Our World
in Data
Oxford Martin School logoUniversity of Oxford logoGlobal Change Data Lab logo
Data

Share of companies using artificial intelligence technology

See all data and research on:
Artificial Intelligence

What you should know about this indicator

  • The McKinsey survey asked organizations in which business functions they had adopted AI technologies, such as machine learning, computer vision, or natural language processing.
  • Respondents could choose from eleven business functions, including marketing and sales, product and service development, IT, service operations, knowledge management, software engineering, human resources, legal, risk and compliance, corporate strategy and finance, supply chain management, and manufacturing.
  • An organization was considered to be using AI if it had adopted it in at least one of these areas.
  • The term “adopted” was not strictly defined, so reported use of AI ranged from limited experimentation by a small group of employees to widespread implementation across departments.
  • The regional groupings, as defined by McKinsey & Company, classify countries into specific categories. The "Developing markets" grouping includes countries such as India, Latin America, and the Middle East and North Africa (MENA). The "Greater China" grouping includes Hong Kong and Taiwan.
  • The number of companies that respond to the survey varies between years and ranged between 1363 and 1843 between 2021 and 2024.
  • The data is adjusted to account for differences in response rates and to ensure that each country's economic contribution to global GDP is properly represented.
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 Survey via AI Index (2025); McKinsey & Company Survey via AI Index (2023) – with minor processing by Our World in Data
Last updated
April 8, 2025
Next expected update
April 2026
Date range
2021–2024
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

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

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.
  • 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: 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. Retrieved from https://archive.ourworldindata.org/20260323-134357/grapher/share-companies-using-artificial-intelligence.html [online resource] (archived on March 23, 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 Survey via AI Index (2025); McKinsey & Company Survey via AI Index (2023) – with minor processing by Our World in Data

Full citation

McKinsey & Company Survey via AI Index (2025); McKinsey & Company Survey via AI Index (2023) – with minor processing by Our World in Data. “Share of companies using artificial intelligence technology” [dataset]. McKinsey & Company Survey via AI Index, “AI Index Report” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260323-134357/grapher/share-companies-using-artificial-intelligence.html (archived on March 23, 2026).

Download

Quick download

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.

Download full data

Includes all entities and time points

Download displayed data

Includes only the entities and time points currently visible in the chart

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://ourworldindata.org/grapher/share-companies-using-artificial-intelligence.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/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://ourworldindata.org/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://ourworldindata.org/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://ourworldindata.org/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://ourworldindata.org/grapher/share-companies-using-artificial-intelligence.csv?v=1&csvType=full&useColumnShortNames=false")

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