Google has signed new utility agreements with Indiana Michigan Power and Tennessee Valley Authority to deliver demand response capabilities targeting machine learning workloads.
These efforts aim to help grid operators manage rising energy demands by reducing or shifting data center power usage during high-stress periods.
The initiative supports Google’s 24/7 carbon-free energy goal and helps avoid costly infrastructure expansion by making large electricity loads more flexible.
Google is scaling up its efforts to make data centers more energy-flexible through new utility agreements designed to support growing power demands — particularly from AI workloads — while strengthening grid reliability.
The company announced partnerships with Indiana Michigan Power (I&M) and the Tennessee Valley Authority (TVA) to implement demand response capabilities at its data centers. For the first time, these programs will specifically target machine learning (ML) workloads, building on a successful pilot with Omaha Public Power District (OPPD) where power demand was reduced during three grid events last year.
“I&M is excited to partner with Google to enable demand response capabilities at their new data center in Fort Wayne, IN,” said Steve Baker, president and COO of I&M. “As we add new large loads to our system, it is critical that we partner with our customers to effectively manage the generation and transmission resources necessary to serve them. Google’s ability to leverage load flexibility as part of the strategy to serve their load will be a highly valuable tool to meet their future energy needs.”
Demand response — the ability to shift or reduce electricity use during peak periods — allows large electricity users like data centers to connect to the grid more quickly, reduces the need for new transmission infrastructure, and improves overall grid efficiency.
As part of its broader 24/7 carbon-free energy strategy, Google is also working with Centrica Energy and transmission system operator Elia in Belgium, and Taiwan Power Company in Taiwan. These collaborations enable the company to adjust non-urgent compute tasks, such as processing YouTube videos, during high-demand periods to support grid stability.
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Google views flexible demand as essential to bridging the gap between today’s rapid load growth and the slower pace of clean energy deployment. With AI driving substantial increases in energy use, the company sees demand response as a promising tool for managing these loads — particularly in regions with constrained generation and transmission infrastructure.
While this approach is still in early stages and dependent on location, Google notes that integrating ML workloads into demand response expands its potential. “By engaging in long-term resource planning with utility partners like I&M and TVA,” the company stated, “we can integrate flexibility into future grid development alongside Google’s data center infrastructure deployment.”
Google emphasized that while new power generation and transmission projects remain critical, demand response will play a pivotal role in managing AI-driven energy growth. The company reaffirmed its commitment to working with system operators, utilities, and industry stakeholders to align digital innovation with a cleaner, more reliable, and more affordable energy future.
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