Tag: Energy Policy

  • Powering the AI Revolution

    Why America’s Data Center Future Depends on the Electrical Grid

    America’s race to lead the artificial intelligence revolution will not be won by semiconductor technology and investment alone. It will also depend on where data centers are built, whether the electrical grid can deliver the power they need, and whether communities trust the decisions being made in their backyards.

    Artificial intelligence is rapidly becoming one of the most important technologies shaping America’s economic and national security future. Companies are investing billions of dollars in advanced computing infrastructure, developing increasingly powerful AI models, and building enormous data center campuses to support the next generation of artificial intelligence.

    But there is a fundamental problem that deserves much more attention: AI cannot scale without electricity, and electricity cannot be delivered without adequate infrastructure.

    The United States may have world-leading technology companies, advanced semiconductor manufacturers, and enormous investment capital. However, none of these advantages guarantees that the country can build and operate enough AI data centers to maintain its competitive position.

    The challenge is increasingly about energy availability, grid location, transmission infrastructure, and reliability.

    As we discussed in our recent article, America Won’t Lose the AI Race to China’s Chips. It Will Lose It to Distrust, America’s ability to lead in artificial intelligence will depend on more than technological innovation. It will also depend on whether the country can build the physical infrastructure required to support that innovation while maintaining public confidence.

    The AI Infrastructure Problem Starts With Electricity

    Modern AI data centers are fundamentally different from traditional commercial buildings.

    They house thousands of specialized processors, high-performance networking equipment, advanced cooling systems, and supporting infrastructure. These systems require substantial amounts of electricity, often operating continuously to train AI models and deliver computing services.

    As AI adoption expands, so does the demand for computing capacity. That creates a corresponding demand for electricity.

    The challenge is that electrical infrastructure cannot necessarily expand as quickly as technology investment.

    A technology company can announce a multibillion-dollar data center project, acquire land, order computing equipment, and begin construction. But if the local electrical grid cannot provide the required power, the project may experience significant delays before it can become operational.

    This creates a new reality for data center developers: securing electricity must happen before construction decisions are finalized, not after the buildings are completed.

    The availability of power should be one of the first considerations in determining where America’s next generation of AI infrastructure is built.

    Grid Location: Building Where Electricity Is Available

    Historically, data center developers have considered land prices, tax incentives, fiber connectivity, proximity to major markets, and access to skilled labor when selecting locations.

    Those factors remain important, but electricity availability is becoming an increasingly important consideration.

    A site may offer inexpensive land and favorable development incentives but still be unsuitable for a large AI data center if the surrounding electrical infrastructure cannot support its requirements.

    Developers must evaluate several factors before selecting a location:

    • Existing generation capacity: Is sufficient electricity available within the regional power system?
    • Substation capacity: Can nearby substations accommodate the additional electrical load?
    • Transmission access: Can electricity be delivered to the property without major infrastructure limitations?
    • Grid congestion: Are existing transmission and distribution systems already constrained?
    • Future expansion: Can the location support additional computing capacity as AI requirements increase?

    The distinction between national electricity generation and locally available electricity is particularly important.

    China has substantially more total electricity-generation capacity than the United States. However, national generation capacity does not automatically mean that electricity is available at every location where a data center might be constructed.

    The same applies to the United States.

    Having sufficient electricity somewhere within a country does not mean that the power can be delivered economically and reliably to a particular data center campus.

    This is why grid location should become a primary consideration in national AI infrastructure planning.

    Transmission Infrastructure: The Bottleneck Between Power Generation and Computing

    Electricity generation is only one part of the equation.

    Power must travel through transmission lines, substations, transformers, and distribution networks before reaching the facilities that consume it.

    These systems require significant investment, careful engineering, regulatory coordination, and time to construct.

    For AI data center developers, transmission infrastructure can become one of the biggest obstacles to completing a project.

    Even when electricity generation is available, existing infrastructure may not have sufficient capacity to deliver the required power.

    Addressing these limitations may require:

    • New high-voltage transmission lines.
    • Substation construction and expansion.
    • Additional transformers and electrical equipment.
    • Improvements to local distribution networks.
    • Coordination between utilities, developers, and regional grid operators.
    • Long-term planning for additional electrical demand.

