For the United States to lead the world in AI, we must make substantial investments in computing power and electricity that make it possible to build AI in America. As technology evolves, the required resources, infrastructure, and regulatory conditions need to change too. That’s why we are releasing a set of policy recommendations to support building the necessary domestic infrastructure to train the world’s most capable AI models in the U.S. and support the broad deployment of AI across sectors. 

Advances in AI, driven by cutting-edge American companies, are reshaping our economy and society. At Anthropic, we see our AI models used every day by American businesses, scientists, educators, governments, and others—in ways that make workers more productive, our economy more prosperous, and our nation more secure.

By acting decisively now we can ensure that the future is built here in America.

Our full list of recommendations can be found in our new report, “Build AI in America.” Below, we summarize its contents.

Energy needs for global AI leadership

Frontier AI model training requires continuous access to firm, reliable power sources, and meeting this goal will require extraordinary U.S. energy capacity across a range of energy technologies. Data centers used to develop state-of-the-art models need stable power access to operate effectively, and given the energy demand for AI development, an “all of the above” approach is required to ensure American AI leadership. This approach will help the U.S. meet immediate energy needs, expand sources of firm power, and maximize opportunities for AI to catalyze emerging energy technologies, like next-generation geothermal and advanced nuclear technologies.

While the U.S. is lagging in bringing energy generation online, China is rapidly building energy infrastructure for AI, having added over 400 gigawatts of power capacity last year compared to the just several dozen gigawatts added in the U.S. This disparity is especially concerning in the context of AI development: we project that 2GW and 5GW data centers will be needed to develop single advanced AI models for Anthropic in 2027 and 2028, respectively. With several other U.S. companies developing frontier AI models, we expect total frontier AI training demands in America to reach 20-25GW in total by 2028. For context, this is roughly twice New York City’s peak electricity demand, and at least as much will likely be needed for serving everyday AI model demand (called “inference”). Put another way, the U.S. AI sector needs at least 50GW of electric capacity by 2028 to maintain global AI leadership.

While the Trump Administration has already taken important steps toward removing barriers by setting ambitious nuclear power targets and accelerating National Environmental Policy Act (NEPA) reviews, to compete with China, it is critical that the U.S. take further action to address regulatory challenges that can delay energy projects.

The U.S. can enable the buildout of large-scale infrastructure for AI training in strategic locations, including by accelerating permitting, supporting targeted transmission projects, and collaborating with utilities to speed up grid interconnection processes. Beyond infrastructure for training AI, we propose broader reforms to support AI deployment nationwide and strengthen supply chains and workforce development. These include accelerating geothermal, natural gas, and nuclear permitting, developing a U.S. Army Corps of Engineers “nationwide permit” for AI data centers to speed Clean Water Act reviews, creating strategic reserves of critical grid components and gas turbines, and expanding technical training programs. Policymakers also have the opportunity through our proposals to keep prices low for ratepayers both through regulatory authority as well as by increasing overall supply.

Two pillars of American AI infrastructure

We propose two strategic pillars that will address the full spectrum of infrastructure challenges—from large-scale training facilities to infrastructure supporting nationwide AI deployment.

Pillar 1: Building large-scale AI training infrastructure

Make federal lands available as options for AI infrastructure construction, avoiding years-long state and local zoning processes;Accelerate NEPA processes for AI infrastructure, including by conducting advance reviews of certain projects;Partner with the private sector to expedite critical power line buildouts and upgrades; andSupport utilities in making key reforms to accelerate interconnection processes, including by deploying AI to boost efficiency. Where critical for national security, leverage existing federal authorities to ensure that AI training infrastructure receives timely interconnections.

Pillar 2: Building broad-based infrastructure for AI innovation nationwide

Accelerate geothermal, natural gas, and nuclear permitting;Establish National Interest Electric Transmission Corridors to speed transmission permitting in areas of significant AI data center growth;Strengthen domestic production of critical grid components and turbines through loan and loan guarantee programs and building strategic reserves of these products; andSupport training, apprenticeship, and entrepreneurship programs for critical energy workers, electricians, and construction workers.

America has the economic strength, technical prowess, and innovative spirit to meet AI's infrastructure challenges. Our recommendations offer a practical blueprint that uses existing federal authorities while cutting through regulatory barriers that have held back energy development for too long.

By partnering across government, industry, and communities, we can build the foundation for decades of American leadership in AI.

Read the full report.