How the AI Bubble Might Play Out

[Celerity]

There are a multitude of financial risks now accumulating.

https://prospect.org/2025/12/03/how-ai-bubble-might-play-out/



I may not know everything about business, but I’m reasonably confident that it’s a bad sign when you write a seven-page letter about how your company is not Enron. That was the task of some poor soul at Nvidia over the Thanksgiving holiday, trying to calm market nerves put on edge by short sellers alleging financial improprieties. One sensational claim asserted that Nvidia was having trouble collecting billions of dollars in sales, with spikes in inventory and lower cash flow than its competitors. Michael Burry, last seen correctly predicting the housing bubble in The Big Short, also questioned how much cash Nvidia was leaking to investors and employees. And skepticism about Nvidia funding its own customers to bulk up sales has already been rampant.

Nvidia refuted much of this in its memo, but there was a quality to it best expressed by an internet meme. To sum up, Nvidia’s “We are not Enron” T-shirt has people asking a lot of questions already answered by the shirt. A slap fight between a tech company and some short sellers would be less interesting if we all weren’t so reliant on the outcome. Nvidia’s graphics processing units (GPUs) are the guts of most of the data centers now proliferating throughout the country. Deals between computing providers, AI model makers, speculative data center builders, and private credit firms (read: shadow banks) lending into the build-out represent a historically large source of the nation’s industrial activity. It’s powering energy demand, stock valuations, and wild venture capital deals for companies with no products, just vague mumblings of “something something AI.”

In short, AI has eaten America. Whether it rests on a solid foundation or on quicksand will determine whether we have a future of prosperity or pain. And so when Nvidia starts wearing a “We are not Enron” T-shirt, that sinking feeling sets in. But what are the actual vulnerabilities here? Why could AI as a business fail even if its models produce something useful in some form? The possibilities are so vast that it’s hard to summarize, but let me try. As outlined in the latest episode of the Organized Money podcast that I co-host (listen above), data centers are both infrastructure and technology, but they may be better thought of as real estate.

They are giant boxes with tenants who need computing power, built with construction loans that roll over into traditional real estate loans and bundle into mortgage-backed securities, in case you wanted to be reassured that nothing untoward is going on. After all, when have mortgage-backed securities ever been a problem for the economy? Usually an “anchor tenant”—a big AI firm like OpenAI or Meta or Amazon—guarantees payments of what amounts to rent. They’re paying for the build-out, but through complicated off-balance-sheet vehicles owned by lenders and underwriters, as I’ve talked about at more length elsewhere. But AI firms are also floating corporate bonds in unprecedented numbers, growing the debt load.

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[highplainsdem]

1. Saw this on X today:

Link to tweet

[Norrrm]

2. Have AI analyze and write up the situation.

Would you trust it?

[Celerity]

3. No, I do not trust AI summaries at all. So much disinfo and errors. It is a major problem on DU. Posters toss out AI

summaries for replies and even OPs and think they are contributing valuable information to the discussion. Some even try and fob off AI product as their own work with no attribution. It is dismaying and a bad, bad look for the board IMHO.

[FascismIsDeath]

5. Ethical problems aside, generative AI itself is a useful tool but like everything else, people should verify.

For example, when Google search has an AI blurb about something, just about everything in that blurb has a little link you can click on and see where it got the information from. Just like I've always told people about using Wikipedia, check the citation and see what it says and where its from. Its the same for using AI to research something. In that context, its fine as a tool for quick information or a portal to the actual places where the information actually comes from.

There are many other issues with how people are using it and the way they are obtaining training data for the models and of course the horrible environmental impact of these massive data centers. But those are other topics.

[Xolodno]

4. I remember going to a conference and it was all about "big data".

More than half of those vendors did not survive.

Vendors are pushing AI hard right now because companies need to recoup their investments and pay the bills. CEO's are eating it up because they see dollar signs in the reduction of employee's. I've played around with AI, its a very useful tool, however, and this will sound cliche, it doesn't think outside the box. To jump from one data stream to another or figure out how to merge two or more data streams together, etc. it can't do. You still need a human.

Of course the problem with these bubbles, it can take a few years for it to come crashing down. Meanwhile the rest of us suffer.

[Intractable]

6. So, apparently, one of the major risks of AI is that companies are so heavily invested and deeply indebted

that they will default on their loans and crash the economy.

Or, alternatively, be successful and eliminate every job, and thus crash the economy.

We might not make it to the AI danger we all worry about -- something like a Skynet.