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How Organizations Use AI: Evidence from ChatGPT

Author

Listed:
  • Aaron Chatterji
  • David Holtz
  • Neel Rakholia
  • Prasanna Tambe
  • Gawesha Weeratunga

Abstract

We study how organizations use frontier generative AI by linking ChatGPT Enterprise account records to usage, worker roles, task classifications, and public-company financial data through March 2026. These linked data enable a privacy-preserving analysis of adoption, worker roles, and message-level tasks at scale: for instance, the worker-level sample we analyze at the six-month adoption horizon includes over 1,500 organizations and over 17 million messages. We document four facts about enterprise AI adoption and use. First, ChatGPT Enterprise usage has grown rapidly due to a combination of new firm adoption and growing intensity among existing adopters. Second, U.S.-based public company adoption is concentrated among larger, more valuable, and more R&D- and SG&A-intensive firms. Third, active use within adopting firms spans job functions and seniority levels, with especially high usage intensity among early-career workers. Fourth, ChatGPT Enterprise usage encompasses a broad range of knowledge work tasks, including writing, technical work, communication, and information synthesis. In aggregate, these results suggest that firms differ widely in the speed, breadth and purpose of their enterprise AI adoption, and that they are still actively learning how to integrate AI into organizational workflows.

Suggested Citation

  • Aaron Chatterji & David Holtz & Neel Rakholia & Prasanna Tambe & Gawesha Weeratunga, 2026. "How Organizations Use AI: Evidence from ChatGPT," Papers 2608.12236, arXiv.org.
    • Handle: RePEc:arx:papers:2608.12236
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    References listed on IDEAS

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    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Timothy Bresnahan, 2024. "What innovation paths for AI to become a GPT?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 305-316, March.
    3. Ruth Appel & Peter McCrory & Alex Tamkin & Miles McCain & Tyler Neylon & Michael Stern, 2025. "Anthropic Economic Index report: Uneven geographic and enterprise AI adoption," Papers 2511.15080, arXiv.org.
    4. Fuentelsaz, Lucio & Gomez, Jaime & Polo, Yolanda, 2003. "Intrafirm diffusion of new technologies: an empirical application," Research Policy, Elsevier, vol. 32(4), pages 533-551, April.
    5. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    6. Kiran Tomlinson & Sonia Jaffe & Will Wang & Scott Counts & Siddharth Suri, 2025. "Working with AI: Measuring the Applicability of Generative AI to Occupations," Papers 2507.07935, arXiv.org, revised Dec 2025.
    7. Bresnahan, Timothy F. & Trajtenberg, M., 1995. "General purpose technologies 'Engines of growth'?," Journal of Econometrics, Elsevier, vol. 65(1), pages 83-108, January.
    8. Goldfarb, Avi & Taska, Bledi & Teodoridis, Florenta, 2023. "Could machine learning be a general purpose technology? A comparison of emerging technologies using data from online job postings," Research Policy, Elsevier, vol. 52(1).
    9. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    10. James M. Brand & Mert Demirer & Connor Finucane & Avner A. Kreps, 2024. "Firm Productivity and Learning with Digital Technologies: Evidence from Cloud Computing," NBER Working Papers 32938, National Bureau of Economic Research, Inc.
    11. Nicholas Bloom & Luis Garicano & Raffaella Sadun & John Van Reenen, 2014. "The Distinct Effects of Information Technology and Communication Technology on Firm Organization," Management Science, INFORMS, vol. 60(12), pages 2859-2885, December.
    12. Fabrizio Dell’Acqua & Edward McFowland & Ethan Mollick & Hila Lifshitz & Katherine C. Kellogg & Saran Rajendran & Lisa Krayer & François Candelon & Karim R. Lakhani, 2026. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality," Organization Science, INFORMS, vol. 37(2), pages 403-423, March.
    13. Luis Garicano, 2000. "Hierarchies and the Organization of Knowledge in Production," Journal of Political Economy, University of Chicago Press, vol. 108(5), pages 874-904, October.
    14. Scott Counts & Yan Chen & Jing Dong & Himanshu Sharma & Andrey Zaikin & Rui Hu & Alperen Kok & Gorkem Ozer Yilmaz & Siddharth Suri & Kiran Tomlinson & Sonia Jaffe & Will Wang, 2026. "AI in the Enterprise: How People Use M365 Copilot Chat," Papers 2605.23958, arXiv.org.
    15. Luis Garicano & Esteban Rossi-Hansberg, 2006. "Organization and Inequality in a Knowledge Economy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(4), pages 1383-1435.
    16. Timothy F. Bresnahan & Erik Brynjolfsson & Lorin M. Hitt, 2002. "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(1), pages 339-376.
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