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The AI bubble will pop the same way the dotcom bubble popped. A lot of money lost and the hype will die down, but the technology will remain and reach a homeostasis at the level where it's actually a helpful tool.
When the dotcom bubble popped the internet didn't disappear, it just became what it was supposed to be. When the AI bubble pops the technology will still be there for use cases where it's actually appropriate and useful.
GenAI is here to stay in one form or another, with long term impacts.
I wager the bubble will pop when OpenAI finally admits they have no path to making good on their purchasing commitments. They aren't the whole bubble and Altman has made what should be obviously the worst financial moves, however the broader market will be more bearish on anything they vaguely think to be OpenAI like.
I suspect it'll be with a year from now, based on what I've read.
The companies will never stop doing the GenAI things, but they may be less utterly obnoxious about it. I suspect Google and Anthropic have the highest chances of enduring a pop, anthropic for being well regarded in the field and Google because they get to make most phones go to them automatically whether requested or not.
I think GenAI will persist in obnoxious ways, but at least more bearable without folks desperately needing it to be adopted for the sake of their wealth.
The industry will end up with one or two winners and a lot of losers. Very hard to predict these things (smart money in 1997 was that Apple was about to file bankruptcy). One or two companies will have success and the rest will evaporate or be absorbed. Then the AI product itself will be priced up (and dumbed down) significantly.
AI will not go away, but will be far more limited and specialized. The day of free general access to powerful chatbots will be up.
Anybody thinking AI goes away is just wishfully thinking, and/or ignorant.
While I agree that AI is here to stay, he did say the bubble popping. I could believe that there could be a reduced level of investment for a while. In the past, we did have periods where we thought that various AI tasks would be easier to solve than they were, and investment fell back as we discovered that there were more hard problems to solve before we could accomplish a particular feat. Didn't go away, but did see a decrease in work on it for a while.
https://en.wikipedia.org/wiki/AI_winter
In the history of artificial intelligence (AI), an AI winter is a period of reduced funding and interest in AI research.[1] The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or even decades later.
The term first appeared in 1984 as the topic of a public debate at the annual meeting of AAAI (then called the "American Association of Artificial Intelligence").[2] Roger Schank and Marvin Minsky—two leading AI researchers who experienced the "winter" of the 1970s—warned the business community that enthusiasm for AI had spiraled out of control in the 1980s and that disappointment would certainly follow. They described a chain reaction, similar to a "nuclear winter", that would begin with pessimism in the AI community, followed by pessimism in the press, followed by a severe cutback in funding, followed by the end of serious research.[2] Three years later the billion-dollar AI industry began to collapse.
There were two major "winters" approximately 1974–1980 and 1987–2000,[3] and several smaller episodes, including the following:
1966: failure of machine translation
1969: criticism of perceptrons (early, single-layer artificial neural networks)
1971–75: DARPA's frustration with the Speech Understanding Research program at Carnegie Mellon University
1973: large decrease in AI research in the United Kingdom in response to the Lighthill report
1973–74: DARPA's cutbacks to academic AI research in general
1987: collapse of the LISP machine market
1988: cancellation of new spending on AI by the Strategic Computing Initiative
1990s: many expert systems were abandoned
1990s: end of the Fifth Generation computer project's original goals
Enthusiasm and optimism about AI has generally increased since its low point in the early 1990s. Beginning about 2012, interest in artificial intelligence (and especially the sub-field of machine learning) from the research and corporate communities led to a dramatic increase in funding and investment, leading to the current (as of 2026) AI boom.
Obviously, we did achieve a number of those
like, we have pretty solid machine translation of human language today. I remember, pre-Brexit, a senior EU translator for the UK talking about EU translation work. One thing he mentioned was that he did all of his first drafts via Google Translate and then just did manual cleanup by hand
and I'd call that a fairly prestigious translation position. But it took more time and research than we initially expected.
I think the AI bubble will pop when another part of the economy needs capital, sucking up the capital going to AI.
AI burning money for market share isn't new to Wall Street, that's been tech for the past generation. The issue is going to be liquidity to not test these valuations. Once they are tested, they are going to collapse.
Our 401k will go down a bit, a bit of money will be transferred from retail investors to the big players, the rich will get richer and the poor will get poorer. You won’t see so many ads for dumb AI services that literally no one wants. The big players will be fine, maybe, maybe, a few data centers shut down, but most of them don’t.
Probably:
Maybe:
Internet was the "AI" of the dotcom bubble. It didn't go anywhere after the bubble burst and neither will AI. What will go away are the companies with only hype but no product. Amazon and eBay came about during the dotcom bubble and now companies like OpenAI and Anthropic will likely be equivalent ones.