    These are not minor construction details. They are essential components of the infrastructure supporting America’s AI economy.

    The federal government, state governments, utilities, and private developers must coordinate their efforts to ensure that electrical infrastructure keeps pace with computing demand.

    This is also where the proposed Department of Technology could play an important role.

    As outlined in our article, How Our Proposed Department of Technology Could Supercharge the Stargate Project, large-scale AI infrastructure initiatives require coordination across federal, state, and local governments.

    Energy planning should be part of that coordination.

    Reliability: AI Data Centers Cannot Operate on Uncertain Electricity

    Having access to electricity is not enough. AI data centers also need reliable electricity.

    AI training and inference workloads can involve thousands of processors operating simultaneously. An unexpected interruption in power can disrupt computing operations, interrupt services, and create expensive recovery requirements.

    For companies investing billions of dollars in computing infrastructure, electrical reliability is a business-critical issue.

    Data center developers must consider the resilience of the entire electrical system, including:

    Grid redundancy: Multiple electrical supply paths can reduce the risk associated with individual transmission failures.

    Backup generation: On-site generators can provide emergency electricity when utility service is interrupted.

    Battery energy storage: Batteries can help manage peak demand, provide short-duration backup power, and support grid stability.

    Uninterruptible power supplies: UPS systems provide immediate protection for critical computing equipment during electrical disturbances.

    Microgrids: Properly designed microgrids can integrate utility electricity, on-site generation, and energy storage to improve operational resilience.

    These technologies should be considered part of the original development strategy rather than expensive additions after a project experiences electrical limitations.

    Reliability also has implications beyond individual facilities. Large data center developments must be evaluated in the context of the surrounding electrical system and the communities that depend on it.

    A project should not simply secure enough electricity to operate its own equipment. Its development should also account for the impact of additional demand on the regional power system.

    Energy Storage and Renewable Energy Must Be Part of the Solution

    Expanding electricity generation and transmission will be essential, but the United States should also consider how energy storage and distributed generation can support future AI infrastructure.

    Solar, wind, nuclear energy, natural gas generation, and battery storage can all play different roles in meeting electricity demand.

    The challenge is developing an energy strategy that balances availability, affordability, reliability, and environmental considerations.

    Energy storage deserves particular attention.

    Our proposal for California’s NEM 4.0 emphasizes the importance of battery storage in supporting grid stability, improving energy management, and helping balance electricity supply and demand.

    The same broader principle applies to AI infrastructure.

    Battery systems can help facilities manage periods of peak demand, provide short-duration backup power, and potentially participate in programs that support the electrical grid.

    However, batteries are not a substitute for adequate generation and transmission capacity. They are one component of a larger energy infrastructure strategy.

    The United States should pursue a diversified approach that combines reliable generation, modern transmission networks, energy storage, and responsible demand management.

    The Cost of AI Infrastructure Should Not Be Shifted to Local Communities

    There is another issue that cannot be ignored: who pays for the electricity infrastructure required to support the AI industry?

    New data centers can require substantial investments in electrical infrastructure. Utilities may need to upgrade substations, expand transmission networks, and improve local distribution systems.

    Those investments raise important questions about how costs are allocated.

    If infrastructure upgrades primarily benefit a private data center developer, should ordinary electricity customers bear the financial burden?

    How should utilities account for the additional demand when determining electricity rates?

    What protections should exist to prevent households and small businesses from subsidizing infrastructure built primarily to support large technology companies?

    These questions deserve transparent answers before major development agreements are finalized.

    The public should not be expected to accept higher electricity bills without understanding why those costs are increasing and who is responsible for paying for the infrastructure.

    This is one reason public opposition to data center development should not be dismissed as simple resistance to technological progress.

    As we discussed in our recent analysis of America’s AI infrastructure expansion, communities have legitimate concerns about electricity costs, water consumption, land use, and the lack of transparency surrounding some development agreements.

    A successful AI infrastructure strategy must address these concerns rather than treating them as obstacles to be overcome.

    Public Trust Is an Infrastructure Requirement

    Data center construction is often presented as a private-sector investment that brings jobs, economic development, and technological innovation to a community.

    But these projects can also place significant demands on local infrastructure and resources.

