI can be applied to its portfolio companies -- investments he says are being made across every one of the 200 companies in which General Atlantic is invested -- he added, "You cant invest in the private market without an understanding of what Oracle, what Google, what Microsoft is doing." "You can't make good decisions. We have to be fully aware of what they are doing even if we are not investing in them," Ford said. General Atlantic has been "pretty aggressively" investing across its portfolio companies in AI and Ford said it has already seen a "pretty high payback," and he added that is in what he would describe as just the "front edge" of the value opportunities from apply AI, in areas like customer care, coding and digital marketing. Laffont, whose firm invests in both public and private companies, said it is fair to have concerns about tech stocks that increase in value very quickly because that can be at odds with a bullish view of valuations over the longer term. That's because with publicly traded stocks, he said, belief in the future doesn't necessarily mean that belief hasn't already been priced in. He cited Oracle's recent stock chart as an example -- though he did not specifically indicate concern about the company which other market skeptics have recently voiced -- which over the past year rose from $150 per share to near $350 per share, before falling back into the $220-range.

AI anxiety on the rise: Startup founders react to bubble fears

Markets were on edge this week as a steady stream of negative headlines around the artificial intelligence trade stoked fears of a bubble. Famed short-seller Michael Burry cast doubt on the sustainability of AI earnings. Concerns around the levels of debt funding AI infrastructure buildouts grew louder. And once high-flyers like CoreWeave tanked on disappointing guidance. CNBC's Deirdre Bosa asked those at the epicenter of the boom for their take, sitting down with the founders of two of the buzziest AI startups. Amjad Masad, founder and CEO of AI coding startup Replit, admits there's been a cooldown. "Early on in the year, there was the vibe coding hype market, where everyone's heard about vibe coding. Everyone wanted to go try it. The tools were not as good as they are today. So I think that burnt a lot of people," Masad said. "So there's a bit of a vibe coding, I would say, hype slow down, and a lot of companies that were making money are not making as much money." Masad added that a lot companies were publishing their annualized recurring revenue figures every week, and "now they're not." Navrina Singh, founder and CEO of startup Credo AI, which helps enterprises with AI oversight and risk management, is seeing more excitement than fear. "I don't think we are in a bubble," she said. "I really believe this is the new reality of the world that we are living in. As we know, AI is going to be and already is our biggest growth driver for businesses. So it just makes sense that there has to be more investment, not only on the capability side, governance side, but energy and infrastructure side as well." Watch this video to learn more.

Business and AI leaders are getting nervous about a bubble

Like other infamous bubbles -- the dot-com bubble, the cryptocurrency bubble, and the housing bubble of the 2000s -- an AI bubble could cause massive disruption to the wider economy. A bubble occurs when the price of something rises above its actual value, typically because investors become overly excited. And investors have been very excited about AI. A recent report from Stanford University estimated that AI investment reached $109.1 billion in the U.S. in 2024. That's 12 times higher than China's investment and 24 times higher than the UK's investment. CNBC reported that Goldman Sachs' David Solomon, Morgan Stanley's Ted Pick, investor Michael Burry, and Picsart CEO Hovhannes Avoyan are all worried about a potential AI bubble. In fact, even some AI leaders are getting nervous. "I think the evaluations are pretty exaggerated here and there, and I think there is signs of a bubble on the horizon," Jarek Kutylowski, CEO of German AI firm DeepL, told CNBC. This isn't the first time we've heard about a potential AI bubble. In August, OpenAI's Sam Altman talked about his own AI bubble fears to a small group of reporters, including The Verge's Alex Heath, over dinner in San Francisco. "When bubbles happen, smart people get overexcited about a kernel of truth," Altman told the reporters. "If you look at most of the bubbles in history, like the tech bubble, there was a real thing. Tech was really important. The internet was a really big deal. People got overexcited. Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes."

