The inexorable rise of Artificial Intelligence (AI) is forcing a reassessment of the clean energy transition. Training and running AI models are both energy-intensive processes, adding significantly to the electricity needs of data centers. Despite the widespread use of renewable energy and progress to make processes more energy efficient, demand is expected to grow.
AI’s appetite for energy is colossal. Goldman Sachs estimates that around 47 GW of additional power generation capacity will be needed in the U.S. alone by 2030 to meet the burgeoning demand. They predict that some 60% of this new demand will need to be satisfied by legacy energy sources, most likely natural gas, or 3.3 billion cubic feet of additional incremental demand. This forecasted demand is being driven in large part by data centers, the humming engines driving AI, which require massive quantities of dependable power generation rather than relying on inherently intermittent renewables.