    Residents deserve to know how much electricity a proposed facility expects to consume, whether new transmission infrastructure will be required, how water resources will be affected, and whether existing utility customers could experience additional costs.

    They should also have meaningful opportunities to participate in decisions before projects are approved.

    This is particularly important when government officials negotiate development agreements behind nondisclosure agreements or make decisions without sufficient public input.

    Transparency is not simply a political preference. It is an important part of successful infrastructure development.

    Projects that fail to earn public confidence can encounter opposition, legal challenges, delayed approvals, and even rejection at the ballot box.

    The United States cannot afford to treat public trust as an afterthought while attempting to build the infrastructure necessary for its AI future.

    A Department of Technology Could Help Coordinate America’s AI Infrastructure

    The growing relationship between artificial intelligence, electricity, and national competitiveness highlights the need for more coordinated technology governance.

    Today, decisions involving AI infrastructure can span multiple federal agencies, state regulators, county governments, municipalities, utilities, and private companies.

    Each organization has different responsibilities, priorities, and regulatory requirements.

    The result can be fragmented planning, inconsistent policies, delayed infrastructure investments, and insufficient public accountability.

    The proposed Department of Technology offers a framework for addressing some of these coordination challenges.

    A federal Secretary of Technology could help coordinate national AI infrastructure priorities, cybersecurity standards, and long-term technology planning.

    State technology leaders could work with utilities, regulators, and regional stakeholders to identify electrical infrastructure needs and coordinate development priorities.

    County and municipal technology leaders could help ensure that local communities have access to relevant information and meaningful opportunities to participate in decisions affecting their infrastructure.

    This approach would not replace the responsibilities of existing utility regulators or energy agencies. Instead, it would provide an additional framework for coordinating technology development with the infrastructure required to support it.

    The goal should be straightforward: make it easier to build the infrastructure America needs while ensuring that development remains transparent, accountable, and beneficial to the public.

    Conclusion: America’s AI Future Depends on Its Ability to Deliver Power

    The competition to lead artificial intelligence is increasingly becoming a competition to build the physical infrastructure that makes advanced computing possible.

    Semiconductors, software, research, and investment remain essential. But they cannot compensate for insufficient electrical generation, inadequate transmission infrastructure, or unreliable power delivery.

    Grid location determines whether a data center can access the electricity it needs.

    Transmission infrastructure determines whether that electricity can reach the facility.

    Reliability determines whether the facility can operate consistently.

    And public trust determines whether communities and governments will support the continued expansion of this infrastructure.

    China’s substantial electricity-generation capacity demonstrates the importance of energy resources in the global AI competition. The United States must recognize that technological leadership requires a comparable commitment to modernizing and expanding its electrical infrastructure.

    But building more data centers should not be the only objective.

    America must build them intelligently, locate them responsibly, strengthen the electrical grid, protect consumers from unfair infrastructure costs, and ensure that communities have a voice in decisions that affect their future.

    The AI revolution will run on electricity. The countries that can generate it, transmit it, deliver it reliably, and earn public support for the infrastructure behind it will have a significant advantage in the decades ahead.

    America’s next great technology investment may not be another semiconductor fabrication facility or AI research laboratory. It may be the electrical infrastructure that makes all of them possible.

    Department of Technology believes that technological leadership and public accountability must advance together. Building the infrastructure of tomorrow requires more than private investment. It requires coordinated planning, reliable energy, and public trust.

  • America Won’t Lose the AI Race to China’s Chips. It Will Lose It to Distrust.

    Voters have already rejected data centers at the ballot box in 2026. The officials building this infrastructure are still hiding deals and holding stakes in the companies they oversee.

    Last week, on November 3rd, 2026, voters delivered a verdict on the AI buildout. They weighed nearly 40 data center-related ballot measures across 10 states, and in Edgewater, Florida, over three-quarters of voters approved a ban on new data centers. This week, ProPublica reported that our United States Secretary of the Interior, Doug Burgum is leading the push to put data centers on public lands while holding between $18.1 million and $64.4 million in AI-company investments, according to an analysis by the advocacy group Save Our Parks.

