AI, Tech Stocks Drop For 4th Day Due To OpenAI IPO Halt, Inflation, Data Centers

As tech stocks sell off for the fourth day in a row it seems the markets are engaged in a titanic struggle between two opposing belief systems. On one side are those who still think 'this time is different,' meaning AI is going to be the most extraordinarily stupendifferous economic force in human and possibly universal history. 

They are now - some say, finally - coming up against those who are beginning to question whether the underlying assumptions about AI's ability to deliver results can ever be realized, especially given the inflationary and operational impact of expenditures on data centers and the rest of the proposed AI build-out. One could think of it as the hype caucus versus the sanity caucus. Jeff Bezos wondering aloud in a public interview why the US would possibly worry about human water needs versus AI's demand is evidence of the former. OpenAI suddenly suggesting it may postpone its IPO because a trillion dollar valuation is no longer achievable is evidence of the latter. That AI is inflationary, at least in the short term, is no longer in question. It is evidence of an historical pattern (NO! AI is like other eras?!) in which new technologies place higher demand on scarce resources. That may change - over time - but the looming question is whether the literally unheard-of demands for capital and materials can be borne by the companies assuming them, let alone the broader global economy. JL

Lee Shan reports in CNBC and Justin Lahart reports in the Wall Street Journal:

Tech stocks sold off (again today) amid mounting concerns over the rising cost of AI infrastructure. investor enthusiasm may also be capped by reports that OpenAI could delay its initial public offering until next year as it struggles to secure demand at a $1 trillion valuation as America’s massive AI build-out is beginning to push up prices on everything from smartphones to electricity. With so much demand, prices are rising for many of the things that go into the AI build-out. And because those things are used for more than AI, price increases are spilling over into the broader economy.  Memory and storage chips are used in a broad array of consumer-electronics products that includes everything from videogame consoles to cars. “In the first phase of any major tech revolution, you have a strain on limited resources, and that puts upward pressure on prices.”

Tech stocks sold off on Friday amid mounting concerns over the rising cost of artificial intelligence infrastructure.

U.S. semiconductor companies struggled in premarket trading. Intel shed just over 3%, Sandisk fell 4.74%, Arm lost 3.66% and Marvell dropped 3.29%.

In Europe, key chip stocks were also down as the market opened. ASML was down 0.83%, Infineon fell 2.96%, ASM International dropped 3.67%, ST Microelectronics shed 2.95% and Be Semiconductor was won 3.25%.

SoftBank Group, which plunged more than 12%, led losses across the region after the Nasdaq Composite fell for a fourth straight session overnight. The tech-heavy index dropped 0.46% as a 6% plunge in Apple overshadowed Micron’s stronger-than-expected earnings. 

The Japanese conglomerate could remain under pressure after its chip designer Arm Holdings fell 3.2% overnight, underperforming the broader semiconductor sector even as AI-related stocks rebounded sharply.

Andrew Jackson, an equity strategist at Ortus Advisors, said investor enthusiasm for SoftBank may also be capped by reports that OpenAI could delay its initial public offering until next year as it struggles to secure demand at a $1 trillion valuation.  

President Trump’s trade wars have waned. The price of gas is finally falling. But inflation has a new catalyst: America’s massive artificial-intelligence build-out is beginning to push up prices on everything from smartphones to electricity.

The question now is how widely that build-out might ripple through the economy, and how long it could keep inflation elevated. The answers will have big consequences for the economy.

The money pouring into the AI arms race is unprecedented. Analysts peg capital spending at five of the so-called hyperscalers—Alphabet, Amazon, Meta Platforms, Microsoft and Oracle—at $741 billion this year, according to FactSet, up nearly 75% from last year. 

Where is all that money going? While much of the conversation is focused on what AI can do, the build-out itself is strikingly physical, said Columbia University economist Stijn Van Nieuwerburgh.

The data centers used for AI require sophisticated computing equipment, cooling systems to keep that equipment from overheating, electric and fiber-optic cables and backup generators to prevent power disruptions. Based on announced and planned developments, Van Nieuwerburgh estimates that spending on the AI build-out through 2032 could come to about $8 trillion—nearly five times the market value of the entire New York City property market.

