Goldman economist offers a reality check on AI adoption: it took 15 years for computers to really show up in the data

Are you feeling a little underwhelmed by AI’s transformation of the economy? The so-called “fifth industrial revolution” is supposed to wipe out half or even all of white-collar work and yet adoption is kind of begrudging, even optional for many workers. For those who have started using it, it kind of feels like homework a lot of the time—it writes your emails for you, but it’s still wrong a lot of the time. Three and four decades ago, the computer revolution was similarly hyped, and yet for a lot of the time, it looked more like Pets.com than what turned into the iPhone.

That’s the angle taken by Goldman Sachs’ Elsie Peng, who looked closely at the productivity uptick from the computing revolution in a research note for the bank earlier this month. The last time something this big came along, she wrote, things actually got measurably worse before they got better—for four years, by her reckoning. Then they flatlined for another four. Only in year eight did gains from computing become statistically significant. The productivity boom everyone associates with the personal computer didn’t actually show up in the macro data until 15 years after the PC was commercialized.

Goldman’s official view is still that AI will “meaningfully boost productivity growth over the next decade.” What Peng is arguing is that the AI boom’s boosters — and a lot of investors pricing that boom into equities — may be badly miscalibrated on timing. And the reason why, she finds, has less to do with the technology than with the humans being asked to use it.

The J-curve nobody mentions

The PC was commercialized in 1981. By the early 1980s, investment in information and communications technology was rising sharply across most industries. And yet the productivity trend was flat until the late 1990s.

Peng’s industry-panel analysis finds that the productivity impact followed what she calls a J-curve: a modest drag for the first four years, statistically significant gains only after eight, and a peak impact of roughly 0.6 percentage points in year 12. If ChatGPT’s 2022 launch is the equivalent of the PC’s 1981 debut, that J-curve puts the productivity payoff arriving around 2030 at the earliest, and peaking around 2034.

Three forces created the lag the first time. Key components such as semiconductors and telecom equipment........

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