The author argues that top executives at hyperscalers such as Amazon, Alphabet, Meta, Microsoft, and Oracle face asymmetric incentives that encourage them to continue hundreds of billions in data-center spending even if they privately doubt the returns, because admitting a major misallocation risks their jobs and reputations.

Responses from Gemini, Grok, and ChatGPT to an identical prompt all indicate that management would likely escalate commitment, reframe metrics, or delay recognition of losses rather than cut spending, citing sunk-cost psychology, career risk, and organizational inertia.

The piece draws parallels to agency problems in the housing bubble and notes that such dynamics can sustain investment booms until external pressure forces a reckoning.

First off, here are the latest numbers from the AI giants:

A couple of months ago, I decided to ask AI about the incentive structure facing asset managers at places like pension funds and hedge funds. The issue I raised was that these asset managers may face perverse incentives when it comes to investing in AI-related companies. These companies have been far outpacing the rest of the market over the last few years. This means that if they didn’t invest in them, their performance would badly lag their peers. That could cost them bonuses and even lead to their firing. On the other hand, if the AI-related stocks all plummet, they will get a “Who could have known?” amnesty, where they can avoid responsibility by saying that everyone made the same mistake.

In this scenario, AI agreed that asset managers would keep throwing money at the AI companies even if they believed that their growth model doesn’t make sense. This means that even if the asset managers had the exact same view I do of the prospects of the AI companies being record-setting profit makers, they would continue to invest in them. The incentives are totally asymmetric; keeping their job might mean ignoring their judgment and riding the wave.

Unfortunately, this is not the only case where a perverse incentive structure can lead to counter-productive behavior. The top executives at the hyperscalers — Amazon, Alphabet, Meta, Microsoft, and Oracle — may be in a similar situation.

At this point, all of them have committed hundreds of billions of their companies’ capital to building data centers to support the AI producers, primarily OpenAI and Anthropic. Suppose they came to hold the view that the AI companies would be unable to meet the trillions of dollars in lease commitments for which they are on the hook. This would mean that the hyperscalers would be sitting there with trillions invested in data centers for which they have no market.

From the standpoint of the companies, if they held this view of the future of AI, it would be best to cut their losses and stop building today. However, from the standpoint of the top executives at these companies, it would likely make more sense to just keep investing. After all, they can’t be sure; maybe AI will ultimately pay off.

However, if they were to pull the plug and try to cut their losses, they would be admitting that they threw hundreds of billions of dollars of their companies’ assets in the toilet. This would likely get them fired and probably end their career as a top executive of a huge tech company. In that scenario, they would likely keep building data centers even if they believed that they were throwing good money after bad.

This is the question I posed to AI. As I did last time, I posed the identical question to Gemini, Grok, and ChatGPT.

AI Says the Hyperscalers Will Keep Blowing Hundreds of Billions

I have posted my question and the answers verbatim, which you can read below, but the basic story is that AI agrees that the CEOs and other top execs might continue to throw good money after bad. As with my last question about the incentives of asset managers, I may have loaded the deck with my description of the incentive structure facing top management, but does anyone think I have mischaracterized it? What would happen to Satya Nadella at Microsoft or Sundar Pichai at Alphabet if they announced that they had been mistaken in investing hundreds of billions of dollars of their companies’ money in data centers, and they were prepared to write down the spending as a massive loss?

It may be a somewhat different story with Mark Zuckerberg at Meta, since he largely controls the company. After all, he owned up to an $80 billion loss on Metaverse and is still running the show. This may give Zuckerberg more freedom than the other top execs, but it’s not clear we should feel much confidence in his judgement.

These sorts of agency problems kept the housing bubble going as long as it did. Mortgage issuers were happy to issue mortgages to people who they knew were unlikely to be able to make payments, because they knew they could resell almost any mortgage, regardless of its quality, to the investment banks.

As part of the story, appraisers deliberately began giving inflated appraisals because they knew the issuers expected them. Most appraisers work as independent contractors. They knew that if they came in with an appraisal too low to allow a mortgage, they would be unlikely to be rehired.

The investment banks were happy to buy any mortgage they could get, because they knew they could package them into mortgage-backed securities (MBS). They could in turn count on getting investment-grade ratings from the credit rating agencies, because the investment banks were paying the credit rating agencies for their rating. The credit-rating agencies’ analysts understood that they were expected to come back with investment-grade ratings regardless of the quality of the security. This rating allowed the investment banks to sell their MBS all over the world.

Agency problems are common in capitalism. Markets should be structured to minimize them, but there is rarely a constituency to crack down on a specific abuse until it causes something really bad. And even then, the affected industry may delay action until everyone has forgotten about it. (Then Senator Al Frankenproposed an amendment to the Dodd-Frank financial reform bill that would have eliminated the conflict-of-interest problem with the credit rating agencies by having the SEC choose the agency hired for bond issues. While it passed the Senate with a huge bipartisan majority, Treasury Secretary Timothy Geithner had it killed in conference by imposing a two-year study period.)

Anyhow, after the AI bubble bursts, we may get some investigations into the agency problems that have allowed it to grow so dangerous. Until then, it will be business as usual.

Suppose the CEO and top management at a major hyperscaler had spent hundreds of billions of dollars on data centers. Although they think there is little likelihood that investing hundreds of billions more will pay off for the company, acknowledging their mistaken investment could mean getting fired and professional humiliation. What would they be likely to do?

Based on established corporate governance, psychological behaviors, and economic theory, top executives facing this dilemma are highly unlikely to admit the mistake immediately. Instead, they often engage in specific face-saving and risk-shifting behaviors to protect their positions.

Here is what management would likely do, ranked by probability:

1) Double Down on the........

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