Others point out that cost pressures are not limited to server racks. Danish Farki, CEO of Fab Economics, said the AI ecosystem is layered from silicon to software services, creating multiple points where infrastructure costs eventually resurface.
“Cloud service providers are likely to phase in more granular pricing models tailored to customer type across cloud, AI, and SaaS services to absorb costs associated with the White House Energy and Grid Compact,” Faruqui said.
This may not manifest itself as an explicit energy surcharge, but instead surfaces through reduced discounts, increased spending, and premiums for guaranteed capacity and performance.
“Small businesses will feel the impact first, but large strategic customers will remain isolated for longer,” Rawat said. “Ultimately, compactification slows down and reallocates cost pressures, but it doesn’t eliminate them.”
Impact on data center design
The proposal could also accelerate changes in the way AI facilities are designed.
“Data centers will evolve into localized microgrids that combine utility power with higher levels of implementation of on-site generation and battery energy storage systems,” Faruqui said. “AI data centers will require grid interaction design, requiring intelligent high-speed switching gear, increased battery energy storage capacity for frequency regulation, and advanced control systems that can manage on-site resources.”
