Fed study: AI’s slow productivity story fits a century-old historical pattern

New research from the Federal Reserve Bank of St. Louis, analyzing nearly 490,000 corporate earnings calls, confirms what official data has been showing for three years: Artificial intelligence has not yet produced a measurable bump in aggregate productivity. But one of the paper’s authors offered a more disquieting possibility—that AI may already be generating real gains that are structurally invisible, because AI itself is destroying the value of what it has made abundant.

The mechanism is simple. When AI makes some output radically cheaper to produce, that output simultaneously becomes less valuable, and the productivity math cancels itself: Gains in one column get erased by falling prices in another. Anyone can now generate marketing materials, animations, even a passable news story with a keystroke. But if everyone can, none of it commands what it used to. The task got easier; the output got cheaper. Somewhere in that trade, a real gain disappeared from the statistics without ever showing up as a loss.

“Some things are going to become more abundant,” said Serdar Ozkan, one of the paper’s authors. “That means they’re also going to become probably less valuable.”

Economists Ozkan and Aakash Kalyani, along with research associate Nicholas Sullivan, scanned roughly 490,000 earnings call transcripts from 5,198 publicly traded U.S. firms between 2000 and 2025, using an AI model to tag sentences about productivity and AI. The share of productivity commentary tied to AI rose from near zero before ChatGPT’s late-2022 debut to roughly 15% of all productivity discussion by the end of 2025.

Approximately 95% of AI-related productivity sentences describe gains executives expect in the future, not gains already realized, a share that........

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