    Our United States Secretary of the Interior, Doug Burgum says any suggestion that his decisions are driven by personal investments is false. But lawyers told ProPublica his holdings appear to be acceptable under current law. That is the real scandal. If an official can steer national AI policy while holding a stake in the industry he is steering, the problem is the law, not just the official.

    The argument of this piece is simple: America will not lose the AI race to foreign chips. America will lose it to its own distrust, unless the people building our AI infrastructure are accountable to the people who live next to it.

    A Lead That Depends on Power and Public Trust

    The United States still dominates the hardware and capital side of AI. Global data center capacity is projected to grow by 97 GW between 2026 and 2030, effectively doubling, and that buildout could require $3 trillion in investment. China, meanwhile, is closing the capabilities gap and training a large share of the world’s AI researchers.

    Chips are no longer the binding constraint. Energy and public consent are. BloombergNEF estimates a 63 GW gap between what AI chip shipments imply the U.S. should build by 2033 and what energy constraints will allow. A country that cannot power its data centers, or persuade its citizens to host them, will not win this race.

    Washington DC Has Not Built the Grid

    AI is, at bottom, a question of electricity. A serious national defense strategy would fast-track nuclear baseload, advanced renewables, and modernized transmission lines. Instead, Congress has taken only minimal steps to regulate these facilities, and the cost is landing on aging local utility systems and the people who pay for them.

    The Backlash Is Rational

    Gallup found that 71% of Americans oppose an AI data center in their local area, including 48% who are strongly opposed. A later Heatmap Pro poll put strong support at just 4%, down from 13% a year earlier. This is not simple NIMBYism. A majority of Americans, 59%, expect their electricity bills to rise if a data center opens nearby, and these facilities also draw heavily on local water and grid capacity.

    When officials answer this with dismissal, they deepen the problem. Burgum has blamed the mass rejection of data centers on a foreign psyop. Calling public worry about bills and water a foreign plot cannot win the cooperation of the communities that must host the infrastructure of national power.

    Secrecy and Self-Dealing

    Consider Tucson, a drought-stricken city. Amazon Web Services and a developer spent nearly two years negotiating a $3.6 billion, 290-acre data center campus behind NDAs, keeping the public in the dark about projected water usage. Residents learned the details only after the deal was largely set.

    Tucson is not unusual. In Virginia, 25 of 31 local governments involved in data center development had signed NDAs. In Louisiana, records requests found at least 54 NDAs signed by elected officials. This is the pattern we warned about in our analysis of America’s AI Action Plan: data centers sited without local democratic input.

    The conflicts reach the top, too. ProPublica’s database shows more than 320 members of our Trump administration have ties to Alphabet, with large numbers also tied to Nvidia and Meta. Our Secretary of the Interior, Doug Burgum pledged to divest many of his AI investments, but not his stake in Titan Development, a real estate firm that has handled land acquisitions for data centers in the Southwest. And the administration has not completed any environmental reviews for data centers on public lands.

    This is not a one-party problem, and the rules must not be one-party rules. The standards proposed here should apply to every official in every administration, including all members of Congress, the White House and others.

    Reform is starting. Lawmakers in at least ten states have introduced bills to restrict or ban these NDAs, Pennsylvania’s governor has barred them for agencies under his control, and a bipartisan federal bill, the No Secrets for Data Centers Act, would void NDAs signed by officials acting in their official capacity. Industry has a defense: one developer says NDAs protect officials from insider-trading exposure, since a planned campus can count as material non-public information. That argues for narrow disclosure rules and a limited carve-out for genuine trade secrets. It does not justify blanket secrecy over water, power, and tax breaks.

    “Won’t Rules Slow Us Down?”

    The strongest objection is that accountability will slow the buildout and hand China an advantage. The opposite is closer to the truth. Projects imposed on unwilling communities are the ones being voted down, and secrecy is what turns a zoning question into a ballot-box revolt. Transparency is how projects survive.

    The Fix: Accountability at Every Level

    Our AI strategy is currently shaped by appointed officials, zoning boards, and “AI czars” who answer to executives rather than voters. The framework at Department of Technology proposes a permanent Department of Technology with layered accountability:

    • Federal: a cabinet-level Secretary of Technology, nominated by the President and confirmed by the Senate. That gives one accountable official real authority over national AI policy, cybersecurity, and digital infrastructure, with a public confirmation process where conflicts must be disclosed and divestment pledges can be tested.
    • State, county, and local: elected technology leaders. They face voters, and they would decide questions like whether a data center goes up beside a reservoir.

