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.

While oil gets the headlines, disruptions to liquefied natural gas (LNG) supply are a more direct threat. LNG is a key energy source for data centers, so price spikes or shortages could derail the massive capital expenditures driving the AI buildout.

While no hyperscale data center is officially operating in the Permian core yet, major players are positioning for a buildout. Chevron is planning a 2.5-5GW power facility with Microsoft as a potential offtaker, validating the thesis of using trapped natural gas to power AI infrastructure.

The race to build power infrastructure for AI may lead to an oversupply if adoption follows a sigmoid curve. This excess capacity, much like the post-dot-com broadband glut, could become a positive externality that significantly lowers future energy prices for all consumers.

For years, the tech industry criticized Bitcoin's energy use. Now, the massive energy needs of AI training have forced Silicon Valley to prioritize energy abundance over purely "green" initiatives. Companies like Meta are building huge natural gas-powered data centers, a major ideological shift.

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).

Unlike the globally priced oil market, the U.S. natural gas market is more regionally driven and benefits from significant domestic production. This structure makes it more resilient to international conflicts and price volatility. For power-intensive AI data centers, this translates to more stable and predictable energy costs, providing a key operational advantage.

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.