Crusoe Cloud located a massive AI data center in West Texas because the area has so much wind and solar power that prices frequently go negative. Transmission bottlenecks mean renewable producers must often shut down, creating a unique opportunity for energy-hungry data centers to co-locate and absorb the stranded, ultra-cheap power.

The demand for electricity from AI is growing faster than the grid's bureaucratic capacity to expand. Doomberg predicts most new data centers will need to generate their own power, likely from natural gas, to bypass connection bottlenecks and avoid causing retail electricity price spikes for consumers.

The massive electricity demand from AI data centers is creating an urgent need for reliable power. This has caused a surge in demand for natural gas turbines—a market considered dead just years ago—as renewables alone cannot meet the new load.

To overcome energy bottlenecks, political opposition, and grid reliability issues, AI data center developers are building their own dedicated, 'behind-the-meter' power plants. This strategy, typically using natural gas, ensures a stable power supply for their massive operations without relying on the public grid.

IREN builds data centers in locations like West Texas that have massive, underutilized wind and solar capacity due to transmission bottlenecks. By co-locating, IREN arbitrages this stranded, low-cost renewable power by converting it into high-value compute directly on-site.

Contrary to the renewables-focused narrative, the massive, stable energy needs of AI data centers are increasing reliance on natural gas. Underinvestment in grid infrastructure makes gas a critical balancing fuel, now expected to meet a fifth of the world's new power demand (excluding China).

The public power grid cannot support the massive energy needs of AI data centers. This will force a shift toward on-site, "behind-the-meter" power generation, likely using natural gas, where data centers generate their own power and only "sip" from the grid during off-peak times.

Analyst Doomberg explains a counter-intuitive market dynamic: US shale wells produce both oil and natural gas. When high oil prices spur more drilling, it creates a glut of natural gas as an unwanted byproduct. This drives down gas prices, making energy cheaper for the AI data centers that rely on it.

The urgent need for AI compute capacity is outpacing grid upgrade timelines, which can take 3-5 years. In response, hyperscalers are installing "behind the meter" power solutions—often less-efficient, simple-cycle natural gas generators—as a pragmatic way to get data centers operational years faster than waiting for utility connections.