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.
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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".
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.
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.
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.
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.
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.
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.
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.
It will if it is too expensive to generate a positive return on investment. That’s not to say that there aren’t (very) specific use cases where running an LLM makes sense, but the general use case of attempting to replace human workers with AI will likely be recognized for the pipe dream that it is. Companies are already realizing this with the AI bills coming due now, and this attitude will compound once they start having major failures and no one is still around who can fix the problems.
Are you saying that you think there is a possibility that AI technology, especially LLMs, would disappear from usage? Even as search tools? Even used locally?
Like I said above, I think there will be some very specific cases where running an LLM makes sense. Think along the lines of querying lakes of scientific data. This won’t be something of value to the average Joe or the average company. My experience with using LLMs for general search has been very hit or miss. I always end up using a general search engine, even for internal data sources.
Maybe that’s just you but millions of people are interfacing with LLMs every day as a replacement to a traditional search engine. I don’t see that changing. Either way, sounds like you are agreeing that AI will not go away entirely. That would be a silly thing to say.
It’ll also go dormant as LLMs are only one AI tech. Other AI tech will be developing while supporting infrastructure grows until we have another boom. World models for example and JEPA. That’s why Meta is pushing AI glasses. They need training data.
Those millions of people using AI for general search are currently getting it for free, which is going to end when the bubble bursts and the companies providing it go under, if not sooner when said companies try to make a profit. This is exactly what’s happening to corporate AI customers now. They are realizing there isn’t a good ROI now that OpenAI and other AI providers are being forced to charge proper costs for queries and tokens, rather than the teaser or “adoption” rates they charged before.
Interesting theory. I’d be surprised if Google started charging for their AI results. Too much free training data and they can afford to keep models running for the masses. They’re not solely an AI company. At the worst, these AI companies get swallowed up by bigger companies that can keep running even if AI is not profitable, which it is in some cases.
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.
You'll be able to buy LLM hardware (video cards and RAM) for cents on the dollar as companies fail. The NASDAQ will drop a bit, the number of LLMs will reduce
Better than the GFC where all we got was Enron corporate branding and expensive houses
Comparable to dot com where loads of nerds bought $5 servers
I think part of the process is going to be the enshittification of AI services. (Temporary, until the technology for sustainable infrastructure catches up.) Tokens will cost a premium, and a lot of businesses that depend on AI will turn to China's cheaper offerings.
Hobbyists will turn more to home-grown AI systems.
In recent news, Chinese AI is catching up to Anthropic. It'll be interesting if the Trump administration tries to block the Chinese AI offerings in order to bolster US ones. Trump and the AI tech bros are familiar bedfellows after all.
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.
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.
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.
Ai is here to stay. There will be winners
Many companies will take huge losses but the real losses will be communities with huge dead buildings and unrewarded tax incentives. Power companies with wasted investments trying to feed datacenters that no longer exist and the rate payers that have to pay for it
I think there will continue to be a free tier: Apple is a great example of using small local ai to do useful things for their customers. However the latest models will be have to be much more expensive to cover the business case. Scale matters, so there’s a good chance the winners won’t just dominate in a country but globally
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.
Probably:
- GenAI continues to be used for marketing, and anything else where form matters more than substance
- anything where meaning is really critical might still use it, but will require solid oversight/governance. Software, research, medicine, teaching, etc.
Maybe:
- AI bubble bursts, with ripple effects into the broader economy, particularly in the US. This will be a huge problem if big banks are heavily leveraged for their AI investments (not sure this is the case, but it seems likely). If this happens, the collapse will be much worse than the GFC, perhaps worse than the great depression.
- Political spillover.. No idea what this will look like, but it's a big trigger...
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