Data centers expected to use 4x more electricity by 2035
A new BloombergNEF report predicts that US data centres will consume roughly one-fifth of the country's generated electricity by 2035, a fourfold increase from current levels, driven largely by surging demand for AI computing power. This matters because it signals a dramatic acceleration in energy demand forecasts, with data centre capacity expected to reach nearly 200 gigawatts within a decade, placing further strain on power grids that are already struggling to keep pace with connection requests.
BloombergNEF's new estimate is 83% higher than its own December forecast, and other bodies including EPRI and S&P have similarly revised their projections sharply upwards. Nearly half of the new capacity will go towards AI training and inference, with the US expected to host 64% of AI chips by power demand by 2033. Grids in the PJM Interconnection (Virginia to Illinois) and ERCOT (Texas) will face particular pressure, with data centres taking up 34% and 22% of capacity respectively; PJM has already seen electricity prices rise 76% over the past year amid the strain, prompting one utility to threaten withdrawal from the network. Globally, aggressive AI adoption could add 1,935 terawatt-hours of new demand by 2033 — nearly matching India's entire annual electricity use.
- Data centres may use 20% of US electricity by 2035, quadruple today's level
- AI-driven demand is straining grids like PJM and ERCOT, raising prices
- Global data centre electricity demand could nearly match India's annual usage by 2033
Both sides, in good faith
The strongest fair case each way — we don't pick a winner.
The case for
Advocates of rapid data-centre expansion argue that the computing capacity underpinning AI is a strategic economic and technological asset, and that the United States hosting the majority of AI chip capacity secures leadership in a transformative industry, attracting investment, creating jobs and keeping the country ahead of geopolitical rivals such as China. They contend that utilities and grid operators have overcome comparable step-changes in demand before, that new capacity will ultimately be met through a mix of gas, nuclear, renewables and grid modernisation, and that near-term price pressure is a worthwhile trade-off for the long-run productivity gains AI is expected to deliver across the economy.
The case against
Critics, including many residents and consumer advocates in affected grid regions, argue that ordinary ratepayers are being made to shoulder the cost of a speculative technology boom, pointing to the 76% electricity price rise already seen in PJM territory as evidence that grid strain from data centres is translating directly into household hardship. They contend that forecasts have been revised upwards so sharply and so often that planning bodies cannot reliably size infrastructure, risking either reliability problems or costly overbuilding, and that without stronger safeguards, cost-allocation reform or utilities themselves reconsidering commitments, the burden of AI's energy appetite will fall disproportionately on the public rather than the technology firms profiting from it.