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Power constraints for AI are boosting backlogs at GE Vernova and Eaton
Electric Power Research Institute projections say data centers could consume up to 17% of total U.S. electricity by 2030, intensifying demand for grid equipment and power hardware.
AI deployment is no longer limited by semiconductor supply, instead hinging on access to raw electrical capacity, according to MarketBeat Ratings. As hyperscalers expand data center footprints, they face physical constraints that cannot be solved with software.
MarketBeat Ratings says investors are rotating toward electrification beneficiaries like GE Vernova and Eaton as strong earnings visibility is supported by multi-year backlogs and shifts in pricing power toward manufacturers. The outlet frames the move as investors shifting from highly valued software pure plays into the physical power components needed to keep server farms running.
The story also points to U.S. grid limitations, citing Electric Power Research Institute projections that data centers could consume up to 17% of total U.S. electricity by 2030. It adds that delays in utility interconnection queues are pushing operators to pursue behind-the-meter solutions.
MarketBeat Ratings links that structural shift to heightened demand for hardware including transformers, switchgear, liquid-cooling systems, and heavy-duty gas turbines, arguing that when demand exceeds manufacturing capacity, suppliers gain leverage over revenue and margins.