AI Data Centers Set to Consume 25% of US Electricity by 2030 - Power Becomes the Constraint
AI data centers could consume 24-25% of US electricity by 2030, positioning energy as the primary constraint for hyperscale deployments. This isn't projection - it's already reshaping infrastructure decisions.
Amazon and Meta are securing long-term nuclear and natural gas contracts. The US aims to quadruple nuclear capacity by 2050. Global data center spending is forecast at $7 trillion by 2030, with $1.3 trillion allocated to power infrastructure alone.
The Crypto-to-AI Pivot
Bitcoin miners are repositioning as AI infrastructure providers. Companies like Core Scientific and Bit Digital project mining revenue will fall from 85% of total revenue to under 20% by late 2026. The reason: AI offers more predictable returns than mining's volatility.
The trade-off matters. Bitcoin mining provided grid flexibility - Texas grid operator ERCOT paid miners $31.7 million in 2024 for demand curtailment during peak loads. AI workloads don't curtail. They run 24/7, demanding baseload power that competes directly with other uses.
BlackRock frames this as an "energy war" between AI and crypto. Ireland's data centers illustrate the pressure: electricity consumption from facilities may double by 2026, forcing policy choices about priority access.
What This Means for Enterprise
US electricity demand could rise 75-100% by 2050. For CTOs planning AI deployments, this translates to:
- Location decisions driven by power availability, not just connectivity
- Premium pricing for guaranteed baseload capacity
- Regulatory scrutiny on energy allocation
Some miners are deploying AI-powered grid optimization platforms (GridBeyond reports 8-14% profitability improvements). The irony: using AI to manage the power that AI consumes.
The Infrastructure Reality
The constraint isn't silicon - it's substations. Hyperscalers can buy GPUs. They can't quickly build transmission capacity. Nuclear takes a decade to deploy. Natural gas is faster but faces environmental opposition.
Enterprise teams banking on unlimited cloud scale should plan for power-constrained pricing tiers. The days of assuming infinite compute may be ending. The question isn't whether you can run the model - it's whether you can power it.