AI Data Centers Face Looming Power Crisis: Gartner Predicts Widespread Shortages by 2027

Gartner Predicts Power Shortages Will Restrict 40% of AI Data Centers By 2027

Rapid Growth in Energy Consumption For GenAI Will Exceed Power Utilities' Capacity AI and generative AI (GenAI) are driving rapid increases in electricity consumption, with data center forecasts over the next two years reaching as high as 160% growth, according to Gartner, Inc. As a result, Gartner predicts 40% of existing AI data centers will be operationally constrained by power availability by 2027. "The explosive growth of new hyperscale data centers to implement GenAI is creating an insatiable demand for power that will exceed the ability of utility providers to expand their capacity fast enough," said Bob Johnson, VP Analyst at Gartner. "In turn, this threatens to disrupt energy availability and lead to shortages, which will limit the growth of new data centers for GenAI and other uses from 2026." Gartner estimates the power required for data centers to run incremental AI-optimized servers will reach 500 terawatt-hours (TWh) per year in 2027, which is 2.6 times the level in 2023 (see Figure 1). Figure 1: Estimated Incremental Power Consumption of AI Data Centers, 2022-2027 Source: Gartner (November 2024) "New larger data centers are being planned to handle the huge amounts of data needed to train and implement the rapidly expanding large language models (LLMs) that underpin GenAI applications," said Johnson. "However, short-term power shortages are likely to continue for years as new power transmission, distribution and generation capacity could take years to come online and won't alleviate current problems." In the near future, the number of new data centers and the growth of GenAI will be governed by the availability of power to run them. Gartner recommends organizations determine the risks potential power shortages will have on all products and services. Electricity Prices Will Increase The inevitable result of impending power shortages is an increase in the price of power, which will also increase the costs of operating LLMs, according to Gartner. "Significant power users are working with major producers to secure long-term guaranteed sources of power independent of other grid demands," said Johnson. "In the meantime, the cost of power to operate data centers will increase significantly as operators use economic leverage to secure needed power. These costs will be passed on to AI/GenAI product and service providers as well." Gartner recommends organizations evaluate future plans anticipating higher power costs and negotiate long-term contracts for data center services at reasonable rates for power. Organizations should also factor significant cost increases when developing plans for new products and services, while also looking for alternative approaches that require less power. Sustainability Goals Will Suffer Zero-carbon sustainability goals will also be negatively affected by short-term solutions to provide more power, as surging demand is forcing suppliers to increase production by any means possible. In some cases, this means keeping fossil fuel plants that had been scheduled for retirement in operation beyond their scheduled shutdown. "The reality is that increased data center use will lead to increased CO2 emissions to generate the needed power in the short-term," said Johnson. "This, in turn, will make it more difficult for data center operators and their customers to meet aggressive sustainability goals relating to CO2 emissions." Data centers require 24/7 power availability, which renewable power such as wind or solar cannot provide without some form of alternative supply during periods when not generating power, according to Gartner. Reliable 24/7 power can only be generated by either hydroelectric, fossil fuel or nuclear power plants. In the long-term, new technologies for improved battery storage (e.g sodium ion batteries) or clean power (e.g small nuclear reactors) will become available and help achieve sustainability goals. Gartner recommends organizations re-evaluate sustainability goals relating to CO2 emissions in light of future data center requirements and power sources for the next few years. When developing GenAI applications, they should focus on using a minimum amount of computing power and look at the viability of other options such as edge computing and smaller language models. Gartner clients can learn more in "Emerging Tech: Power Shortages Will Restrict GenAI Growth and Implementation." Gartner IT Infrastructure, Operations & Cloud Strategies Conference Gartner analysts will provide additional analysis on cloud strategies and infrastructure and operations trends at the Gartner IT Infrastructure, Operations & Cloud Strategies Conferences taking place November 19-20 in London, December 3-4 in Tokyo and December 10-12 in Las Vegas. Follow news and updates from these conferences on X using #GartnerIO. About Gartner for Information Technology Executives Gartner for Information Technology Executives provides actionable, objective insight to CIOs and IT leaders to help them drive their organizations through digital transformation and lead business growth. Additional information is available at www.gartner.com/en/information-technology. Follow news and updates from Gartner for IT Executives on X and LinkedIn using #GartnerIT. Visit the IT Newsroom for more information and insights. About Gartner Gartner, Inc. (NYSE: IT) delivers actionable, objective insight that drives smarter decisions and stronger performance on an organization's mission-critical priorities. To learn more, visit gartner.com.

