From the article

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 discussions 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 has held steady since 2023. When executives do describe AI’s effect, they’re almost uniformly bullish: 95% describe productivity as rising, compared with 75% for non-AI commentary.

Researchers say this is exactly what history predicts.

Ozkan said he wasn’t surprised by the future-tense findings, since aggregate data already showed no meaningful bump in productivity once capital investment was accounted for. He invoked economist Robert Solow’s famous quip that “you can see the computer age everywhere but in the productivity statistics,” drawing a direct line to electrification; it took “several decades,” Ozkan said, to reorganize factories, retrain workers, and change workflows before its productivity payoff showed up in the data.

Stanford economist Erik Brynjolfsson called this the “productivity paradox” in a 1993 paper for MIT, and lately has taken to describing the current situation as the modern sequel.”

Researchers at the St. Louis Fed looked through 490,000 earnings calls and saw AI productivity surged—but only in talk.