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Estimated share of working-age population using selected generative AI tools

What you should know about this indicator

  • These are modelled estimates, not survey data. They are derived from anonymized usage signals collected automatically by Microsoft's software and services, which log whether users visited any of 19 platforms, including ChatGPT, Gemini, Claude, DeepSeek, Grok, Midjourney, and others.
  • Microsoft can directly observe this mainly on Windows desktops and tablets. It then scales these numbers up to estimate total use across desktop, tablet, and mobile devices in each country.
  • To do this, Microsoft adjusts for how common desktop and tablet devices are in each country, how much internet use happens on mobile rather than desktop, and how many users share data with Microsoft.
  • Users with less than 90 minutes of activity per month are excluded, to reduce the influence of one-time or very infrequent users. It is not clearly stated whether this threshold refers to all internet activity seen by Microsoft or only to activity on AI websites.
  • Some countries do not have enough data for their own estimate and are assigned a regional average instead.
  • Coverage is limited in some countries, especially Russia, Iran, and parts of China, so estimates for these places carry greater uncertainty.
  • This indicator only covers selected AI websites and apps. It does not include AI features built into other software, such as productivity tools or enterprise systems.
Estimated share of working-age population using selected generative AI tools
Estimated share of the working-age population (aged 15–64) who used a website or app, such as ChatGPT or Gemini, in the second half of 2025.
Source
Microsoft (2026) – with minor processing by Our World in Data
Last updated
April 7, 2026
Next expected update
April 2027
Date range
2025–2025
Unit
%

Sources and processing

This data is based on the following sources

Microsoft – Microsoft AI Diffusion Report 2025

Microsoft measures AI diffusion as the share of people worldwide who have used a generative AI product during the reported period. This measure is derived from aggregated and anonymized Microsoft telemetry and then adjusted to reflect differences in OS and device-market share, internet penetration, and country population. Additional details on the methodology are available in their AI Diffusion technical paper.

Retrieved on
April 7, 2026
Retrieved from
https://www.microsoft.com/en-us/corporate-responsibility/topics/AI-Economy-Institute/reports/Global-AI-Adoption-2025/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Microsoft Research. AI Diffusion Report 2025. January 2026.

Microsoft measures AI diffusion as the share of people worldwide who have used a generative AI product during the reported period. This measure is derived from aggregated and anonymized Microsoft telemetry and then adjusted to reflect differences in OS and device-market share, internet penetration, and country population. Additional details on the methodology are available in their AI Diffusion technical paper.

Retrieved on
April 7, 2026
Retrieved from
https://www.microsoft.com/en-us/corporate-responsibility/topics/AI-Economy-Institute/reports/Global-AI-Adoption-2025/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Microsoft Research. AI Diffusion Report 2025. January 2026.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

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  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Estimated share of working-age population using selected generative AI tools”, part of the following publication: Charlie Giattino, Edouard Mathieu, Veronika Samborska, and Max Roser (2023) - “Artificial Intelligence”. Data adapted from Microsoft. Retrieved from https://archive.ourworldindata.org/20260421-080745/grapher/estimated-share-people-generative-ai.html [online resource] (archived on April 21, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Microsoft (2026) – with minor processing by Our World in Data

Full citation

Microsoft (2026) – with minor processing by Our World in Data. “Estimated share of working-age population using selected generative AI tools” [dataset]. Microsoft, “Microsoft AI Diffusion Report 2025” [original data]. Retrieved April 21, 2026 from https://archive.ourworldindata.org/20260421-080745/grapher/estimated-share-people-generative-ai.html (archived on April 21, 2026).

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