Energy Transition Generative AI

Data Center Demand | Framing the Frenzy 

byCarson Kearl
TeleGeography Submarine Cable Map used under license CC BY-SA 4.0

One of the most common and important questions for the power sector today is what impact artificial intelligence and the data centers needed to generate it will have on energy consumption. AI is quite unlike any energy challenge we’ve seen, and it is a key part of why 15 consecutive years of near-flat power consumption in the U.S. is about to come to an end.

Some of the biggest uncertainties we see:

  • How will technological efficiency gains offset potential load growth?
  • If generative AI is achieved, how much faster will power supply have to grow?
  • What energy technologies are fit to meet this unprecedented source of demand?
  • Where will these facilities be cited, and will they elect to go behind the meter?

In our view, rapid technological innovation like Nvidia’s new Blackwell chip design (which would have consumed 75% less power to train ChatGPT4) and a mystical level of cooperation between federal bodies, regulators, AI companies and energy suppliers is a minimum requirement to allow for the rapid deployment of these facilities. The most readily available power supply will come from gas-fired generators. However, if emissions are as great a concern as the Magnificent Seven group of tech companies claims, the only viable paths forward to achieve zero-emissions and triple redundancy will be the accelerated development of advanced baseload supply solutions, such as nuclear and geothermal.

Research Highlights

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Picture of Carson Kearl

Carson Kearl

As an Analyst on the Energy Transition Research team at Enverus, Carson is the lead on data centers and advanced energy technologies. He was previously an analyst on the macro team and has additional experience advising large industrial consumers on their energy consumption. His education in economics at the University of Alberta focused on industrial organization and power markets.

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