In the era of generative AI and increasingly complex large language models (LLMs), tech companies are competing not only in algorithmic innovation but also in infrastructure performance. One of the biggest emerging challenges is the surge in energy demand and the resulting pressure on data center power supplies.
Traditional electrical grid connections are often not powerful enough, and building new on-site power plants is costly, complex, and time-consuming. As a result, some data centers are turning to an unconventional aviation-inspired solution — repurposed gas turbines that once flew in airplanes but now generate hundreds of megawatts on the ground.
ProEnergy, a U.S.-based energy company, reports that it has supplied 21 turbines providing over 1 gigawatt of power, designed to act as “bridge energy” solutions for five to seven years until full grid connections are ready.
But why jet turbines specifically? They’re lighter, faster to deploy, and can be brought online in a fraction of the time required to secure new grid access — a process that can take 8 to 10 years. Meanwhile, building out transmission infrastructure often faces delays, local opposition, and lengthy permit procedures, pushing the AI industry to seek more immediate alternatives.
However, these turbines are far from a perfect fix. They’re scarce, and converting them from aviation to stationary use takes time. There are also environmental and logistical concerns: What about the resulting CO₂ emissions? Could the fuel supply chains required to keep these turbines running disrupt existing systems?
In the long term, the more sustainable path likely lies in investing in renewable energy sources — such as wind, hydro, and solar power — that can provide cleaner, more reliable, and cost-effective electricity to meet the growing energy appetite of artificial intelligence.