It really is possible to spend too much on AI

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.

- Asa Fitch

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.