AI Data Centers Drive Surge in Natural Gas and Solar Energy Demand
Artificial intelligence (AI) data centers are dramatically increasing electricity demand, outpacing traditional data centers by a wide margin. A server rack in a conventional data center consumes 5 to 10 kilowatts, while AI data center racks require 40 to 100 kW, according to Hanwha Data Centers. A single AI query uses 10 to 15 times more electricity than a traditional web search. The energy intensity of these facilities is also far greater, using 10 to 50 times more energy per square foot than a commercial office building.
Developers are projected to spend $7.6 trillion on AI data centers through 2031, driving a surge in demand for reliable power sources. Natural gas has emerged as a top choice for new data centers, with builders preferring locations near gas pipelines to expedite projects. Parag Nathaney, an energy analyst, noted that large gas-powered generators are currently the most common solution. Companies like GE Vernova, Siemens, and Mitsubishi have seen increased orders for generators and turbines related to data centers.
Renewable energy is also playing a role, with solar generation expected to rise by 21% in 2026 and 18% in 2027 due to data center growth. However, concerns about emissions persist. Kim Lundgren of sustainability consulting firm KLA highlighted that while natural gas is cleaner than coal, methane leaks from transport and pipelines remain a significant climate change driver. The Trump administration has eased regulations to encourage domestic energy production, including natural gas, oil, and even coal, which is seeing a resurgence in some areas.
Nuclear energy is another option being explored, with Constellation Energy investing $1.6 billion to reopen a reactor at the Three Mile Island Nuclear Generating Station to power Microsoft’s AI data centers. Similar partnerships are emerging, such as NextEra Energy and Alphabet/Google’s plans to reopen the Duane Arnold Energy Center nuclear plant. These developments underscore the complex balance between meeting AI’s energy demands and addressing environmental concerns.