Tech execs admit AI is a bubble and they're pretty happy about it: 'We can't deny there's a ridiculous amount of investment going on' | Fortune

If the AI boom had a physical form, it was alive and kicking at Web Summit this week as 71,000 startup founders, venture capital investors, tech CEOs, and the media who follow them gathered under literal storm clouds in Lisbon, Portugal, to discuss the future of the industry. Tech stocks sold off dramatically as the conference wore on, after 'Big Short' investor Michael Burry pointed out that some AI hyperscaler tech companies -- including Meta and Oracle -- were elongating the depreciation schedules of their AI capital expenditure (capex) to make their short-term profitability look more favourable. The Nasdaq Composite lost 2.3% yesterday. In addition, Oracle shares declined by 30% over the last month as investors rejected the company's plan to increase its debt in large part to spend more on AI chips. But few people inside the giant dome of the MEO arena at Web Summit seemed concerned. Fortune asked a dozen executives at the conference for their opinions. What follows is a selection of their perspectives. Broadly, people fell into three categories of opinion on whether AI spending is sustainable: Laura Chambers, CEO of Mozilla -- maker of the Firefox browser -- sees the situation as a classic, straightforward bubble. Funding is abundant, it is easier than ever to make low-grade products, and most AI companies are running at a loss, she says. "Yes. It's really easy to build a whole bunch of stuff, and so people are building a whole bunch of stuff, but not all of that will have traction. So the amount of stuff coming out versus the amount of stuff that's going to [be sustainable] is probably higher than it's ever been. I mean, I can build an app in four hours now. That would have taken me six months to do before. So there's a lot of junk being built very, very quickly, and only a part of that will come through. So that's one piece of the bubble," she said. "I think the most interesting piece is monetization, though. All the AI companies, all these AI browsers, are running at a massive loss. At some point that isn't sustainable, and so they're going to have to figure out how to monetize." Babak Hodjat, chief AI officer at Cognizant, said he believed diminishing returns were setting in to large language models. The DeepSeek launch from earlier this year -- in which a Chinese company released an LLM comparable to ChatGPT for a fraction of the cost -- was a good example of this. Building AI was once a huge, expensive, and difficult undertaking. But today, many AI use-cases (such as custom-built, task-specific AI agents) don't need huge models underpinning them, he said. "The bulk of the money that you see -- and people talk about a bubble -- is going into commercial companies that are actually building large language models. I think that technology is starting to be commoditized. You don't really need to use that big of a large language model, but those guys are taking money because they need a lot of compute capacity. They need a lot of data. And their valuation is based on, you know, bigger is better. Which is not necessarily the case," he told Fortune. Dan Gardner, CEO of digital creative agency Code & Theory compared the current moment to the dot-com boom of 2000: "It is a bubble, and it's not a bubble. It's a bubble in the sense that there will be tremendous amount of wasted capital [like what happened in the 2000 crash.] That was a bubble, and a tremendous amount of people lost their money. And we had some of the biggest companies in the world [like Amazon and Google], trillion-dollar companies, that came out of that." Lyft CEO David Risher said that AI may be a financial bubble right now, but the companies within it are nonetheless building tools and learning skills that will be transformational in the long term. Talking to CNBC, he said: "Let's be clear, we are absolutely in a financial bubble. There is no question, right? Because this is incredible, transformational technology. No one wants to be left behind." But he argued that the financial bubble was a short-term problem. "The data centers and all the model creation, all of that is going to have a long, long life, because it's transformational. It makes people's lives easier. It makes people's lives better ... On the other hand, you know, the financial side, it's a little risky right now." Several AI supply companies can't keep up with demand -- and are pretty happy about it. They aren't blind to the potential for a contraction, but know the business they are doing is real and backed by demand from clients with deep pockets. Brad Smith, president of Microsoft, told Fortune: "From a long-term perspective, I think the answer is no. I think that we've got years, if not decades, ahead of us for growth. From a short-term perspective, I'll only speak for Microsoft; I can't speak for every company in the industry. We have more demand than supply. That's the reality from customers, and we have an ongoing pipeline of demand and needs, and we see steady growth, and we're encouraged by where things are going. And we'll always be disciplined as we're investing." Emily Fontaine, global head of venture capital at IBM, operates a $500 million AI-focused venture capital fund. She has already made 23 investments into companies building AI products that often fit into an ecosystem run by IBM products or by clients of IBM. "I strongly believe, if you have conviction, and you're investing in the right companies, you're gonna make the right decisions for your criteria," she said. She admits the industry is living through a heady boom: "We can't deny a ridiculous amount of money is going into AI startups, right? $160 billion, year-to-date. That's just the U.S. Look at that compared to 2024, which was $104 billion. It's a huge amount. We can't deny there's a ridiculous amount of investment going on." But she says client demand is robust: "I strongly believe that investing is going to pay off. Over the last few months we've gone from AI adoption in say, 26% now to 43% in enterprise companies." Ami Badani, head of strategy/CMO at chipmaker ARM, has a front row seat. ARM has a partnership with Nvidia in which the former provides the latter with multiple services, licenses, and products. They just can't make chips fast enough, she told Fortune. "I feel like there's enough demand. Even today, you look at demand and that exceeds supply, and there's an insatiable amount of demand and appetite for where we need to get to, so I don't really worry about 'could folks pull back?' If you look at GDP growth and where we believe that we need to get to in terms of AI, and these use cases, that's all limited by power and compute," she said. "So I don't worry about it [a bubble] too much. It doesn't wake me up at night, if that's what you're asking." Nicolas Sauvage, president at TDK Ventures, supervises the VC firm's $500 million investment fund. Like Badani, he sees an environment where demand is stronger than supply. "Are we going to have a moment where the demand is going to be less than the supply, especially when every company is racing to build that infrastructure, are getting as much chipset as they can today? The demand is matching. Actually, the demand is higher than the supply, so we're not seeing that over-supply," he said. He is, obviously, aware that the major AI companies are not yet showing the revenues they will need to demonstrate that they are sustainable businesses. But that is because they don't yet need to -- in fact they can turn on the revenue switch any time, he said: "My feeling is that any of these companies could decide to turn the revenue tap on if they want it. They are not at the point where they are being challenged to do that, so the question is, when do they decide to do it?"

