AI Demand Drives Massive Power and Infrastructure Investments
Industrial power and technology companies are expanding capacity and partnerships to address critical electricity and cooling bottlenecks caused by surging AI data center demand.
The rapid scaling of artificial intelligence applications is creating severe infrastructure bottlenecks, forcing hyperscalers and data centers to scramble for long-term power and cooling solutions. BlackRock estimates that 148 gigawatts of additional power capacity will be required by 2030 to meet this demand, while firms like Fidelity and Janus Henderson report that supply for compute, memory, and cooling cannot keep pace with scaling needs.
Industrial power companies are capitalizing on this shortage. GE Vernova has accumulated a $76 billion backlog for heavy-duty gas turbines and grid equipment, reporting a 106% increase in organic equipment orders during the first quarter of 2026. Similarly, nVent Electric raised its 2026 organic sales growth outlook to 21%-23% in May 2026, driven by liquid-cooling collaborations with Nvidia.
Technology providers are also forming strategic alliances to stabilize the AI buildout. Hewlett Packard Enterprise expanded its partnership with ScanSource on July 1, 2026, to integrate networking solutions. Simultaneously, Vultr selected Hewlett Packard Enterprise and Nvidia for large-scale deployments using NVIDIA GB300 NVL72 hardware. In the energy sector, Cummins Inc. recently secured a prime power award with Circe Energy to support high-performance computing data centers in West Texas.
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