Big Tech Thinks AI Underspending Riskier Than Overspending. Investors Are Dubious

We're back in 'but this time it's different' mode. Again. 

Alarm bells should - and are - going off about projections that, to be polite (and not get flamed by politically connected billionaires) are being called 'challenging.' Fortunately, there are enough smart people working for companies with functional institutional memories raising questions that, at least in a growing number of cases, the proverbial brakes are being tapped. But Big Tech, many VCs and others with a stake in the hype are angrily dismissing concerns - even as a growing number of analysts are pointing out that the entire economy is being driven by a build-out whose capacity may never be utilized. And, as investors are becoming more prudent, the AI hypesters are simply turning to debt financing rather than pulling back. Which means the entire economy is at risk, the theory evidently being that it's better to be bankrupt than accused of 'not getting it.' JL

Asa Fitch reports in the Wall Street Journal:

It has become a tech-industry truism: Spending too little on chips and other infrastructure for AI is riskier than spending too much. But investors have begun questioning this logic, fretting that the spending might inflate a bubble that will inevitably pop. Spending too much can be very bad. Ask Intel. If it waited for demand for its chips to materialize before building, it couldn’t capitalize on their success. So Intel paid for manufacturing expansion before the returns on those investments were there. It has been a disaster. A similar dilemma faces today’s AI players: they believe they can’t wait for AI’s business to be proven before investing. (But) large financial commitments to AI projects might no longer make sense, becoming a burden for years to come. If assumptions about the value of AI-related assets and contracts change, write-downs are also inevitable. A lot of startups could fail. 

It has become a tech-industry truism: Spending too little on chips and other computing infrastructure for artificial intelligence is riskier than spending too much.

As OpenAI Chief Executive Sam Altman recently put it, people can either overinvest and lose money or underinvest and lose revenue. Or as Meta Platforms chief Mark Zuckerberg said on a call with analysts after it reported earnings last month, AI’s promise as a revenue driver meant “we want to make sure that we’re not underinvesting.”

But investors have begun questioning this logic, fretting that the spending spree might be inflating a bubble that will inevitably pop. Indeed, spending too much can be very bad. Just ask Intel. 

The storied American chip maker faced a similar spending decision—albeit under different circumstances—not long ago.

Having fallen behind rivals in Asia in the race to make cutting-edge semiconductors, Intel brought in Pat Gelsinger as chief executive in 2021 to engineer a turnaround. Gelsinger laid out a strategy to leapfrog those rivals while also becoming a leading contract chip maker. To succeed, the plan would require Intel to vastly expand its chip-manufacturing capacity.

But chip factories cost tens of billions of dollars each and take years to build. So Intel had to splash out on the manufacturing expansion before the returns on those investments were there.

If Intel waited for demand for its cutting-edge chips to materialize before building, it couldn’t capitalize on their success. A similar dilemma faces today’s AI players: they believe they can’t wait for AI’s business potential to be proven before investing.

 

So Intel plowed ahead. It had the financial chops to do it, too, with a fairly healthy balance sheet and more than $21 billion of free cash flow the prior year. Capital expenditures ballooned from about $14 billion in 2020 to $25 billion in 2022.

“We are overinvesting,” Gelsinger said at a Credit Suisse conference in late 2021, calling the move “a very conscious decision to get back in front of it.”

That may have been the correct move for Intel in its circumstances then. But technological missteps and changed circumstances in the chip market undercut the effort within a couple of years. 

The result has been nothing short of a disaster. Manufacturing projects have been put on hold or canceled. The company has been bleeding cash with free cash flow in negative territory in all but three of its last 14 quarters.

Intel has sold assets to raise money, unloading part of its stake in self-driving car-technology company Mobileye and divesting a majority of its programmable-chip business to private-equity firm Silver Lake. It laid off thousands of employees to save money. The company suspended its dividend. Gelsinger was ousted. It increasingly looks like Intel may need to be split up to get back on track.

 

With its stock plummeting, the U.S. government took a 10% stake in Intel in August. That gave its shares a boost, but the company is valued now at around $171 billion—roughly 1/26 the valuation of AI chip giant Nvidia. Intel was worth more than Nvidia five years ago.

A similar—if not worse—reckoning could easily be in store for companies that are splashing out on AI, should demand fail to materialize in the way they envision.

Large financial commitments to AI data-center projects might no longer make sense, becoming a burden for tech companies for years to come. If assumptions about the value of AI-related assets and contracts change, write-downs are also inevitable. A lot of startups could fail.

Investors have recently expressed trepidation about returns on big AI investments. That has sent AI-related stocks on a bumpy ride the past few weeks. Things will undoubtedly look a lot gloomier in markets if tech’s penchant for overspending becomes a definitive miscalculation.

But Intel’s experience also illustrates that companies can muddle through a period of overspending. While Intel has been substantially weakened, it is far from bankrupt.

 

And the largest of the big-spending tech companies—Microsoft, Alphabet and Amazon.com—are in good financial shape, even if their spending has begun to hurt them.

Alphabet, Google’s parent, has been particularly shrewd. It has leveraged its search-engine dominance to gain a step on competitors in AI while not breaking the bank with capital spending. Its planned capital expenditures this year amount to only 23% of projected revenue—well below that of peers.

Other companies that have leveraged up to spend on AI or have few other business ventures are more vulnerable. Those companies—like Oracle, CoreWeave and to some extent Meta—might have to make moves like Intel if AI’s returns don’t end up justifying their investments.