OpenAI Signals: ChatGPT Work Usage Data Across 165 Work Activities and Nearly 100 Countries
OpenAI released OpenAI Signals data that maps how consumers use ChatGPT for work across 165 work activities and nearly 100 countries, with quarterly coverage spanning Q1 2025 through Q3 2026. The headline finding is that work-related ChatGPT use became less concentrated in the most common activities: across 74 countries observed in every quarter, the ten most common activities represented an average of 51.1% of each country's classified work messages in Q3 2026, down from 56.0% in Q1 2025.
Key numbers at a glance
- 165 work activity categories, called Intermediate Work Activities (IWAs), are used to classify work-related ChatGPT use.
- Nearly 100 countries are covered by the release.
- 74 countries were observed in every quarter of the dataset.
- The data is represented quarterly and spans the first quarter of 2025 through the third quarter of 2026.
- The ten most common activities represented an average of 51.1% of each of those 74 countries' classified work messages in Q3 2026, down from 56.0% in Q1 2025.
- About 43% of the employment-weighted task mix for mapped U.S. occupations falls into "Other" IWAs, outside the individually reported categories.
What OpenAI released
OpenAI published OpenAI Signals data that explores 165 work activities across nearly 100 countries, revealing how consumers use ChatGPT for work. The release is positioned as a research resource: it gives researchers a new way to study AI's role in the economy, with new information on the work activities people bring to ChatGPT, from preparing instructional materials and developing marketing content to programming and analyzing business data.
The data connects ChatGPT usage to 165 work activity categories called Intermediate Work Activities (IWAs). IWAs are commonly used categories of tasks for the kinds of work people do across occupations. The dataset is represented quarterly and spans a period from the first quarter of 2025 through the third quarter of 2026.
OpenAI states that researchers can use this data to explore how ChatGPT use for work differs across countries, track changes over time, and match this data to other economic indicators.
Why IWAs and O*NET matter for comparability
The OpenAI Signals work data draws on O*NET, a standardized framework that groups occupation-specific tasks into broader categories of work activities shared across occupations. Using a common framework helps researchers compare ChatGPT use with other types of occupational and employment data.
That design choice is what makes the dataset joinable to employment statistics and other economic indicators rather than being a standalone usage report. The classification layer, not just the raw usage counts, is the part OpenAI is offering to outside researchers.
The core finding: work-related use became less concentrated
Connecting the data to IWAs revealed that work-related use became less concentrated in the most common activities. In OpenAI's framing, that means countries tended to specialize in their work over time, and different countries specialized in different types of work.
Across 74 countries observed in every quarter, the ten most common activities represented an average of 51.1% of each country's classified work messages in Q3 2026, down from 56.0% in Q1 2025.
OpenAI notes that these differences might reflect variation in the kind of work done across countries or varying access to AI tools. OpenAI presents exploring these questions as one example of many that researchers can pursue with this new data.
Country-level variation and the interactive explorer
The release includes an interactive chart for exploring work activities within a specific country over time, moving from broad activity groups to more specific activities. OpenAI states that the data shows wide variation across countries in how people use ChatGPT for work.
Users of the explorer can select an activity group to see the tasks within it, see how those change over time, or choose a country to explore its mix of work-related messages. The chart reports shares as a percentage of work-related messages, starting from Q1 2025.
Comparing ChatGPT use with work across the U.S. economy
Connecting ChatGPT usage data with IWAs lets researchers compare ChatGPT messages with activities performed across U.S. jobs. The release includes paired visualizations that compare how people use ChatGPT with the activities performed across U.S. jobs, showing the difference between how people use ChatGPT for work and the actual work being done in the U.S. economy.
OpenAI reports that the two distributions differ substantially, largely because about 43% of the employment-weighted task mix for mapped U.S. occupations falls into "Other" IWAs, outside the individually reported categories. These include activities such as moving materials, operating vehicles, and maintaining health or medical records. OpenAI states that these omitted categories did not meet its threshold for consistent representation in the original U.S. ChatGPT sample.
The economy-side visualization is described in the release as the "Share of economy-wide activity" measured against a fixed 2025-01-01 reference. An accompanying tool lets users select an activity to see how much it appears in ChatGPT usage versus the overall U.S. economy.
What the data covers and what it excludes
The data covers work-related messages on individual ChatGPT plans. It does not include enterprise messages or Codex use. Any interpretation of the findings therefore describes consumer ChatGPT work usage rather than the full range of ways organizations use OpenAI products.
Privacy and methodology protections
OpenAI states that to protect users' privacy, researchers do not read individual conversations. Automated systems classify messages after identifying information is removed. OpenAI publishes aggregated statistics, withholds results for small groups, and adds statistical noise to protect individual messages.
How researchers can use the release
This release builds on OpenAI Signals, OpenAI's ongoing effort to share evidence about how people use AI. OpenAI invites researchers to explore the data, connect it with other sources, and investigate what these patterns mean for workers and businesses.
The release also includes a citation section for referencing the dataset. Because the underlying unit is a work activity rather than a job title or an industry, the data can be matched against occupational and employment sources that use the same O*NET-derived structure.