Examines how AI-era load growth collides with the public rulebook for electricity. These articles focus on federal and state regulation, interconnection, reliability jurisdiction, rate design, cost allocation, consumer protection, planning obligations, and the question of when private infrastructure becomes a public responsibility.
AI data centers are exposing gaps in U.S. power regulation. Verified large-load governance—milestone-based forecasting, cost-causation tariffs, flexible service classes, operational visibility, and coordinated oversight—can reduce cost and reliability risk.
Morgan Bazilian
AI data centers are pushing FERC to confront the Shadow Grid, where private power, co-located generation, and hyperscale load blur into public grid obligations, forcing a shift from queue chaos to coordinated infrastructure governance.
Brandon Owens
The White House AI framework accelerates infrastructure at unprecedented speed—but exposes 10 systemic risks, from rising grid fragmentation and cost shifting to reliability, market and governance gaps, as a “Shadow Grid” emerges outside traditional oversight.
Brandon Owens
State and federal policies are opening regulatory seams that let large AI data centers build off-grid power, often gas-fueled, outside traditional utility oversight. Clean-energy mandates bind the grid, not private systems—creating a parallel “shadow grid” with emissions and ratepayer risk.
Brandon Owens
AI-driven digital loads are reshaping not just how much electricity the grid uses, but how it behaves. Traditional tariffs price magnitude and timing, not volatility. Aligning rates with demand behavior—without mandates—may be the next quiet evolution in cost-of-service regulation.
Brandon Owens
States must ensure AI-driven data center growth strengthens—not strains—the grid. Fair pricing, consumer protection, and community reciprocity can align private innovation with public equity, turning energy demand into shared resilience.
Brandon Owens