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Share of total electricity demand coming from data centers

See all data and research on:
Artificial IntelligenceEnergy

What you should know about this indicator

  • This indicator shows what share of a country’s or region’s total electricity demand comes from data centers.
  • It covers total data-center electricity use (including cooling and other support systems), across both general-purpose and AI-specialized servers.
Share of total electricity demand coming from data centers
Data center electricity consumption as a share of total electricity demand of the country or region. Data centers power a wide range of online services beyond AI, such as streaming services and cloud storage. The data does not allow a separate estimate for AI use.
Source
International Energy Agency (2025); Ember (2026) – with major processing by Our World in Data
Last updated
November 7, 2025
Next expected update
November 2026
Date range
2020–2024
Unit
%

Sources and processing

This data is based on the following sources

International Energy Agency – Energy and AI

Retrieved on
November 7, 2025
Retrieved from
https://www.iea.org/data-and-statistics/data-product/energy-and-ai
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.
International Energy Agency (IEA), 'Energy and AI'. Published online at iea.org. Retrieved from: 'https://www.iea.org/data-and-statistics/data-product/energy-and-ai' [online resource]
Retrieved on
November 7, 2025
Retrieved from
https://www.iea.org/data-and-statistics/data-product/energy-and-ai
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.
International Energy Agency (IEA), 'Energy and AI'. Published online at iea.org. Retrieved from: 'https://www.iea.org/data-and-statistics/data-product/energy-and-ai' [online resource]

Ember – Yearly Electricity Data Europe

This dataset contains yearly electricity generation, capacity, emissions, imports and demand data for European countries.

You can find more about Ember's methodology in this document.

Retrieved on
January 26, 2026
Retrieved from
https://ember-energy.org/data/yearly-electricity-data/
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.
Ember - Yearly Electricity Data Europe (2026).
Most of the data is taken from the European Commission's Eurostat annual data.

This dataset contains yearly electricity generation, capacity, emissions, imports and demand data for European countries.

You can find more about Ember's methodology in this document.

Retrieved on
January 26, 2026
Retrieved from
https://ember-energy.org/data/yearly-electricity-data/
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.
Ember - Yearly Electricity Data Europe (2026).
Most of the data is taken from the European Commission's Eurostat annual data.

Ember – Yearly Electricity Data

This dataset contains yearly electricity generation, capacity, emissions, import and demand data for over 200 geographies.

You can find more about Ember's methodology in this document.

Retrieved on
January 9, 2026
Retrieved from
https://ember-energy.org/data/yearly-electricity-data/
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.
Ember - Yearly Electricity Data (2026).
The data is collected from multi-country datasets (EIA, Eurostat, Energy Institute, UN) as well as national sources (e.g China data from the National Bureau of Statistics).

This dataset contains yearly electricity generation, capacity, emissions, import and demand data for over 200 geographies.

You can find more about Ember's methodology in this document.

Retrieved on
January 9, 2026
Retrieved from
https://ember-energy.org/data/yearly-electricity-data/
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.
Ember - Yearly Electricity Data (2026).
The data is collected from multi-country datasets (EIA, Eurostat, Energy Institute, UN) as well as national sources (e.g China data from the National Bureau of Statistics).

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 calculated this share by dividing data center electricity consumption by total electricity demand for each country or region.

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 total electricity demand coming from data centers”, part of the following publication: Charlie Giattino, Edouard Mathieu, Veronika Samborska, and Max Roser (2023) - “Artificial Intelligence”. Data adapted from International Energy Agency, Ember. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/data-centers-share-electricity-demand.html [online resource] (archived on March 4, 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:

International Energy Agency (2025); Ember (2026) – with major processing by Our World in Data

Full citation

International Energy Agency (2025); Ember (2026) – with major processing by Our World in Data. “Share of total electricity demand coming from data centers” [dataset]. International Energy Agency, “Energy and AI”; Ember, “Yearly Electricity Data Europe”; Ember, “Yearly Electricity Data” [original data]. Retrieved April 6, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/data-centers-share-electricity-demand.html (archived on March 4, 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://ourworldindata.org/grapher/data-centers-share-electricity-demand.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/data-centers-share-electricity-demand.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/data-centers-share-electricity-demand.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/data-centers-share-electricity-demand.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/data-centers-share-electricity-demand.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/data-centers-share-electricity-demand.csv?v=1&csvType=full&useColumnShortNames=false")

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