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How ChatGPT adoption has expanded

Chimera readability score 66 out of 100, Academic reading level.

A new picture of global AI adoption.
ChatGPT adoption is widening and deepening around the world. New OpenAI Signals data shows that people use ChatGPT more often and for a broader range of tasks over time, while its user base is becoming more global and more diverse.
Using aggregated data, OpenAI Signals measures how people interact with Individual ChatGPT plans (these include Free, Go, Plus, and Pro plans) over time. This analysis offers a view into how Individual AI usage is evolving as ChatGPT reaches global scale.
The visualizations below highlight several core trends in global AI adoption: how use of ChatGPT deepened since launch, the ways people incorporate ChatGPT into their routines, and how this varies across languages and regions. Together, these findings provide a clearer picture of how people around the world are incorporating ChatGPT into work, learning, and daily life—in other words how AI is benefiting a large swath of humanity.
As individuals use ChatGPT for longer, they both send more messages daily and try more new capabilities. Over time, users both did more things and did things more on ChatGPT. Six months after signing up, users sent 50% more messages per day than they did when they signed up. They also doubled the number of distinct tasks they’ve tried on ChatGPT.
ChatGPT adoption has grown sharply across every continent since July 2023. In relative terms, the fastest growth has been in Africa and Asia.
A similar pattern appears across country-development groupings: lower-Human Development Index (HDI) countries have seen the fastest relative growth in weekly active users since July 2023. OpenAI has continued to provide low-cost access to ChatGPT through our free and Go plans.
Usage by people with typically-female names has increased, now representing most usage globally. Brazil, Colombia, Poland, and Namibia rank among the countries where messages sent by users with typically feminine names most significantly exceed users with typically masculine names. In contrast, Pakistan, Bangladesh, Angola, the Democratic Republic of Congo, and Mali have the most concentrated usage by those with typically masculine names. Overall, this data shows our best estimate of how many people with typically feminine or masculine names are using ChatGPT since we do not collect information on users’ gender.1
Non-English ChatGPT usage grew alongside global usage. Users predominantly using a language other than English now represent over half of active users. The leading non-English languages on ChatGPT are Spanish, Portuguese, and Arabic.
Uzbek, Kazakh, and Burmese were the languages with the largest percentage increase in their share of active users since July 2023.
OpenAI Signals is an ongoing effort to ensure that researchers and policymakers have the best data at their fingertips to understand how AI is affecting and will impact the economy.
Author
Footnotes
- 1
This analysis excludes messages from names that are not typically masculine or typically feminine. For more about the methodology we used to determine this please read our full methodology.

Sentinel — Human

Confidence

The text exhibits high coherence and specific data referencing consistent with formal research reporting, suggesting human authorship or careful editorial review of proprietary data.

Signals Detected
low severity: Moderate sentence length variance and formal, data-driven tone.
low severity: High internal coherence; the flow from macro trends to specific demographic/geographic data is seamless.
low severity: Uses statistical findings and explicit source naming ('OpenAI Signals'); standard scientific reporting structure.
low severity: Claims are tied directly to specific data points and methodologies (e.g., July 2023 growth, specific country rankings); risk of fabrication is low.
Human Indicators
The concluding statement and footnote structure suggest adherence to formal reporting standards typical of institutional releases.
The specificity of the demographic data (names associated with gender) points toward a specialized, human-curated dataset presentation rather than generic LLM synthesis.