$250 Billion in AI Spending, So Why Isn't It in the Data?

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Hello, dear reader. This is Oswarld’s Knowledge Talking.

These days, AI is everywhere you look. Turn on the news — AI. Sit through a company meeting — AI. Open an investment report — AI. So a recent headline from The Economist caught my eye: “The AI productivity boom is not here (yet).” Between 2024 and 2025, companies around the world poured more than $250 billion into AI — roughly ₩350 trillion in Korean currency terms. And yet Torsten Slok, chief economist at Apollo, put it this way: “You can see AI everywhere except in the macroeconomic data.”

That line matches word for word something someone said 40 years ago, and that’s what I want to dig into today. If we’re pouring this much money into AI, why isn’t it showing up in the economic indicators?

The Ghost of Solow: The Same Question, 40 Years Ago

In 1987, Nobel laureate economist Robert Solow wrote a now-famous line in a New York Times book review: “You can see the computer age everywhere but in the productivity statistics.” From the 1960s through the 1980s, transistors, microprocessors, and memory chips advanced at an explosive pace, and PCs started showing up in every office. But something strange happened. US productivity growth fell from an average of 2.9% a year between 1948 and 1973 to just 1.1% after 1973. Extraordinary technology had arrived — and productivity growth had been cut roughly in half.

This phenomenon became known as the “Solow Paradox” — technology is clearly advancing, yet it doesn’t show up in the economic data. And in 2025, economists are watching AI trace exactly the same pattern.

There’s an important concept here: general-purpose technology (GPT)¹. It refers to technologies like the steam engine, electricity, and the computer — technologies that ripple through the entire economy. What they have in common is a broad range of application, continuous improvement over time, and a wave of further innovation that follows in their wake. AI fits squarely into this category.