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How retrofitting can help win the AI infrastructure race

The need for AI infrastructure is increasing rapidly. By 2030, global data center capacity is projected to nearly double, but the development of new facilities is being hindered by grid limitations, lengthy planning processes, and supply chain setbacks. Consequently, numerous operators are reevaluating the power, cooling, floor-loading, and network capacity that can be provided within current locations.

A carefully planned retrofit can liberate unused capacity by enhancing the particular systems that restrict higher-density workloads: power distribution, cooling, containment, and fiber pathways. However, this method is effective only when the physical constraints of the site are understood prior to commencement.

A comprehensive strategy is needed, where teams must identify and interconnect power, cooling, structural, and network connections. Upgrades should be planned in a systematic manner, considering ongoing operations and known site limitations. The task is not just about improving an existing establishment but ensuring that it can be modernized securely, effectively, and without disrupting its operation.

Retrofitting will be crucial in such cases. The rate at which products or services are brought to the market has become a significant factor that sets operators apart from one another. By early 2026, the total data center capacity in the UK is predicted to be around 2.9GW, and it is necessary to have at least 03GW of AI-ready data center capacity by 2030, which is a three times growth compared to the present.

Operators should not solely depend on new constructions to address this significant increase. It may take multiple years to build a fresh website.

 

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