"Nearly half of respondents (48 percent) cite power access as the biggest scheduling constraint, with grid connection wait times stretching years. In the US, for example, some requests face a seven-year queue, although the US Energy Secretary is taking steps to address this. In Britain, developers similarly report delays requiring substation upgrades worth hundreds of millions. The scale problem is the sheer amount of AI infrastructure currently being planned:"
"Deloitte warned in June that power requred by AI datacenters in the US may be 30 times greater inside a decade with 5 GW facilities already in the planning pipeline. Turner & Townsend recommends on-site generation, energy storage or grid-independent power solutions to support projects, especially for AI facilities. The report's authors propose renewables for energy creation though in reality this is likely to be generators driven by gas-powered turbines."
Supply chain constraints and limited power availability are hampering efforts to scale datacenter capacity for AI workloads. Nearly half of respondents cite power access as the biggest scheduling constraint, with grid connection wait times stretching years in some markets. Some US connection requests face a seven-year queue while UK projects need costly substation upgrades. Planned AI infrastructure demand is vast: disclosed projects could consume tens of gigawatts, equating to millions of households' power. Forecasts indicate power demand from AI datacenters could multiply dramatically within a decade, with multiple multi-gigawatt facilities already planned. On-site generation, energy storage, grid-independent power, and improved cooling supply chains are recommended to mitigate bottlenecks.
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