Dark Clouds Suddenly Gathering Over AI Industry

A major tech selloff is shaking up Wall Street as the enormous gulf between AI company valuations and their lagging revenues continues to grow. As the Wall Street Journal reports, the stock market has been showing marked signs of "fragility," with Nvidia slipping seven percent last week. Despite signs of an end to the ongoing federal shutdown buoying up some excitement, the AI chipmaker continued its plunge this week, sliding another three percent on Tuesday. Meta shares have also fallen almost 17 percent since its quarterly earnings report late last month, despite the company beating investors' expectations. AI software giant Palantir has suffered a similar fate, dropping eight percent since posting better-than-expected numbers early last week. In short, there's clearly a dark cloud gathering over the AI industry, where lofty claims of immense capabilities always seem to remain in the future, and investors are increasingly balking at astronomical spending on AI infrastructure. There are growing concerns that the untold billions of dollars being spent on data center buildouts may never lead to the promised returns. Tech leaders are now openly discussing an AI bubble that could plunge the United States deep into a recession if it were to pop, economists have warned. Adding to the uncertainty is Japanese company SoftBank, which announced this week that it had sold off its Nvidia stake for $5.8 billion -- money it promptly used to bankroll different AI bets, including heavy investments in OpenAI. SoftBank's shares slid as much as ten percent on Tuesday, following concerns that SoftBank had to sell in order to meet exploding funding needs. In an apparent attempt to calm spooked investors, SoftBank Vision Fund CFO Navneet Govil promised that the AI hype wouldn't lead to a disaster. "What's different between the dotcom boom and today is that AI companies are generating meaningful revenues," he told reporters, as quoted by Reuters. "There's a lot of talk about [capital expenditures] spend, but it's actually driven by demand." Looming in the shadows is Michael Burry, who famously shorted the US housing market before its collapse in 2008. Last week, Burry bet over $1 billion that the share prices of AI chipmaker Nvidia and software company Palantir will fall, stoking further fears. Companies are already suffering billions of dollars in losses as revenues continue to lag behind. While the privately-run OpenAI is playing its cards close to its chest, the Sam Altman-led firm is planning to spend $1.4 trillion over the next eight years. That's despite only making around $20 billion in annual revenue today as it continues to hunt for a meaningful business model. But whether the latest stock market selloff is symptomatic of an impending implosion is anything but certain. Investors continue to pour billions into the AI industry, with firms announcing billion-dollar deals and plans for enormous data center projects. That's despite a notable lack of a "clear financial model for profitable AI," as the WSJ puts it -- an enormous bet that has once bullish investors growing increasingly wary.