The bubble bursts when investors start losing faith that the company they have invested into will become profitable so they pull out, which makes other investors get scared so they pull out too and then the company goes under.
Exactly. The AI bubble popping will not "un-invent" AI technology. The technology exists and can be a useful tool for the right use cases, just like the internet still existed after the dotcom bubble popped.
LLMs will still exist and will still be trained and used. What won't exist are AI only companies.
OpenAI and Anthropic will likely be the companies going under when the bubble bursts. Because unlike all the other big companies involved in AI (Nvidia, Microslop, Google, Meta etc.), they don't have anything else to diversify with and they have never made a profit. When investors withdraw they are done for. The other companies will take a hit, but they will survive, because they have profits from other things.
The difference is that there were services that could leverage the Internet and be profitable. Every AI company is wildly unprofitable and burning unfathomable amounts of money. There's no path for them to become profitable, unlike some companies in the dotcom era.
I personally would exclude OpenAI from my list of likely to endure. OpenAI partners are largely switching to Anthropic, their models and tools are generally less well regarded. The only time I had someone advocate for them it was due to some scenario where it was much cheaper.
Problem is that based on what I've read. Altman has way overextended his company. The financial obligations outpace their revenue and likely revenue way too much.
Anthropic has some risk since Microsoft, Google, and Apple insourcing would be a big problem for them.
One change for me is celebrating on the anniversary of an AI company shutting down.
Big tech will keep their AI. Like others here have said, AI companies without another income stream will go belly up.
Some data centers will be sold and repurposed. Others will sell off their hardware to the consumer market.
Lower temperatures and less noise near the former data centers.
I don't see property values going back to where they were unless a data center is dismantled and the water table recovers.
I think it will be triggered by the massive overvaluation of many AI labs. Investors will sell. In the meanwhile, other sectors will still have to adjust to the new reality of token generators, so the wider economy is impacted.
LLMs will not disappear, just like real estate did not disappear after 2008,and the internet did not disappear after the dotcom bubble burst.
But I can imagine the end of hyperfocus on the "AGI race".
I’m assuming one or two significant players will go bust, but probably not the biggest like Google, Microsoft, Amazon. They might take some serious hits, and they’ll deprioritize AI, but still exist. Maybe someone like Oracle or xAI goes under and gets parted out like an airliner getting scrapped. A lot of data center projects will be cancelled, others will shut down, and the local politicians that pushed for those data centers will see their political careers end as their districts are left with big empty buildings and infrastructure debts that will be hard to pay.
Wouldn't such turbulent times be exactly when established companies are at risk as well? E.g., what electrification is doing to VW.
Although the risk for AI-first vs general big tech does depend on the root cause of the disruption.
Well yes, but for example, when someone activated voice interaction with their phone, Google or Apple decide what AI solution is used, and Google already decided to roll their own. When most companies go into AI, just expanding their existing relationship with Microsoft is what their business leaders like. Generally the established companies have preserved the customer engagement even when they resell newcomers.
An example of what you ponder would be like Sears, kmart, Amazon. The thing was that Amazon was greatly valued going direct. People loved the prices and shipping speed. Imagine if instead Amazon decided to partner with Sears and K mart and those companies largely handled the customer engagement with Amazon fulfillment on the backend. Amazon would have been much more exposed to those companies bringing it in house. This latter situation more closely resembles OpenAI and Anthropic right now, at least for the big businesses likely to pay enough after the price hikes.
Dogs and cats living together etc.
Social media companies will fill the gaps, continuing to spread their toxicity through society unchecked. The Pied Piper of Hamelin is starting to look more like a cautionary tale.
Considering from where the bubble grows, my wisest guess as to when it will start showing cracks (and I'm not very wise, by the way) would be Republicans doing bad at next elections.
As of now it seems that any losses from AI industry would simply be tanked (Nvidia's capitalization, for example, still ain't a joke, they've got a lot of money to burn) or socialized. Little bits of regulations or opposition to socializing of losses may actually move the loss needle beyond pain point, where we can hope for panic to ensue.
If bubble pops - AI is here to stay anyway. Chinese have shown with their DeepSeek that you can run decent sized models locally, and the main gatekeeper of local AI is, you guessed it, Nvidia. Prices for server GPU's are disproportionately high and one of the reasons is to not allow plebs like us to have that. But with further optimization of AI models they'll become more and more accessible on hardware consumers already have.
My second guess of when though would be investors getting tired of AGI promises as it is AGI that has to magically turn money pit of AI into unprecedented profits.
The old message to people: only the first people get rich in a gold rush. The people who make the real money are the people selling shovels to the late investors.
Nvidia are selling shovels. They'll do great as long as they prepare for the pivot after the people rushing give up.
