Share of U.S. Electricity Used for AI

Many high-forecast respondents emphasize that tech companies are making unprecedented capital commitments to AI infrastructure: “With the building of data centers and dramatic investments in large-scale infrastructure, such as Project Stargate, alongside policies and executive orders enabling the leasing of federal land for more AI data centers…I absolutely think electricity consumption for AI in the near term will skyrocket.” Others point to the possibility that competition between companies and nations for supremacy in AI may lead to “an explosion in energy usage.” Low-forecast respondents tend to focus more on potentially formidable constraints, particularly when considering “the material and political investments necessary to get significant growth—physical data centers, chips, permitting, water for cooling, transmission lines, etc.”

Many forecasters anchor on institutional projections: “The Boston Consulting Group says 7.5% in 2030 [for data centers]. Bloomberg says 8.6% [for data centers] by 2035…AI-specialized servers accounted for 15% of total global data center demand in 2024. Electricity usage by specialized AI hardware accounted for 11-20% in 2024. Demand implies that a share of AI-related U.S. data center electricity consumption of 50/180=27.8%.”

A common low-forecaster consideration was that “there is a huge amount of scope for efficiency gains [and] things will become more efficient as they scale up,” and several noted that “DeepSeek appears to consume considerably less power” than frontier U.S. models. High-forecast respondents, however, largely don’t believe efficiency improvements will meaningfully reduce overall consumption: “More efficient chips and algorithms will simply lead to more compute going into training and inference.” One argues, “Jevons paradox will surprise on the upside - i.e., even more efficient chips will mean more usage with little savings in terms of energy efficiency.”

Many low-forecast respondents emphasize business model concerns: “The current economics of all of this are obviously not sustainable: we're spending billions of dollars on these data centers in support of AI companies, or AI segments of hyperscalers, that are losing huge amounts of money off their core AI businesses.” Multiple forecasters note “AI will need to begin demonstrating economic and social utility rapidly to justify the investments in physical infrastructure necessary to sustain rapid growth in energy consumption.”

Some high-forecast respondents emphasize that “China is also investing massive amounts in datacenters,” with one writing “there's a chance that we enter an arms race that is mostly determined by who can pump the most electricity into AI.” A low-forecast respondent suggests this dynamic, instead of resulting in U.S. growth, could drive infrastructure offshore: “Major developers will possibly respond by increasingly outsourcing the physical infrastructure of data processing to locales outside of the US—there's no particular reason why models need to be trained inside of U.S. borders where the economic and political expenses are potentially much higher.”

High-forecast respondents typically expect continued returns from scaling: “I think it's more likely than not that transformative superintelligence will have arrived by 2040, in which case almost all knowledge work …will be reliant on the use of AI models.” Whereas low-growth forecasters commonly express that they anticipate diminishing returns: “Unless further scaling leads to qualitative leaps in AI capabilities, the growth in electricity consumption for AI training and deployment is unlikely to be exceptionally rapid;” “We have already seen indications that the limits of scaling may be soon reached.”

Rarely emphasized by high-forecasters, low-forecast respondents frequently pointed out that “while growth in power production will likely be necessary for much growth in AI systems, overall power consumption is the denominator in this calculation, and increased demand from electric vehicles could play a role in growing this denominator” and therefore “data centers' energy consumption will grow in absolute terms, but not so much in relative terms.”