Sunday, November 15, 2026

Goldman Sachs: AI Will Drive 165% Global Data Center Power Surge by 2030, Repricing Energy Assets Worldwide

Goldman Sachs projects global data center power demand will rise 165% by 2030, a surge no existing electricity grid was designed to absorb. A single ChatGPT query consumes roughly 10x the electricity of a Google search, and hyperscalers now rank among the largest grid customers on earth. Utilities with nuclear capacity and proximity to data center clusters are emerging as structural winners across the US, Europe, and Asia.

LM Salvado
LM Salvado

June 23, 2026

This article was written by AI. Published before our source requirement (10 August 2026); sources were not recorded. How we work

Goldman Sachs: AI Will Drive 165% Global Data Center Power Surge by 2030, Repricing Energy Assets Worldwide
Image generated by AI for illustrative purposes. Not actual footage or photography from the reported events.

Goldman Sachs projects global data center power demand will rise 165% by 2030: a surge no existing electricity grid was designed to absorb.1

The scale of AI's energy appetite is stark. A single ChatGPT query consumes roughly 10x the electricity of a Google search.2 Training next-generation large language models requires power equivalent to a small city.2 Microsoft, Amazon, and Alphabet now rank among the largest electricity consumers on the US grid.2

The mismatch is global. Most national grids were engineered for 1-2% annual demand growth.2 The US, Europe, and Asia all face the same constraint: legacy transmission infrastructure cannot absorb an AI-driven demand spike at this speed. In Europe, grid congestion is already pushing data center operators out of Amsterdam and Dublin into lower-density markets. Singapore has imposed capacity moratoriums due to power and land limitations.

Utilities near hyperscaler campuses hold structural pricing leverage worldwide. Power purchase agreements with AI operators are effectively price-inelastic: hyperscalers cannot tolerate outages the way industrial customers can. That asymmetry shifts negotiating power toward the generator.

Nuclear operators carry a particular global advantage. AI companies have designated 24/7 carbon-free power as a procurement requirement, not a preference. Nuclear baseload meets that specification. Intermittent renewables require storage additions that raise effective costs. France, with its nuclear-heavy grid, is emerging as a preferred data center destination for European operators.

In the US, Bitzero Holdings (AIBZ) is among the operators positioning for the AI energy infrastructure opportunity.2 Globally, capital is flowing toward any generator with contracted capacity near major data center hubs: from Northern Virginia to Frankfurt to Tokyo.

The logic is simple: AI energy demand is not discretionary. Hyperscalers have committed multi-year capital programs totaling tens of billions in data center construction. The electricity to run those facilities must come from somewhere. Operators with the right geography, grid interconnection, and generation mix are positioned to capture that demand before interconnection queues tighten further.

For market participants globally, the question is no longer whether AI creates utility upside. It is which operators, in which countries, have the grid position and permitting status to capitalize.

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This is a Via News analysis. It synthesizes signals, events and patterns across our coverage rather than deriving from a single source document, so it carries no external source pointer. Via News is a conduit: where a claim traces to a specific document, we link it. How we source

LM Salvado
LM Salvado

LM Salvado is an AI possibilist: he takes the risks of AI seriously, and still sees the route through them. Founder of Via News Agency, an AI-native newsroom built on full source-traceability, he tracks how AI is reshaping markets, capital, and labor, the quiet shifts that happen before the headlines catch up.

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