Despite hopes for unlocking a new era soaring growth and abundance, AI has yet to manifest itself clearly in macro data, according to Apollo Chief Economic Torsten Slok.

In a note on Saturday, he recalled economist Robert Solow’s quip from the 1980s as PCs were transforming the economy: “You can see the computer age everywhere but in the productivity statistics.”

The same thing can be said today about AI, Slok wrote, noting that data on employment, productivity and inflation are still not showing signs of the new technology. Profit margins and earnings forecasts for S&P 500 companies outside of the “Magnificent 7” also lack evidence of AI at work.

“AI is everywhere except in the incoming macroeconomic data,” he said.

To be sure, investors are not waiting for AI to upend business models, and their fears have laid waste to the stock market recently.

As increasingly capable chatbots roll out, shares with exposure to wealth managers, insurance brokerages, tax preparation, accounting services, professional data, legal research, trucking, and logistics have sold off hard.

Meanwhile, AI evangelists see stunning economic gains. Anthropic CEO Dario Amodei said at the World Economic Forum last month that AI could boost GDP growth to 5%-10%.

And Elon Musk, cofounder of xAI, predicted AI will create so much wealth that working will be optional in the not-too-distant future.

But Slok is not yet convinced.

“Maybe there is a J‑curve effect for AI, where it takes time for AI to show up in the macro data. Maybe not,” he wrote on Saturday.

That will depend on the value creation from AI, Slok explained. So far, it’s playing out differently than the computer revolution did in the 1980s.

Instead of early innovators reaping monopoly pricing power until rivals erode that lead, fierce competition among large language model developers has driven their prices toward zero for end-users.

But from a macro perspective, the value AI creates is derived from how it’s used in the economy, not from a specific product, Slok said. So far, economists don’t foresee much impact, pointing for several studies.

The Penn Wharton Budget Model, for example, sees an annual gain in total factor productivity from AI amounting to just 0.1-0.2 percentage point, translating to a cumulative boost of 1.5% by 2035.

“After three years with ChatGPT and still no signs of AI in the incoming data, it looks like AI will likely be labor enhancing in some sectors rather than labor replacing in all sectors,” Slok said.

Similarly, the Congressional Budget Office has penciled in a relatively conservative view, estimating AI will add just 0.1 percentage point a year to total factor productivity growth and eventually boost output by 1 percentage point by 2036.