A Typical AI Query Use Less Energy Than Using a Laptop One Minute

Super fact 138 : A Typical AI Query use less energy than using a laptop for one minute. A typical AI Query use between a few drops of water to half a bottle of water at worst. Data centers in the United States use roughly 0.2% of total U.S. freshwater when combining direct facility cooling and indirect water used for electricity generation. A ten minute shower uses more energy than 5,000 typical AI Queries.

The bar graph shows that a typical AI query uses 0.3 Watt hours of energy whilst a 5-minute laptop usage uses 2 Watt hours. Charging a mobile phone use 20 Watt hours and watching TV for one hour uses 90 Watt hours. Average US consumption per person and per is 24 Watt hours and a one minute shower uses 1,600 Watt hours.
How does the electricity consumption of individual AI queries compare to other everyday activities? Marginal increase in electricity consumption from different activities, measured in watt-hours (Wh). Note Estimates for AI cover inference only; however, model training adds little per query given how many queries each model serves over its lifetime. Data source: AI text query estimates from EpochAI (2025). Other estimates explained at https://hannahritchie.github.io/energy-use-comparisons  OurWorldinData – Research and data to make progress against the world’s largest problems.   Licensed under CC-BY by the author Hannah Ritchie.

According to the Manhattan institute, NVIDIA, Google and this article the data centers in the United States use roughly 0.2% of total U.S. freshwater when combining direct facility cooling and indirect water used for electricity generation. Most fresh water used in the US is for irrigation / agriculture and the second largest consumer of fresh water is thermoelectric plants (coal, natural gas, nuclear). Worldwide 70% of freshwater used is used by agriculture and industry is another big user. According to this article Google says that a typical AI query uses five drops of water, and half a bottle of water at the worst. You can read more about water usage here, here, here, and here.

Around half of all energy used by data centers is thermoelectric. Most of the freshwater usage that is part of the 0.2% number is due to the thermoelectric powerplants supplying the energy to data centers. However, it should be noted that as clean energy is increasingly adopted this number will decline. On the other hand, the manufacturing of computer chips, which also use a lot of freshwater, is not taken into account in this number because it is a onetime event that is difficult to account for. It might double or even triple the 0.2% number, which is still very little.

It should be noted that there are a lot of valid concerns about AI and datacenters, but to reduce carbon emissions and pollution and to waste less freshwater, it might be more effective to eat less beef, irrigate your lawn less, take shorter showers, drive an EV or a hybrid instead of a gas guzzling SUV with an internal combustion engine, or perhaps use public transportation. You’d start with the low hanging fruit. In fact, if the AI query you are about to make saves you some time on your laptop, then the AI query probably helps the environment.

Datacenters use less freshwater than many of us would expect, and typical AI queries use almost no energy and correspond to very little use of freshwater. I think this comes as a surprise to many considering the ongoing datacenter panic. It is therefore a super fact.

Datacenters and Energy Usage

Datacenters use a significant amount of energy but perhaps not as much as one would think. However, their energy use is increasing, and they are part of our rising energy demand. With a growing population, a growing economy, cryptocurrencies, AI, datacenters, electrification, we are going to need a growing supply of electricity and an expanding grid. Hopefully our energy sources will be mostly clean energy, which luckily seems to be the trend. See “The Unfolding Clean Energy Revolution”.

The United States is the country with the most datacenters and as can be seen in the graph below, the datacenters in the United States use a relatively large portion of its available electricity for datacenters and it is increasing.

The graph shows that the share of electricity used for data centers in the US is 5%, Europe 2%, China 1%, Middle East 0.3%, Africa 0.2%, Central & South America 0.1%, and globally it is 1.5%.
5% of electricity generated in the United States is used for data centers. Electricity consumed by data centers as a share of electricity generation in 2025. Note: Data centers power a wide range of services, including streaming, messaging, and cloud storage, as well as artificial intelligence (AI). Data sources: International Energy agency (2026); Ember (2026). CC BY

The Growing Energy Use by Datacenters

The three graphs below are from this page and this page. Note the projected increase in electricity use for data centers. Note that by visiting these pages you play around with the graphs and changed regions and countries and other settings to generate your own graphs.

