The Outlook for Data Center Power Demand as AI Token Use Grows

数据中心电力需求的前景,随着人工智能代币应用的扩大而增长。

Goldman Sachs Exchanges

2026-09-01

32 分钟
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Global data center power demand could rise 170% by 2030 from 2025 levels according to Goldman Sachs Research’s Brian Singer and Carly Davenport. They joined hosts Allison Nathan and George Lee on the Goldman Sachs Exchanges podcast to  discuss how data centers will source that power, the key bottlenecks, and the impact of growing pushback from some local communities.  Key takeaways:  The rise in power demand from AI more broadly is forecast to be the equivalent of adding another Japan to the world’s power consumption by 2030 compared to the start of 2024.  Goldman Sachs Research sees seven key binding constraints for data center power today including price, policy, and people. Delays for connecting data centers to regional US power grids are as long as seven years.  The Mid-Atlantic region should remain the largest US data center power market until at least 2030, but the Midwest is set to overtake Texas for second place.   The opinions and views expressed herein are as of the date of publication, subject to change without notice, and may not necessarily reflect the institutional views of Goldman Sachs or its affiliates. The material provided is intended for informational purposes only, and does not constitute investment, legal, or tax advice, a recommendation from any Goldman Sachs entity to take any particular action or be used as a basis for any other investment decision, or an offer or solicitation to purchase or sell any securities or financial products. Any forward-looking statements, case studies, computations or examples set forth herein are for illustrative purposes only. Past performance is not indicative of future results. Neither Goldman Sachs nor any of its affiliates make any representations or warranties, express or implied, as to the accuracy or completeness of the statements or information contained herein and disclaim any liability whatsoever for reliance on such information for any purpose. Each name of a third-party organization mentioned is the property of the company to which it relates, is used here strictly for informational and identification purposes only and is not used to imply any sponsorship, affiliation, endorsement, ownership or license rights between any such company and Goldman Sachs. This material should not be copied, distributed, published, or reproduced in whole or in part or disclosed by any recipient to any other person without the express written consent of Goldman Sachs.  Disclosures applicable to research with respect to issuers, if any, mentioned herein are available through your Goldman Sachs representative or at http://www.gs.com/research/hedge.html.  A transcript is provided for convenience and may differ from the original video or audio content. Goldman Sachs is not responsible for any errors in the transcript.  Date of Recording August 12, 2026.  © 2026 Goldman Sachs. All rights reserved.  Learn more about your ad choices. Visit megaphone.fm/adchoices
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  • Put in perspective, what is AI doing from a power demand perspective?

  • It's adding the power equivalent of the whole country of Japan, which is the number five power consuming country.

  • So this is really significant.

  • The last time we sat down to talk about AI and power, the debate was whether the grid could handle it.

  • That question has now been answered in basically the least comforting way possible.

  • Partly, unevenly, and expensively.

  • Welcome back to AI Exchanges.

  • I'm Alison Nathan, and I'm here together with George Lee, the co-head of the Goldman Sachs Global Institute.

  • Together, we're co-hosting a series of episodes exploring

  • the rise of AI and everything it could mean for companies, investors, and economies.

  • George, great to see you again.

  • Great to be here.

  • So, George, let's first set the table for people who have followed this series.

  • When we first covered this topic, the shorthand was basically that AI would drive a step change

  • in data center power demand after nearly two decades of essentially flat electricity load.

  • But since then, demand forecasts have gone up again.

  • Even as we've discussed many times, models have become more efficient.

  • Megawatts and towards what I think of as all the Ts.

  • We have turbines, transformers, transmission and tradespeople.

  • So new constraints entering the picture and the politics have arrived.