AI Data Centers May Face Power Shortages by 2025

Amazon data centers in Virginia (Credit: Bloomberg/Contributor via Getty Images) AI data centers and supercomputers with hundreds or thousands of graphics cards use a lot of energy, but by 2025, 40% of all AI data centers may not have enough power to function fully. As more AI data centers connect to the grid, like Elon Musk's xAI supercomputer in Tennessee, their collective power demand increases and could hit 500 Terawatt-hours by 2027. That's over double the current needs, according to a new report from Gartner. Meta is also a big player in the data center space, with numerous data centers under construction. Microsoft is looking to add more data centers to its portfolio and is even planning to resurrect Three Mile Island to power its AI vision. These tech giants, as well as Google and Amazon, are increasingly looking to nuclear power to fulfill energy needs. "New larger data centers are being planned to handle the huge amounts of data needed to train and implement the rapidly expanding large language models (LLMs) that underpin GenAI applications," says Gartner VP Analyst Bob Johnson. "However, short-term power shortages are likely to continue for years as new power transmission, distribution, and generation capacity could take years to come online and won't alleviate current problems." Gartner predicts this continued spike in electricity demand will result in higher power prices than usual over time. It'll also make it harder for utility providers to reduce their carbon emissions, meaning all this AI model training and operations may exacerbate climate change. While some academics believe AI could help humans solve the climate crisis, the tech is causing energy and carbon emission problems in the meantime. Developing and using efficient computer hardware and renewable energy sources could help, though, as well as scheduling data centers to only operate at off-peak hours and building them in colder regions to reduce cooling costs.

Nearly half of AI data centers may not have enough power by 2027 | TechCrunch

AI's insatiable thirst for electricity is expected to surge in the coming years, potentially leading to power shortages for data centers. New servers last year demanded 195 terawatt-hours of electricity, according to a new report from Gartner. That's as much as 18 million households use in a year. But by 2027, new servers could command 500 terawatt-hours, or 46 million households worth. That's over and above the juice used by existing data centers, which already consumed 349 terawatt hours in 2022, according to a Goldman Sachs estimate. Without additional sources of carbon-free power, pollution from AI training and use could skyrocket. Sam Altman's big bet on fusion power -- over $375 million -- is starting to make more sense.

AI data centers could make your electric bill go up by 70%

Every use of AI requires massive amounts of data, meaning as AI has surged, companies have been building more and more data centers across the country. Those data centers also require lots of energy to operate, and that means they could soon require more energy than what's available on the grid. If AI's energy demand outstrips electricity supplies, that has real impacts for Americans -- like a higher risk of electricity outages, and higher energy costs. By 2029, consumers and small businesses could see their electricity bills increase 70% because of surging energy demand from AI data centers, according to a new report by the Jack Kemp Foundation, a Washington, D.C. think tank created by former Republican Representative Jack Kemp. That means consumers will bear the brunt of AI's increasing energy use, says Ike Brannon, coauthor of the study and a senior fellow at the Jack Kemp Foundation. This is already beginning to play out in Northern Virginia, which currently has the highest concentration of data centers in the world. In Virginia, data centers could use almost half of the state's total electricity by 2030. The surge of data centers in Northern Virginia -- driven by the federal government and national security agencies -- is already leading to utility increases. "We haven't really increased [energy] supply all that much around here, but demand is going up," Brannon says. In the areas of the state served by utility company Dominion Energy, one price metric for peak demands in 2025 increased from $29 to $444 per megawatt-day.