AI Data Centers Turn to Converted Jet Engines to Bypass Grid Delays
Facing multi-year delays for electrical grid connections, artificial intelligence data center operators are deploying repurposed aircraft jet engines to generate their own power.
Artificial intelligence infrastructure is pressing hard against physical limits, particularly when it comes to electrical power. As grid operators and equipment manufacturers grapple with massive backlogs, data center developers are finding unconventional ways to keep their facilities energized. According to recent reports, some operators are turning to retired aircraft jet engines modified to run on natural gas to circumvent long waiting lists for conventional power sources.
While these repurposed engines are not viewed as permanent installations, they offer a vital advantage: speed. Grid connections can take many years to establish in high-demand regions, creating massive bottlenecks for the AI industry.
The Race for Rapid Energy Solutions
Traditional power infrastructure timelines simply cannot match the pace of the current artificial intelligence buildout. Connecting a 100-megawatt load to the grid in Northern Virginia, for example, typically takes approximately seven years. Meanwhile, major power generation equipment makers indicate that the bulk of new capacity may not come online until 2031.
For companies racing to deploy large-scale compute clusters, these delays translate directly into lost business. Microsoft recently withdrew as the anchor customer for a data center project in England after local utility providers stated they could not supply adequate electricity until the early-to-mid 2030s.
To bypass these roadblocks, industry players are increasingly looking to off-grid or localized generation. Companies such as Elon Musk's xAI have adopted temporary or alternative solutions, utilizing converted jet-engine turbines in Mississippi to support operations at the Colossus 2 data center in Memphis. Similarly, OpenAI integrated gas turbines into its Stargate site project in Abilene, Texas, where startup Crusoe ordered multiple converted units from ProEnergy, a company specializing in rebuilding GE engines originally designed for Boeing aircraft. Additional ventures, such as Crusoe's adjustments involving turbine suppliers, highlight the dynamic nature of the current energy procurement landscape.
Environmental and Efficiency Trade-Offs
Using aircraft engines for ground-based power generation is not without significant drawbacks. Industry experts note that these converted units are considerably less efficient and produce more emissions than turbines specifically engineered for conventional natural gas power plants. Generating an equivalent amount of electricity requires a larger number of these units.
Consequently, many analysts view this trend as a temporary workaround rather than a long-term standard. Environmental and efficiency concerns are expected to take center stage as the industry matures over the next couple of years, particularly as political pressures—including encouragement from the Trump administration for data centers to produce their own electricity—continue to shape the regulatory environment.
What it means for developers
While hardware providers secure power through heavy industrial machinery, software and application builders face a different kind of infrastructure challenge: managing API costs and maintaining access to cutting-edge language models. Developers can try top AI models cheaply through one API at https://apixoai.online, simplifying integration across major models without navigating complex multi-vendor agreements.
Source: Data centers are turning to old jet engines as the wait for power grows — TechCrunch AI. Written by the Apixo team from that report.
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