Saturday Aug 1
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Fed Study Finds No AI Productivity Bump

1AUG
WHERE DID IT GONO BUMPSHRINKS

AI's productivity payoff may be invisible, not absent. St. Louis Fed researchers scanned 490,000 earnings calls and found no AI productivity bump. AI may make output too cheap to count as a gain.

Economists tagged AI mentions across 490,000 calls from 2000 to 2025. Ninety-five percent of the claims describe future gains, not ones already booked.

Researcher Serdar Ozkan says AI may be destroying the value of what it makes abundant, so gains cancel against falling prices. He compares it to electrification, which took decades to reorganize factories before paying off.

Firms talking up AI have also raised R&D and capex spending, not just their language. Nobody yet knows which use case will make the gains show up in the numbers.

full brief & sources

⚡ Why this matters

  • Directly tests the biggest open question in enterprise AI spend: is it actually working?
  • Offers a real explanation for why AI ROI still looks thin in the official numbers.
  • Matches other 2026 Fed research finding gains concentrated in a few industries, not broad-based.

🔍 What happened

  • St. Louis Fed economists scanned roughly 490,000 earnings calls from 5,198 public companies.
  • AI's share of productivity commentary rose from near zero before ChatGPT to about 15% by late 2025.
  • 95% of AI productivity claims describe expected future gains, not gains already realized.
  • When executives do describe AI's effect, 95% call it positive, versus 75% for non-AI topics.
  • Researcher Serdar Ozkan says AI's abundance effect may cancel real gains against falling prices.
  • Firms talking up AI have also raised R&D and capex spending, not just their language.

💬 Smart takes

  • Serdar Ozkan, St. Louis Fed: "Some things are going to become more abundant. That means they're also going to become probably less valuable."
  • Aakash Kalyani, St. Louis Fed: the profession trusts what firms do, not what they say, and the actions now match the optimistic talk.
  • Skeptic: a theory that explains away every disappointing data point is hard to disprove and easy to lean on indefinitely.

🧭 Where this goes

  1. Likely2027 earnings calls show an even higher share of AI productivity commentary.
  2. Likelyofficial productivity data stays flat through next year regardless of AI capex levels.
  3. Possibleone specific AI use case breaks out and shows up clearly in sector-level data first.
  4. Wild Cardeconomists later revise history and credit 2026 as the actual inflection point, missed in real time.

🥄 The Spoon Take

Every CFO says AI is paying off, and the data says otherwise. Both can be true if AI's biggest trick is making things too cheap to count as gains. That's not proof AI is a bust. It's proof the scoreboard might be broken.

🤔 Pushback

This theory is unfalsifiable in the short run. Any flat productivity number can be waved away as invisible abundance.

·Fortune - Fed AI productivity study·St. Louis Fed - AI productivity research·Kansas City Fed - Productivity chapter