Tech giants like Microsoft and Google are outsourcing more and more coding to AI in a productivity push.

But some new research shows the tools might not be as helpful as some expect.

Drew DeBos is digging into that for today's tech check.

Happy Friday, Dee.

Happy Friday. Good morning, Carl.

So this is some cold water poured on the AI productivity hype.

Researchers at Meter, which is an AI nonprofit research firm, ran a real-world trial and found that seasoned engineers were actually 19% slower when using AI tools like cursor.

Instead of speeding them up, the AI often gave

suggestions that looked helpful but actually required time-consuming corrections. Now, this undercuts

a core Wall Street narrative, that AI will supercharge white-collar efficiency and unlock a wave

of productivity gains across the enterprise. Instead, the study suggests that the return on AI coding,

it may be more and even less immediate than investors have priced in.

Now, there is some nuance here.

Prior studies from meter have shown a more straightforward benefit

to junior engineers from AI tools,

particularly for simpler, well-scoped tasks. Now, this latest suggests

that while it can help that group level up, it may actually be increasing reliance on senior

talent because someone still needs to debug, refine, and ship the final product. So that helps

explain the current talent wars, where Zuckerberg is throwing $100 million offers at top AI

engineers. They're more essential than ever. Meanwhile, new data shows that AI adoption appears to be

stalling more broadly. Ramp, this is a platform that tracks enterprise software spend. It shows that

paid AI tool usage was flat at about 40% after a very steep run-up over the past year.

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