    An elected state secretary of technology or county technology commissioner cannot easily hide behind a corporate NDA when residents are looking at their utility bills and voting on the next term. A federal Secretary who is vetted, confirmed, and held to strict divestment rules would have far less room to wave away grid concerns.

    As we argued in Stop the Litigation Loop, a national AI strategy works best when elected state and local partners help carry it out. Elected officials can be conflicted too, so the office needs disclosure and divestment rules from day one.

    Four Legal Changes, Now

    1. Treat AI infrastructure as defense infrastructure. Foundational models, sovereign compute clusters, and their dedicated power supply should be formally classified as critical to national defense.
    2. Create an AI conflict-of-interest offense, modeled on war profiteering law. Criminalize officials trading stock, holding options, or receiving deferred compensation from AI companies bidding on or serving federal defense and intelligence contracts, including public land leases, where the official has authority over those decisions. Provide a safe harbor for diversified index funds and qualified blind trusts, so the rule targets real conflicts rather than ordinary retirement savings.
    3. Ban NDAs on public-interest infrastructure. Void any NDA that binds public officials or covers projects using public funds, land, or incentives, with a narrow carve-out for real trade secrets.
    4. Require divestment as a condition of office. Anyone overseeing technology, public lands, or energy policy, including the proposed Secretary of Technology, should divest direct holdings in AI and tech companies before taking office. Violations should be prosecuted as threats to national defense, not settled with ethics fines.

    What Each of Us Can Do

    • Congress: pass the No Secrets for Data Centers Act and adopt divestment rules that cover both parties.
    • Statehouses: enact NDA bans like those introduced in at least ten states, and require public notice before any rezoning or tax abatement for a data center.
    • Voters: ask every candidate, at every level, two questions. Will you divest from AI and tech holdings while in office? Will you refuse NDAs on projects that use public land, money, or water?

    The Choice

    Our adversaries will not be stopped by a nation whose officials hold stock in the contractors they oversee, hide deals from the towns that host them, and brush off voters’ concerns about their own bills. To win the algorithmic cold war, we have to build the grid and earn public trust. We also have to make sure those who write AI policy have no stake in the outcome. The voters have already spoken. Now the law has to catch up.

    Summary

    Seven in ten Americans oppose a data center in their community, and the officials deciding where they go may own a piece of the companies building them.

    Gallup found that 71% of Americans oppose an AI data center in their local area, and last week voters made that opposition official, weighing nearly 40 data center-related ballot measures across 10 states. This week, ProPublica reported that the Interior Secretary, who is pushing to build data centers on public lands, holds between $18.1 million and $64.4 million in AI-company investments, according to an analysis by the advocacy group Save Our Parks.

    Interior disputes the characterization, and lawyers told ProPublica the holdings appear to be acceptable under current law. That last part is the heart of our new article; America Won’t Lose the AI Race to China’s Chips. It Will Lose It to Distrust, which argues that our race will be decided by the power grid and public trust as much as by chips, and that trust collapses when local officials sign NDAs that hide water and power costs from their own residents and when officials hold stakes in the industries they oversee.

    This is not a Republican or Democratic problem, and the rules we propose would cover every official in every administration. Imagine being able to see what your town agreed to before the contract is signed, knowing the people overseeing AI and energy policy have no financial stake in the outcome, and having a vote over whether a data center goes up beside your reservoir.

    That future is within reach: lawmakers in at least ten states have introduced bills to restrict or ban these NDAs, and a bipartisan federal bill, the No Secrets for Data Centers Act, would void NDAs signed by officials acting in their official capacity. What the momentum needs is public pressure, and public pressure starts with people knowing what is happening.

    So please share this article today: post it with one sentence on why it matters to your town, send it to your city council member or state legislator, forward it to a neighbor who pays an electric bill, and ask every candidate whether they will divest from AI and tech holdings while in office and refuse NDAs on projects that use public land, money, or water. The voters have already spoken, so help make sure the law catches up at department.technology/.