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In a groundbreaking simulation, an AI system called Conductor demonstrated how data centers can dynamically adjust power usage to prevent grid overload and support renewable energy integration.
At the end of a tense and scoreless first half of a soccer match between England and Germany, millions of Brits let out a collective sigh and made tea. The surge in electric kettle usage caused a massive spike in electricity demand. National Grid, which manages the UK’s transmission network, was ready. An AI program instructed a data center in London to reduce power consumption from its energy-intensive chips, ensuring there was enough supply to meet the sudden demand.
This scenario wasn’t just a lucky coincidence-it was a carefully orchestrated simulation. In December 2025, engineers tested a new breed of data center designed to be flexible about its electricity needs. The test recreated the energy demands faced by the UK’s grid during a match from the 2020 Euro tournament. The goal was to see how Conductor, an AI system developed by Emerald AI, would have responded had it been operational at the time.
Conductor is the flagship product of Emerald AI, a Washington, DC-based firm leading the charge in making data centers more grid-friendly. This year, Emerald plans to deploy Conductor in a new facility in Virginia’s Data Center Alley, connecting it to the live grid. When overall demand spikes, Conductor will throttle down the power used by the data center while ensuring that critical tasks are still completed on time.

Emerald’s partners on the project include tech giants like Nvidia and Digital Realty. They bill Conductor as one of the world’s first “power-flexible AI factories.” This innovation could ease a significant bottleneck in getting new data centers online: the time it takes to secure approval for, construct, and connect new power plants far exceeds the time needed to build data centers.
PJM, the grid operator in Virginia and the largest in the US, needs eight years to bring new generation online, according to RMI, an energy research and advocacy group. “We need to solve the energy equation,” says Josh Parker, head of sustainability at Nvidia. “AI factory flexibility is the bridge between the incredible demand for AI and the immediate limitations of our energy grid.”
The success of Conductor in this simulation and its upcoming deployment could pave the way for a new era of data center flexibility. As AI demand continues to grow, ensuring that these facilities can operate within the constraints of existing energy infrastructure is crucial. By working together with grid operators and leveraging advanced AI, the tech industry can help bridge the gap between technological advancement and sustainable energy management.
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Want to get a data center online quickly? Give it some flex.
↗ https://www.technologyreview.com/2026/06/16/1138591/data-center-online-quickly-electric-grid-flex
About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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23 June 2026
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