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Share of companies using artificial intelligence technology

See all data and research on:
Artificial Intelligence

What you should know about this indicator

  • Based on McKinsey & Company’s annual “State of AI” surveys of organizations across many countries, industries, and company sizes.
  • Organizations are counted as using AI if they report using it in at least one business function.
  • Responses are self-reported and should be interpreted as indicative of trends rather than precise measures of global adoption.
  • Reported use often reflects early-stage adoption, such as experimentation or pilot projects, rather than widespread deployment.
  • To account for differences in response rates, results are weighted by each country’s contribution to global GDP.
Share of companies using artificial intelligence technology
Share of companies using AI technology (e.g., machine learning, computer vision, or natural language processing) in at least one business function.
Source
McKinsey & Company via AI Index Report – with major processing by Our World in Data
Last updated
April 20, 2026
Next expected update
April 2027
Date range
2021–2025
Unit
%

Related research and writing

Artificial intelligence has advanced despite having few resources dedicated to its development — now investments have increased substantially

Max Roser

Sources and processing

This data is based on the following sources

McKinsey & Company Survey via AI Index – AI Index Report

The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). The mission is to provide unbiased, rigorously vetted, broadly sourced data to enable policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI.

Retrieved on
April 8, 2025
Retrieved from
https://hai-production.s3.amazonaws.com/files/hai_ai_index_report_2025.pdf
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.
Nestor Maslej, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Njenga Kariuki, Emily Capstick, Anka Reuel, Erik
Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald,
Tobi Walsh, Armin Hamrah, Lapo Santarlasci, Julia Betts Lotufo, Alexandra Rome, Andrew Shi, Sukrut Oak. “The AI Index 2025
Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2025

The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). The mission is to provide unbiased, rigorously vetted, broadly sourced data to enable policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI.

Retrieved on
April 8, 2025
Retrieved from
https://hai-production.s3.amazonaws.com/files/hai_ai_index_report_2025.pdf
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.
Nestor Maslej, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Njenga Kariuki, Emily Capstick, Anka Reuel, Erik
Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald,
Tobi Walsh, Armin Hamrah, Lapo Santarlasci, Julia Betts Lotufo, Alexandra Rome, Andrew Shi, Sukrut Oak. “The AI Index 2025
Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2025

AI Index Report

The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). The mission is to provide unbiased, rigorously vetted, broadly sourced data to enable policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI.

Retrieved on
April 20, 2026
Retrieved from
https://hai.stanford.edu/assets/files/ai_index_report_2026.pdf
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.
Sha Sajadieh, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Lapo Santarlasci, Juan Pava, Nestor Maslej, Russ Altman, Erik Brynjolfsson, Carla Brodley, Jack Clark, Virginia Dignum, Vipin Kumar, James Landay, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Elham Tabassi, Russell Wald, Toby Walsh, Dan Weld. “The AI Index 2026 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2026.

The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). The mission is to provide unbiased, rigorously vetted, broadly sourced data to enable policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI.

Retrieved on
April 20, 2026
Retrieved from
https://hai.stanford.edu/assets/files/ai_index_report_2026.pdf
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.
Sha Sajadieh, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Lapo Santarlasci, Juan Pava, Nestor Maslej, Russ Altman, Erik Brynjolfsson, Carla Brodley, Jack Clark, Virginia Dignum, Vipin Kumar, James Landay, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Elham Tabassi, Russell Wald, Toby Walsh, Dan Weld. “The AI Index 2026 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 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
Notes on our processing step for this indicator

We combine data from multiple releases of the AI Index Report. When the same year appears in more than one release, we use the most recent version.

Reuse this work

  • 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.
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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: Share of companies using artificial intelligence technology”, part of the following publication: Charlie Giattino, Edouard Mathieu, Veronika Samborska, and Max Roser (2023) - “Artificial Intelligence”. Data adapted from McKinsey & Company Survey via AI Index, AI Index Report. Retrieved from https://auto-epoch.owid.pages.dev:8789/20260424-104218/grapher/share-companies-using-artificial-intelligence.html [online resource] (archived on April 24, 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:

McKinsey & Company via AI Index Report – with major processing by Our World in Data

Full citation

McKinsey & Company via AI Index Report – with major processing by Our World in Data. “Share of companies using artificial intelligence technology” [dataset]. McKinsey & Company Survey via AI Index, “AI Index Report”; AI Index Report, “AI Index Report” [original data]. Retrieved May 8, 2026 from https://auto-epoch.owid.pages.dev:8789/20260424-104218/grapher/share-companies-using-artificial-intelligence.html (archived on April 24, 2026).

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Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://auto-epoch.owid.pages.dev/grapher/share-companies-using-artificial-intelligence.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://auto-epoch.owid.pages.dev/grapher/share-companies-using-artificial-intelligence.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://auto-epoch.owid.pages.dev/grapher/share-companies-using-artificial-intelligence.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://auto-epoch.owid.pages.dev/grapher/share-companies-using-artificial-intelligence.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://auto-epoch.owid.pages.dev/grapher/share-companies-using-artificial-intelligence.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://auto-epoch.owid.pages.dev/grapher/share-companies-using-artificial-intelligence.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://auto-epoch.owid.pages.dev/grapher/share-companies-using-artificial-intelligence.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://auto-epoch.owid.pages.dev/grapher/share-companies-using-artificial-intelligence.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear