Last summer, Wells Fargo projected that the demand for power to support artificial intelligence (AI) will surge by 8,050% by 2030, increasing from 8 terawatt-hours (TWh) in 2024 to 652 TWh.
Most of this demand is expected to come from AI training, which is projected to reach 40 TWh by 2026 and 402 TWh by 2030. The power demand for AI inference is also anticipated to accelerate toward the end of the decade.
In August 2024, Amanda Peterson Corio, Google's global head of data center energy, was interviewed during an episode of the U.S. Department of Energy’s Grid Talk podcast.
In the interview, she discussed how Google's data centers consume a significant amount of electricity, prompting the tech giant to participate in the ongoing energy revolution.
In early August 2025, Indiana Michigan Power, a subsidiary of American Electric Power, announced that it had filed a special joint contract with Google to address the utility’s capacity needs through clean energy generation.
This contract aims to provide reliable and affordable service to all customers.
According to the press release, by participating in this program, Google would be able to reduce or shift its electricity demand, performing non-urgent tasks during times when the electric grid experiences less stress.
This initiative is designed to minimize peak load during periods of high energy demand, similar to programs currently offered for residential and commercial/industrial customers.
As a large customer, Google’s involvement enhances Indiana Michigan Power’s ability to manage electricity demand during peak times, ultimately helping to lower overall energy costs.
The Tennessee Valley Authority (TVA) recently announced a partnership to expand on a 2019 agreement, aiming to provide carbon-free renewable power for Google’s data centers in Tennessee and Alabama.
As the third-largest electricity generator in the U.S., TVA operates over 16,000 miles of transmission lines and serves 10 million people across a seven-state region.
Data Center
a three-story urban townhouse transformed into a small data farm, with the ground floor dedicated to servers, the second floor housing networking equipment, and the top floor serving as a community space for education on data technology and AI.
Earlier this year, the American Public Power Association reported that Goldman Sachs Research forecasts a 50% increase in global power demand from data centers by 2027, potentially rising as much as 165% by the end of the decade compared to 2023.
Goldman Sachs also highlighted that large hyperscale cloud providers and corporations developing extensive language models for natural language processing require significant amounts of information and power-intensive processors for training.
Currently, the global data center market consumes about 55 gigawatts of power, with cloud computing workloads accounting for 54%, traditional business functions (like email and storage) at 32%, and AI workloads constituting 14%.
As demand for power from data centers grows, the electric grid will need approximately $720 billion in spending through 2030.
In June 2025, AutoGPT.net, a leading source for breaking news and expert insights on artificial intelligence, published a list of the top 20 AI energy companies transforming the industry.
These companies are leveraging AI to lower carbon emissions and enhance the reliability of clean energy sources such as wind and solar.
The energy sector has become better at predicting energy demand, making renewable resources more accessible by balancing supply and demand while improving grid reliability to reduce power outages.
AutoGPT describes AI as the “brain” of the energy industry.
The top AI energy companies include Siemens Energy, General Electric (GE), Shell AI, BP AI, ExxonMobil AI solutions, Tesla Energy, Iberdrola, Schneider Electric, Enel, Repsol, Duke Energy, E.ON, NextEra Energy, National Grid, Engie, Envision Energy, Xcel Energy, Dominion Energy, Ørsted, and the EDF Group.
Seeking Alpha, a financial services company, noted that growing electricity demand is prompting utilities to invest significantly in grid modernization initiatives.
These efforts involve substantial capital costs, partially funded through significant rate hikes.
Such infrastructure investments are vital for replacing aging systems and meeting the soaring demand from data centers, underscoring the partnership between major tech companies and energy providers.
Moreover, Nvidia and AMD have seen their semiconductor technologies increasingly integrated into nuclear applications, energy management, and radiation detection systems, highlighting the strong relationship between AI and the utilities sector.
Noteworthy AI-utility agreements include a landmark contract between Meta and Constellation Energy, signed in early June, which guarantees nuclear energy for Meta’s data centers.
Additionally, Amazon has secured a contract for 1.9 GW from Talen Energy’s Susquehanna atomic station to support AWS facilities in Pennsylvania.
Recently, Matt Sage shared on social media the importance of reducing power usage in AI data centers during times of grid strain.
He emphasized that Google’s decision to implement this strategy is significant given the rapid growth in size and power demand of data centers.
The AI industry is currently valued at $242 billion, projected to reach $584 billion by 2032.
Utilities are struggling to keep up with this growth and face challenges in passing on billions in additional costs to consumers.
For instance, I&M’s $1.3 billion cost recovery plan was rejected in court.
Google's “back-down” system temporarily halts non-urgent computing tasks, such as processing a YouTube upload, and can redirect these tasks to other data centers.
According to Sage, this method represents more than just minor operational adjustments—it serves as a serious warning.
If the growth of AI and cloud computing remains unchecked, it could create bottlenecks in the electric grid, resulting in lost productivity and increased long-term costs.
Sage suggests that the clear solution is to significantly expand energy storage capacity.
Energy storage acts as a safeguard for uptime; with sufficient battery capacity, data centers could operate smoothly during peak demand periods without needing to throttle services.
Therefore, energy storage is not only crucial for clean energy initiatives but also an essential component of investing in AI and digital infrastructure.