The entire US economy is downstream of the AI buildout dam, and that dam is almost certain to fail
– by New Deal democrat
I’ve been ambivalent about whether the mania for AI is a Boom or a Bubble. That’s because whether its use is transformative or, like Steve Jobs’ claims that the Segway would revolutionize transportation, not so much.
But what has become increasingly clear is that virtually the entire economy has been downstream of its growth. Here’s just how exponential the growth of spending on AI data centers has been:
The stock market has Boomed:
But the stock market Boom has been based almost exclusively on that AI spending:
And the wealth effect of that stock market Boom has led to accelerating spending by the affluent, as shown in Redbook’s weekly retail sales data:
And, as consumption leads employment, that spending has spread out to an increase in not just goods-producing jobs (orange, right scale), but broad service providing jobs (blue, left scale) as well:
Meanwhile, the spike in inflation has caused consumers, most of whom do not have much if any stock holdings, to dig deeper into their savings to a near record low:
In summary, if it weren’t for the Boom in AI related spending, it’s likely that consumer spending would be flat or even negative (remember that real average hourly wages have gone negative YoY, and real aggregate nonsupervisory payrolls have grown just barely in the past year):
In other words, the US economy would likely be in a recession right now.
That’s an awful lot of weight that is being borne by one small sector of the economy.
But I have come to conclude that, even if AI’s usefulness were to live up to its hype, there is one aspect that strikes me as clearly a bubble.
That’s because there are 10 or 20 companies all rushing to build out full-blown all-encompassing data centers. But almost certainly when it all shakes out, even under the best of circumstances there are likely to be only 2 or 3 left. All of the others – and their huge construction and usage footprint – are likely to vanish.
In other words, whether or not the AI Boom is like the dotcom bubble of 1999-2000, it is almost certainly like the browser wars of the 1990s, when there are a variety of providers like Alta Vista and Ask Jeeves, that all got eclipsed by Google and all but vanished from the scene.
And think of the auto industry. Early on there were dozens of manufacturers. But by the end of the second World War, there was one dominant company (GM), one secondary company (Ford) and one also-ran (Chrysler). In computer chips, there has been one dominant company (Intel) and one (until recently) also-ran (Micron). As Ron Insana pointed out, “In 1895, there w[ere] … 1,000 companies [that] made bikes as the new model of transport. By 1905, they were going out of business.”
Fortunately, I don’t have to write a more extensive piece, because it turns out someone else named Dan Wertman of Noetica/Thomson Reuters got there a short time ago, so I will quote them at length:
“Most people liken the AI boom to the dot com bubble. But the right comparison is the lesser-known portal wars. …
“Let’s go back to 1998. The internet had just gone mainstream, and a new kind of company was taking over the web: AltaVista, Excite, Lycos and Yahoo were each racing to become your home base online–the ‘interface’ to the internet. They competed on adding vertical workflows: features like news, email, weather and shopping. Venture capital poured in and they grew fast. For a moment, it looked like any one of them, or all of them, could win, each differentiating themselves in domains in which they were marginally better from the other.
Then a pair of Stanford graduate students created a new model, a search algorithm called PageRank, which used the web’s own link structure as a proprietary data signal. … [W]ithin a few years, PageRank became what we know as Google and every other portal had been rendered irrelevant.
“We are watching the same movie with AI startups today. Thousands of companies are building products on top of the same AI foundation models — OpenAI’s GPT, Google’s Gemini, Anthropic’s Claude – with no added proprietary content or data, only workflows, each aiming to be the “portal” for their vertical. They have different names, different user experiences, different pitches to investors. What most of them share is that the intelligence powering their product is available to every competitor, every established company, and increasingly to ordinary consumers at low or no cost because they’ve added nothing proprietary to enhance their offerings.”
It’s as if people build 20 Hoover Dams, when only 1 was needed. And the rest will ultimately sit idle – and probably fail.
So, dear reader, let me conclude. This aforementioned AI buildout, and that buildout (vs. whatever software value AI has) is all but certain to crash. When, and over what period of time, we do not know.
Hopefully not while the rest of the economy, as it is now, is downstream.
I hope the prediction on AI data centers that the majority will close down, which will save a lot of water in areas that have little spare water to begin with. course before they close the power grid will either be built out a lot (there is one that I am aware of that will need as much electricity as 300,000+ home in Houston. today, that power really doesn’t exist so somebody will have to convince power providers its worth billions of dollars and months of design and build time to upgrade and build new plants to provide that. and I saw that there are over 300+ data centers in Texas alone either proposed, planned or under construction already.
course i also suspect that some businesses will jump on AI as way to reduce employee head count (including some cases entire departments). curse if someone actually enables AI control of robots, not only the knowledge jobs but physical jobs will at some point at risk f disappearing. some AI supporters think that there are as many new jobs as there were of the old jobs, and employees can gravitate to the new jobs, but I don’t think that there are that many new jobs to begin with (as there isnt likely to new a lot of new industries showing up for employees to move on to. which then leads to the question who will buy anything as in the end the AI will do away with all most all jobs, and with jobs no one is buying much of anything at all
david:
Automation also reduces head count. CNC machinery does such. You still need a human on site to maintain it and adjust it when needed. Labor does not disappear. It can be minimized.
course with lots of big business salivating at AI’s impact in their labor force, those may jump a lot faster than others ill (leading to some overreaching and failing, and others (maybe smaller companies) taking their time to decide to jump in its the adoption rate in production that may take months or years depending on how fast adoption is rolled out across the economy, as this appears on what AI advocates push, could be complete in years not decades, and people don’t have time adapt to ‘new’ AI jobs (if any). then what?
also, its my understanding the worlds militaries are also focused on AI, and the ways the sharp end of the stick doesn’t require a human to operate effectively. which should cause concerns about how they operate as most tend to want to reduce casualties and deaths, as t makes for a bad look politically, for those who were all in on peace
david:
The best computer and most unpredictable one on the field in the military is a human. “Adapt implement, and overcome.” You can be taught the how to in the military but as the environment changes so should your strategy.
@Bill,
“as the environment changes so should your strategy.”
Success belongs not to the swiftest or the strongest but to the ones most adaptable to change.
Joel:
I do not disagree. Adaptable yes, and they must recognize when to change.