Infrastructure Risk

As a condition for receiving approval, developers must provide a contractual agreement with the local utility company affirming that the local utility company has existing capacity to meet the energy demand of the data center. These “will serve” letters should also include information on whether the utility anticipates needing to invest in additional generation resources and infrastructure to serve the data center.

Note: Cities may need to coordinate with utilities or state-run public utility commissions in order to retain this right.

Despite the push to develop energy infrastructure to meet data center demands, there remains significant uncertainty about whether demand projections will materialize. This introduces significant risk that developers will pull out of deals early, leaving communities to shoulder the costs of infrastructure rapidly built to serve data center needs. States can protect against this risk by instituting strong compliance laws (also referred to as “compliance tariffs”) that insulate ratepayers from the risks of speculation and overprojection.

Develop Separate Rate Classes for Large-Load Customers

A large-load customer should be defined as a customer that uses or is able to use more than 20 megawatts (MW). A separate rate class for these customers should then be established. There are several ways to establish this separate rate class.

In some states, utilities have solicited approval from the Public Utility Commission (PUC) to create a new rate class specifically for data centers (or more broadly “large-load customers,” which are typically defined in such a way to apply almost exclusively to data centers, but designated via the amount of power used).

Advocates could also petition the state PUC to open such a proceeding in situations where the utility has not been proactive. 

Utility rate cases may also provide an opening to advocate for the creation of a separate tariff class for large loads.

Reject Colocation Policies That Enable AI Data Centers to Soak Up Available Energy

In December 2025, FERC announced that PJM Interconnections’s tariff governing the colocation of generation with large loads like AI data centers was unjust due to unclear and inconsistent rates and terms.¹ FERC directed PJM to create transparent, enforceable tariff rules for such arrangements and new transmission service options in order to protect consumers “by keeping electricity costs manageable.”² Moving forward, FERC action can clarify that colocation policies not disproportionately ease barriers for such AI data center projects.

Enshrine the 2024 FERC Order

Enshrine the November 2024 FERC order,³ which determined that shifting existing generation away from the bulk power market to serve a data center is unjust and unreasonable.⁴

Mandate Load Flexibility Programs and Interconnection Requirements

Direct FERC to mandate load flexibility programs and forced curtailment procedures for data centers⁵ and update large-load interconnection requirements to prevent cascading outages.⁶

Compel the Collection and Publication of Energy-Use Data

Direct FERC and/or the U.S. Energy Information Administration (EIA) to compel the collection and publication of energy-use data by data centers, and compel FERC to require disclosure of when power sellers are affiliated with data centers.⁷ 

Note: Although disclosure of water consumption is also important for data center transparency, FERC does not have jurisdiction over water usage. This recommendation should also be accompanied with provisions that assign appropriate authority over water transparency metrics. For more details, see “Require Comprehensive Transparency Mechanisms and Monthly Reporting.”

Revise Cost-Allocation Methodologies

Direct FERC to mandate that regional transmission organizations (RTOs) such as PJM revise their transmission cost-allocation methodologies so that other customers are not subsidizing the construction of transmission lines that are needed solely to serve data centers.

Reject Nondisclosure Agreements in Utility and RTO Proceedings

The federal government should prohibit the use of nondisclosure agreements (NDAs) in utility and RTO proceedings. If that is not possible, condition eligibility for any preferential rate tariffs or access to interconnection queues on not employing nondisclosure agreements related to development deals. 

Correct Misalignment Between Utility Incentive Structures and Public Interest

Direct FERC to undertake a systematic review of transmission incentive adders and to take other steps necessary to correct misalignment of utility incentive structures with the public interest to ensure that utilities are not overbuilding the transmission system in response to underscrutinized load growth projections.

Protect Against Overbuild

Direct FERC to maintain and regularly update a national database of proposed data centers, working closely with utility commissions and regional transmission operators to accurately forecast load increases, predict accurate infrastructure needs, and protect against overbuilds.⁸ 

1. Federal Energy Regulatory Commission, “Fact Sheet: FERC Directs Nation’s Largest Grid Operator to Create New Rules to Embrace Innovation and Protect Consumers,” December 18, 2025, https://www.ferc.gov/news-events/news/fact-sheet-ferc-directs-nations-largest-grid-operator-create-new-rules-embrace. ↩︎
2. Ibid. ↩︎
3. PJM Interconnection, L.L.C., Order Rejecting Amendments to Interconnection Service Agreement, 189 FERC ¶ 61,078, November 1, 2024, https://www.ferc.gov/sites/default/files/2024-11/20241101-3061_ER24-2172-000.pdf. ↩︎
4. Thanks to Public Citizen for this recommendation. See Deanna Noel and Meghan Pazik, “Reining in Big Tech: Policy Solutions to Address the Data Center Buildout,” Public Citizen, December 3, 2025, https://www.citizen.org/article/reining-in-big-tech-policy-solutions-to-address-the-data-center-buildout. ↩︎
5. Ibid. ↩︎
6. Matthew McHale and Hannah Wiseman, Nine Ways to Address the Energy Impacts of AI Data Centers, Vanderbilt Policy Accelerator, January 2026, https://cdn.vanderbilt.edu/vu-URL/wp-content/uploads/sites/412/2026/01/12211201/Nine-Ways-to-Address-the-Energy-Impacts-of-AI-Data-Centers.pdf. ↩︎
7. Thanks to Public Citizen for this recommendation. ↩︎
8. McHale and Wiseman, Nine Ways to Address the Energy Impacts of AI Data Centers. ↩︎