You’ve probably heard about the nationwide data center building boom, the hype about artificial intelligence and Republican plans to make Pennsylvania a data center/AI hub. A closer look indicates that this boom may soon become a bust, with a negative impact on our nation’s economy.

 
Harris Kupperman, founder of hedge fund Praetorian Capital, called that gulf between tech industry spending and actual revenue in 2025 “astonishing.” However, it doesn’t even begin to scratch the surface. For example, how does it all shake out when we account for 2026, when hundreds of new data centers are expected to pop up?

“Adding the two years together, and using the math from my prior post, you’d need approximately $1 trillion in revenue to hit break even, and many trillions more to earn an acceptable return on this spend,” he writes.

“If the economics don’t work, doing it at massive scale doesn’t make the economics work any better — it just takes an industry crisis and makes it into a national economic crisis,” he concludes.

Overall, the pessimists broadly agree: it’s no longer a matter of if AI is massively overhyped, but when the whole thing comes crashing down.

Read the full article in Futurism

 
Artificial intelligence might be booming on paper, but in the real world, there are signs of a major slowdown.

In their latest biweekly survey of AI adoption, the US Census Bureau found evidence of an obvious drop-off in corporate AI use — the largest since the survey began in November of 2023.

In perhaps the most telling sign, companies that had previously laid off or stopped hiring flesh and blood workers are now scrambling to refill their ranks, realizing the tech is nowhere near as capable as the hype made it out to be.

Unless enterprise AI can flip a switch and start earning its keep, the latest drop-off in AI usage could just be the start of a steep slope toward the bottom.

Read the full article in Futurism

 
The extraordinary rise in US technology stocks over recent years and the correction so far into 2025 have investors drawing parallels to the tech bubble burst 25 years ago. However, Goldman Sachs Research points out that there is a critical difference between the dominant tech companies of today and those that were part of the tech bubble in 2000: their valuations.

The tech bubble was primarily driven by exuberance around the commercialization of the internet, with the Nasdaq index increasing fivefold between 1995 and 2000. Within one month of the bubble bursting in March 2000, the Nasdaq index had lost over a third of its value, writes Goldman Sachs Research’s Chief Global Equity Strategist Peter Oppenheimer in a recent report.

In comparison, the big tech companies today are valued at less extreme levels and the fundamentals of the tech sector are stronger. Oppenheimer doesn’t believe the current tech stocks are in a bubble, but he says we can still learn valuable lessons from history.

Today’s speculation over artificial intelligence (AI) shares some similarities with the dot-com tech bubble – both driven by major tech innovations. One academic study, in a sampling of 51 major innovations introduced between 1825 and 2000, found that bubbles in equity prices existed in 73% of the cases. These bubbles grew when the innovation was more radical and publicly visible at the time of commercialization.

Oppenheimer believes the challenge, both now and then, is figuring out how to value the new innovation and identifying who will benefit the most (or lose the most). Bubbles form when the total value of companies involved in the innovation becomes much higher than the future potential cash flows they are likely to generate.

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