With so much demand, prices are rising for many of the things that go into the AI build-out. And because those things are used for more than just AI, those price increases are spilling over into the broader economy. 

Memory and storage chips, for example, are used in a broad array of consumer-electronics products that includes everything from videogame consoles to cars. Nintendo, Microsoft and Sony have all raised prices on devices. Higher price tags are coming to Apple products, too, according to Chief Executive Tim Cook, who told The Wall Street Journal that the jump in costs was unlike anything he had seen “in any area in over 40 years.”

If AI is as revolutionary as many economists predict, it could eventually cool inflation. That is the lesson from past technological revolutions, which boosted workers’ productivity, making it easier for businesses to meet demand without raising prices. Kevin Warsh, now the Federal Reserve chairman, has previously made that case.

“AI will be a significant disinflationary force, increasing productivity and bolstering American competitiveness,” he wrote in the Journal in November. Warsh’s read on the AI boom’s impact on inflation will be a first major test of his Fed leadership.

AI infrastructure could be built out far faster than past transformational technologies, like railroads in the 19th century, electrification in the early 20th century, or telecommunications during the dot-com boom. But it will take time to bear fruit.

Even under an accelerated timeline, economists at UBS reckon it will be at least a couple of years before AI would start helping to lower inflation. 

In the short term, demand powered by AI is leading to higher prices. In a National Association for Business Economics survey of economists released Monday, 81% of respondents said the AI build-out will add to inflation over the next year.

“In the first phase of any major technological revolution, you tend to have a strain on limited resources, and that tends to put upward pressure on prices,” said EY-Parthenon chief economist Gregory Daco, who is the president of NABE.

Already, this is beginning to show up in the inflation data. Consumer prices for computer software and accessories were up about 15% from a year earlier in May, according to the Labor Department. There could be more price increases in the pipeline: The Labor Department’s measure of wholesale electronic components and accessories was up 27% from a year earlier last month. The effect of the AI build-out on prices could be fundamentally different from either the tariffs that were put in place last year or this year’s jump in fuel prices, according to strategists at Evercore ISI. Both tariffs and oil are one-time shocks, temporarily making their way into price increases. AI is a shock to demand that could persist for years.

Indeed, much of that demand shock has yet to arrive: Fed governor Lisa Cook noted in a speech last month that only a small portion of announced spending on data centers has been put in place. The money that OpenAI and Anthropic expect to raise in their forthcoming initial public offerings could add even more fuel to the AI build-out.

That dynamic is reflected in the rally in the shares of chip stocks, which have moved sharply higher on investor expectations of sharply higher demand. Even with a sharp selloff this week, the PHLX Semiconductor Index is up about 150% over the past year.

Of course, more than just chips go into data centers. And like chips, a lot of the other things that go into building and running a data center are used widely across the economy. That could raise costs for a variety of businesses, which may then try to recoup those costs by charging consumers higher prices.

In some instances, the AI build-out could also add to labor costs. Wages for workers who are in demand from data-center construction have been picking up: Average hourly earnings for electrical and wiring-installation contractors were up 6.5% in April from a year earlier, which compared with 3.6% for all private-sector workers. 

And as new data centers come online, there is increased demand for electricity. Earlier this year, Goldman Sachs economists forecast that data centers will account for nearly half of U.S. growth in power demand through 2030. As a result, they saw consumer electricity prices rising about 6% annually this year and next. 

To be sure, economists don’t foresee the AI build-out fueling anything like the inflation surge the U.S. experienced when the economy reopened following the Covid-19 crisis. Items like smartphones and videogames represent just a tiny fraction of what people spend every year. Even electricity accounts for only about 2.5% of consumer spending, according to the Labor Department.

Instead, it could serve to keep inflation broadly elevated. Economists expect the May reading of the Fed’s preferred measure of inflation, due out from the Commerce Department on Thursday, will show prices were 4.1% higher than a year earlier. The central bank aims to get inflation to 2%—a level not seen in over five years, as a series of temporary-seeming factors pushed prices higher.

“The more these things happen, the more likely it is that people think, ‘Hey, this is a pattern, maybe I shouldn’t expect inflation to come back down,’” said Jón Steinsson, an economist at the University of California, Berkeley.