Epoch AI maps three years of ChatGPT usage

Epoch AI has released a public usage explorer based on chat-export metadata from 5,000 US panelists. Covering ChatGPT activity from its launch in late 2022 through December 2025, the dataset offers an independent view of how frequently retained users return, how long their conversations run, and which models and tools they use.

YouGov assembled the dataset by randomly selecting eligible members of its US panel. Participants had opted to share their ChatGPT exports and had used the product at least once in 2026. They exported their histories between January and August 2026, producing metadata for about 8.3 million messages across 660,000 conversations.

Epoch received no message text. The explorer exposes aggregate activity patterns while excluding transcripts, prompts, responses, and conversation topics.

Inside 8.3 million messages

Each record includes a timestamp, character count, responding model, and any tools invoked. Epoch organizes the data into nine main metrics:

• Participation: active panelists, subscription plan, and first recorded use.
• Engagement: active days per month and messages per active panelist.
• Conversation behavior: prompts per conversation, most-used model, tool use, and reasoning-model use.
• Demographic breakdowns: gender, age, education, household income, employment status, and plan type in the downloadable dataset.

Every series is available at weekly or monthly resolution. Chart overlays mark model and tool launches, allowing researchers to compare usage patterns around releases such as GPT-4o and o1. The overlays establish timing; causal analysis requires additional controls.

The metrics use two related units. “Messages per active panelist” counts user prompts and assistant replies, while prompt-based measures count user submissions. An active panelist has recorded activity during the selected period.

Returning users deepen their habits

Usage rose substantially among participants who remained active through the study’s eligibility window. Median monthly messages per active panelist increased from 14 in January 2023 to 36 in December 2025. The December 2025 mean reached 158 because heavy users accounted for a disproportionate share of activity.

The distribution shifted toward frequent use between December 2023 and December 2025. The share active on at least 21 days per month quadrupled, while the shares using ChatGPT on five or fewer days declined.

Average conversations also lengthened. Mean prompts per conversation rose from 3.7 in December 2022 to 5.8 in December 2025, while the median remained at two prompts in every month except September 2023. A relatively small group running long sessions drove most of the increase in the average.

A sample built around survivors

The eligibility rules create survivorship bias because every participant had to use ChatGPT at least once in 2026. People who tried the product in 2023 and stopped before 2026 are absent, so the sample favors persistent users and mechanically raises historical engagement trends.

Self-selection occurs before random sampling. Participants came from YouGov members who had opted to share their exports, and Epoch did not reweight the results to match US demographics or the broader ChatGPT user base. The panel also skews older and more educated. Epoch notes that this composition may understate some technical or high-intensity behavior, although the direction of bias can vary by metric.

Aggregate trends align closely with figures published by OpenAI. In July 2025, weekly active panelists sent 4.3 prompts per day, compared with about 3.7 implied by OpenAI’s figures. From June 2024 to June 2025, panel prompt volume grew 5.6 times, close to the 5.8-times increase in OpenAI’s data. That agreement supports the broad growth trend but does not resolve demographic and survivorship biases.

Strongest uses, firm limits

Independent longitudinal metadata on consumer AI behavior remains scarce. Epoch’s methodology and downloadable series support several practical analyses:

• Benchmark engagement: compare product metrics with the cadence, concentration, and conversation length observed among retained ChatGPT users.
• Track product shifts: examine whether model and tool launches coincide with changes in usage.
• Compare cohorts: study differences by age, income, education, employment, gender, or subscription plan while accounting for the sample’s composition.
• Reproduce results: download the series and reuse the charts under the CC BY license.

The dataset cannot reveal user goals, task categories, response quality, satisfaction, or prompt content. Chat exports also exclude API traffic. Developers and researchers can treat the reported rates as behavioral benchmarks for retained US users, while population adoption, retention, and market-size estimates require representative data from additional sources.