'Vibe revenue': AI companies admit they're worried about a bubble

LISBON, Portugal -- Top tech executives told CNBC they're concerned about a bubble forming in the artificial intelligence sector, underscoring growing unease within the industry over soaring valuation. In recent weeks, markets have been reckoning with the notion that too much capital is pouring into the AI boom, clouding the outlook on revenue and actual profit and putting high valuations into question. Up to now, warnings around overstretched valuations have mostly come from investors and leaders in the world of finance. Goldman Sachs' David Solomon and Morgan Stanley's Ted Pick have warned of potential corrections as valuations of some major tech firms reached historic highs. The concerns have been crystallized by famed 'Big Short' investor Michael Burry, who this week accused major AI infrastructure and cloud providers, or 'hyperscalers' of understating depreciation expenses on chips. Burry warned that profits at the likes of Oracle and Meta may be vastly overstated. He recently disclosed put options that bet against Nvidia and Palantir. However, CEOs of companies who are themselves developing AI, expressed their concerns this week during interviews with CNBC at the Web Summit tech conference in Lisbon. "I think the evaluations are pretty exaggerated here and there, and I think there is signs of a bubble on the horizon," Jarek Kutylowski, CEO of German AI firm DeepL, told CNBC on Tuesday.

What's Next for AI? Andreessen Horowitz Founders Share Their Thoughts

Stocks of companies tied to artificial intelligence have been hitting stratospheric levels for over a year now, thrilling investors, but also causing concerns about a potential AI bubble. As startups close breathtaking funding rounds, like the $40 billion OpenAI collected in March of this year, fears of an AI bubble are growing - and some say a burst could be even bigger than the dotcom bubble of the late 1990s. The bubble theory is hotly debated. Some within the industry say they agree the investment landscape is bloated, including OpenAI co-founded Sam Altman. Other experts, like Goldman Sachs, however, say we're not in one (yet) - and Fed Chair Jerome Powell has been skeptical of the bubble calls. As that debate rages, investors continue to fund AI startups. Few investors are in as deep as Marc Andreessen and Ben Horowitz. Their venture firm, Andreessen Horowitz (commonly called a16z) has sunk billions into the AI space. In April, it was reported the company was in early talks to raise a massive $20 billion AI-focused fund. The two investors recently came together at a16z's Runtime conferences to talk about where AI can go beyond chatbots. Neither was willing to make any specific predictions about AI's forthcoming capabilities, saying it's too early to even imagine that. Andreessen likened AI to the personal computer in 1975, noting there was no way at that time to imagine what PCs would be capable of today. However, he expects similar levels of advancement - from a stronger starting point. AI, he said, is already approaching levels of human creativity - and while Andreessen would love to see humans continue to have superiority in that area, he thinks it's unlikely. Tools like OpenAI's Sora 2 video, for instance, are already capable of creating realistic scenes, animations, and special effects - and the introduction of AI Actress Tilly Norwood has caused an outcry and prompted debate in Hollywood. "I wanna like hold out hope that there is still something special about human creativity," he said. "And I certainly believe that, and I very much want to believe that. But, I don't know. When I use these things, I'm like, Wow, they seem to be awfully smart and awfully creative. So I'm pretty convinced that they're gonna clear the bar." Horowitz agreed, saying that while AI might not currently create at the same level as human artists, whether painters or hip-hop performers, that's largely due to how little it has learned so far. It's just a matter of time before it has an equal or superior level of talent. And some artists are already looking to use AI to collaborate, he said. "With the current state of the technology, kind of the pre-training doesn't have quite the right data to get to what you really wanna see, but, you know, it's pretty good," he said. "Hip hop guys are interested because it's almost like a replay of what they did -- they took other music and built new music out of it. AI is a fantastic creative tool. It way opens up the palette." While AI can devour as many data sets as programmers throw at it, that doesn't give the technology situational awareness. It is, in essence, book smarts vs. street smarts. But the robotics field is expanding quickly. Elon Musk and Tesla are working on humanoid robots and Robotics company 1X has already started to take preorders for a $20,000 humanoid robot that will 'live' and work around your home. Once that technology and AI are blended, Andreessen said, AI will see a significant jump in actionable intelligence. "When we put AI in physical objects that move around the world, you're gonna be able to get closer to having that integrated intellectual, physical experience," he said. "Robots that are gonna be able to gather a lot more real-world data. And so, maybe you can start to actually think about synthesizing a more advanced model of cognition." While there are plenty of experts who warn the AI market could be in a bubble right now, including OpenAI CEO and co-founder Sam Altman, Horowitz dismisses the idea, saying bubbles occur when supply outstrips demand - and that's not the case with AI. "We don't have a demand problem right now," he said. "The idea that we're going to have a demand problem five years from now, to me, seems quite absurd. Could there be weird bottlenecks that appear, like we don't have enough cooling or something like that? Maybe. But, right now, if you look at demand and supply and what's going on and multiples against growth, it doesn't look like a bubble at all to me."