The graphs depict the growing electricity use by data centers from 2020 to 2025. In the United States the share of electricity used for data centers grew from 2.6% in 2020 to 4.9% in 2025. It also grew for Europe, China, Africa, and the World but less. For the world without the United States and China it grew more modestly from 0.7% to 0.9%.
Share of total electricity demand used by data centers 2020 to 2025. Electricity consumed by data centers given as a share of electricity generation. Data centers power a wide range of digital services including streaming, messaging, and cloud storage. Artificial Intelligence (AI) focused data centers are a subset of this electricity consumption. Data source: International Energy agency (2026); Ember (2026). OurWorldinData.org/artificial-intelligence | CC BY
The graph shows that the share of electricity used for data centers in the US is 4.9%, Europe 1.9%, China 1.1%, Middle East 0.3%, Africa 0.2%, Central & South America 0.1%, and globally it is 1.5%.
Share of total electricity demand used by data centers 2025. Electricity consumed by data centers given as a share of electricity generation. Data centers power a wide range of digital services including streaming, messaging, and cloud storage. Artificial Intelligence (AI) focused data centers are a subset of this electricity consumption. Data source: International Energy agency (2026); Ember (2026). OurWorldinData.org/artificial-intelligence | CC BY
This graph shows that worldwide growth in electricity usage by data centers will grow from 485TWh in 2025 to 945TWh in 2030. However, the portion from Artificial Intelligence (AI) will grow from 155TWh to 465TWh
How much of global electricity is used for data centers? Measured in terawatt-hours (TWh). Estimates for 2025; base-case projections for 2030 from the International Energy Agency (IEA). Note: Projections for 2030 are very uncertain but are shown here to reflect expectations that most data center growth will come from AI-focused ones. Data source: IEA (2026). Key Questions on Energy and AI. CC BY

As you can see in the graphs above, there is a significant portion, but not a large portion, of electricity usage by data centers. However, it is important to note that only a portion of this is for Artificial Intelligence. It will grow though. You can read more about this issue here, and here, or here.

Fresh Water Usage in the United States

The graphics below showing the source and use of freshwater in the United States is in the public domain and is taken from this article.

The diagram shows that the daily surface water withdrawals is 237,000 gallons per day and the daily groundwater withdrawals is 84,700 gallons per day. This is distributed to agriculture (118,000 gallons per day), livestock (2,000 gallons per day). Aquaculture (7,550 gallons per day), thermoelectric power (133,000 gallons per day), Industrial (14,800 gallons per day), domestic (3,260 gallons per day), and public supply (39,000 gallons per day).
Source and use of water in the United States, 2015. The diagram is in the public domain. View media details.

In the diagram above, the top row of cylinders represents where America’s freshwater came from (source) in 2015, either from surface water (blue) or from groundwater (brown). You can see most of the water we use came from surface-water sources, such as rivers and lakes. About 26 percent of water used came from groundwater. The pipes leading out of the surface-water and groundwater cylinders on the top row and flowing into the bottom rows of cylinders (green) show the categories of water use where the water was sent after being withdrawn from a river, lake, reservoir, or well. For example, the blue pipe coming out of the surface-water cylinder and entering the public supply cylinder shows that 23,800 Mgal/d of water was withdrawn from surface-water sources for public-supply uses (you probably get your water this way). Likewise, the brown pipe shows that public-suppliers withdrew another 15,200 Mgal/d of water from groundwater sources. Each green cylinder represents a category of water use. The industrial cylinder, for instance, shows how much groundwater, surface water, and total water was used inthe United States, each day, by industries.

Other Super Facts Related to Artificial Intelligence

The diagram shows a deep learning neural network featuring hidden layers, a couple of input/output layers, and large computer.
The diagram shows a deep learning neural network featuring hidden layers, a couple of input/output layers, and a large computer. The dots in the diagram are neurons. With permission from kwholley63.



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