How People Use ChatGPT - NBER Working Paper

Aug 30, 2026

Uploaded by Finn

Despite rapid adoption of LLM chatbots, little is known about actual usage patterns. The study tracks ChatGPT’s consumer product growth from launch in November 2022 to July 2025, when adoption reached about 10% of the world’s adult population. Using privacy-preserving automated classification of a representative sample of conversations, the paper finds faster growth in non-work messages and identifies dominant conversation topics such as Practical Guidance, Seeking Information, and Writing.

LanguageEnglish

CategoryResearch & Report

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Pages64

Reading Time2 h 41 min

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Abstract

Introduction

NBER WORKING PAPER SERIES HOW PEOPLE USE CHATGPT Aaron Chatterji Thomas Cunningham David J. Deming Zoe Hitzig Christopher Ong Carl Yan Shan Kevin Wadman Working Paper 34255 [http://www.nber.org/papers/w34255](http://www.nber.org/papers/w34255) NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 September 2025 We acknowledge help and comments from Joshua Achiam, Hemanth Asirvatham, Ryan Beiermeister, Rachel Brown, Cassandra Duchan Solis, Jason Kwon, Elliott Mokski, Kevin Rao, Harrison Satcher, Gawesha Weeratunga, Hannah Wong, and Analytics & Insights team. We especially thank Tyna Eloundou and Pamela Mishkin who in several ways laid the foundation for this work. This study was approved by Harvard IRB (IRB25-0983) . A repository containing all code run to produce the analyses in this paper is available on request. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed additional relationships of potential relevance for this research. Further information is available online at [http://www.nber.org/papers/w34255](http://www.nber.org/papers/w34255) NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2025 by Aaron Chatterji, Thomas Cunningham, David J. Deming, Zoe Hitzig, Christopher Ong, Carl Yan Shan, and Kevin Wadman. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. How People Use ChatGPT Aaron Chatterji, Thomas Cunningham, David J. Deming, Zoe Hitzig, Christopher Ong, Carl Yan Shan, and Kevin Wadman NBER Working Paper No. 34255 September 2025 JEL No. J01, O3, O4 ABSTRACT Despite the rapid adoption of LLM chatbots, little is known about how they are used. We document the growth of ChatGPT’s consumer product from its launch in November 2022 through July 2025, when it had been adopted by around 10% of the world’s adult population. Early adopters were disproportionately male but the gender gap has narrowed dramatically, and we find higher growth rates in lower-income countries. Using a privacy-preserving automated pipeline, we classify usage patterns within a representative sample of ChatGPT conversations. We find steady growth in work-related messages but even faster growth in non-work-related messages, which have grown from 53% to more than 70% of all usage. Work usage is more common for educated users in highly-paid professional occupations. We classify messages by conversation topic and find that “Practical Guidance,”“Seeking Information,” and “Writing” are the three most common topics and collectively account for nearly 80% of all conversations. Writing dominates work-related tasks, highlighting chatbots’ unique ability to generate digital outputs compared to traditional search engines. Computer programming and self-expression both represent relatively small shares of use. Overall, we find that ChatGPT provides economic value through decision support, which is especially important in knowledge-intensive jobs. Aaron Chatterji Duke University Fuqua School of Business and OpenAI [ronnie@duke.edu](ronnie@duke.edu) Thomas Cunningham OpenAI [tom.cunningham@gmail.com](tom.cunningham@gmail.com) David J. Deming Harvard University Harvard Kennedy School and NBER [david_deming@harvard.edu](david_deming@harvard.edu) Zoe Hitzig OpenAI and Harvard Society of Fellows [zhitzig@g.harvard.edu](zhitzig@g.harvard.edu) Christopher Ong Harvard University and OpenAI [christopherong@hks.harvard.edu](christopherong@hks.harvard.edu) Carl Yan Shan OpenAI [cshan@openai.com](cshan@openai.com) Kevin Wadman OpenAI [kevin.wadman@c-openai.com](kev

FAQs

How does the paper measure how people use ChatGPT?

It uses a privacy-preserving automated pipeline to classify usage patterns within a representative sample of ChatGPT conversations, including message topics and whether they are work-related.

What does the study find about work versus non-work usage growth?

Work-related messages grow steadily, while non-work messages grow even faster, increasing from 53% to more than 70% of all usage by July 2025.

Which conversation topics are most common in the analysis?

The paper finds that “Practical Guidance,” “Seeking Information,” and “Writing” are the three most common topics, together accounting for nearly 80% of all conversations.

Aug 30, 2026

Uploaded by Finn

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