'You Do Want A Bubble,' Says Groq CEO Jonathan Ross On AI Frenzy -- Insists The Money Will Be 'Returned With Interest' Despite Fears Of A Crash - Meta Platforms (NASDAQ:META), Intel (NASDAQ:INTC)

The surge of money into artificial intelligence is a sign of activity, not a warning sign of collapse, according to Groq CEO Jonathan Ross. Bubble Or Boom Ross told CNBC last month that rising investment reflects competition among companies racing to build better AI systems. When asked whether a bubble was forming, he pushed back and said he saw strong returns for real breakthroughs in the field. "There's subtlety and nuance here," he said. "You do want a bubble because the bubble is the sign that there's a lot of economic activity going on, and you just attract all sorts of people." He said engineers, researchers and investors all take bigger swings during periods of excitement. Don't Miss: Missed Nvidia and Tesla? RAD Intel Could Be the Next AI Powerhouse -- Just $0.81 a Share 7 Million Gamers Already Trust Gameflip With Their Digital Assets -- Now You Can Own a Stake in the Platform He argued that the attention helps push progress faster. According to Ross, the debate should not center on whether AI is in a bubble, but whether money is flowing toward the best ideas. "When you focus on the real AI innovations, you can't put enough money into that, and there will be great returns," he said. However, he also acknowledged mistakes happen, adding there will be investments "that don't return." Money Will Come Back Ross said the key question is whether the money flowing into AI will generate long-term gains. "Is the amount of money that's paid into this AI boom going to be returned with interest? I think the answer to that is, yes," he told CNBC, adding that the strongest returns will come from "real AI innovations." Ross founded Groq in 2016 after working as an engineer at Google, where he helped design the company's Tensor Processing Unit chips, which are built for machine-learning workloads. Trending: Bill Gates Invests Billions in Green Tech -- This Tree-Free Material Could Be the Next Big Breakthrough As investors continue to hunt for computing power, demand for processors has grown. Microsoft Corp. (NASDAQ:MSFT) said capital expenditures reached $34.9 billion, driven by demand for cloud and AI offerings, according to its most recent quarterly results. Meanwhile, chipmakers and cloud providers have announced new spending on infrastructure as companies train and deploy larger and more complex models. Others See Risks The enthusiasm has also led to warnings from major tech voices. Former Intel Corp. (NASDAQ:INTC) CEO Pat Gelsinger told CNBC last month that there is "of course" an AI bubble, even though he does not expect it to burst immediately. Meanwhile, Nick Clegg, former president of global affairs at Meta Platforms Inc. (NASDAQ:META), told CNBC that the AI boom has created "unbelievable, crazy valuations" and said the likelihood of a market correction is "pretty high." Read Next: Wall Street's $12B Real Estate Manager Is Opening Its Doors to Individual Investors -- Without the Crowdfunding Middlemen If there was a new fund backed by Jeff Bezos offering a 7-9% target yield with monthly dividends would you invest in it? Image: Shutterstock INTCIntel Corp$34.94-2.70%OverviewMETAMeta Platforms Inc$599.49-1.71%MSFTMicrosoft Corp$498.80-0.89%Market News and Data brought to you by Benzinga APIs