Via theceopublication.com
The Chicago Fed president says persistent weak productivity data would challenge the rosy assumptions baked into markets and monetary policy alike
Austan Goolsbee, President and CEO of the Federal Reserve Bank of Chicago, is sounding the alarm on a disconnect that could matter a lot more than the latest quarterly earnings from your favorite AI chipmaker. Recent productivity readings have come in weak, and if that trend sticks, Goolsbee says the entire AI-driven growth narrative could need a rewrite.
The productivity paradox, AI edition #
For a while, the data was cooperating with the AI bulls. US productivity growth since late 2022 had been running hot, often 75 basis points to a full percentage point above the trajectory that prevailed before COVID. That was a meaningful acceleration, and it gave credibility to the idea that generative AI tools and related technologies were starting to pull their weight in the real economy. Goolsbee himself acknowledged this trend in multiple speeches dating back to at least February 2025. He wasn’t dismissing the potential of AI. He was, in fact, among the more nuanced voices at the Fed when it came to parsing whether those gains were structural or just noise.
But recent readings have flipped the script. Productivity numbers have deteriorated, and Goolsbee is now warning that a persistent decline would fundamentally alter how policymakers and markets should think about the AI story.
Why front-running AI gains is dangerous #
Goolsbee’s concern goes beyond disappointing data prints. He’s flagging a specific mechanism that could make things genuinely ugly: front-running. Companies and governments have been ramping up spending on AI infrastructure at an extraordinary pace, operating on the assumption that productivity gains will follow. If those gains don’t show up, or show up much later than expected, all that spending becomes inflationary rather than productive. You get the demand-side effects of investment without the supply-side payoff.
Goolsbee has been explicit about this risk. Over-anticipating productivity improvements could create conditions that resemble stagflation, where growth stalls but inflation stays elevated.
The distinction Goolsbee draws is subtle but important. A productivity shock that the economy has already anticipated, one that’s baked into spending plans and asset prices, carries very different policy implications than one that arrives as a surprise.
What this means for markets and monetary policy #
For anyone watching the Fed, Goolsbee’s remarks offer a useful lens for interpreting future policy signals. If productivity data continues to weaken, the case for keeping rates elevated gets stronger, not weaker. That runs counter to the widespread expectation that AI-driven efficiency gains would eventually give the Fed room to ease. Goolsbee’s framing also carries implications for inflation expectations. If the market’s inflation outlook has been anchored partly by faith in AI productivity gains, and that faith erodes, inflation expectations could drift higher.
It’s worth noting that Goolsbee isn’t declaring the AI productivity story dead. He’s saying the evidence needs to catch up with the enthusiasm. The gap between what AI is expected to deliver and what the data currently shows is wide enough to warrant caution.
Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our