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The Efficiency Trap Inside Corporate A.I. Spending

As companies like Meta and Coinbase cut jobs to fund A.I. expansion, they may be weakening the very organizational conditions innovation depends on.

When Meta cut 8,000 employees in April and framed it explicitly as an investment in artificial intelligence, it joined a growing list of highly profitable companies trading headcount for computing. Coinbase followed weeks later, cutting around 14 percent of its workforce, citing market volatility and the proliferation of A.I. tools in the same breath.

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The direction of travel is understandable. The economics of A.I. are real, the competitive pressure is real and at some point, every company with serious A.I. ambitions will have to make tough capital allocation decisions in the face of these realities.

What is less clear is whether the approach some companies are taking is wise. There is, for instance, a clear transatlantic split in the speed and scale of this reallocation, with U.S. firms in particular appearing willing to move more aggressively, cutting deeper and faster. The bets being made are large. And some of the risks attached to them are genuinely hard to foresee. But at least two of them are entirely predictable, and neither is getting nearly enough attention.

The first concerns what happens to organizations when they strip out capacity in the name of efficiency. The word itself is doing a lot of work in these announcements. Because........

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