OpenAI's chief economist studied whether companies love ChatGPT. The data was ChatGPT's.
The paper is more careful than its marketing: honest hedges, real scale, and a dataset no researcher outside the company can touch.
"OpenAI's working paper 'How Organizations Use AI: Evidence from ChatGPT' documents rapid enterprise adoption across 1,500+ organizations and 17M+ messages, with adoption concentrated in larger, R&D-intensive firms and heaviest use among early-career workers." [SOURCE ↗]

THE CLAIM. a working paper from OpenAI's chief economist and coauthors at Columbia and Wharton documents enterprise AI adoption using ChatGPT Enterprise records: usage growing fast, adoption concentrated among larger, more valuable, R&D-intensive firms, and early-career workers using it hardest, across 1,500+ organizations and 17 million messages.
THE CHECK. the paper itself is the careful member of the family. It says its estimates describe conditional associations and should not be interpreted causally, covers only OpenAI's own product, and admits its job-title data is incomplete. The structural problem survives the hedging: the evidence is OpenAI's logs, analyzed by OpenAI, with no external access for auditing, and the sample is by construction OpenAI's paying customers. Meanwhile the companion marketing already converts the caution into momentum: token shares 'suggesting substantive, delegated work' and thirty-minutes-versus-two-weeks anecdotes.
OpenAI's chief economist Aaron Chatterji and coauthors including Berkeley-and-Columbia-affiliated David Holtz posted a working paper, now on arXiv, linking ChatGPT Enterprise account records to usage data, worker roles, message-level task classifications, and public-company financials through March
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