As digital trnssformation accelerates, data centers are becoming the backbone of the digital economy, supporting everything from AI workloads to real-time analytics and autonomous vehicles. McKinsey analysis finds that globally, capital expenditures on data center infrastructure (excluding IT hardware) are expected to exceed $1.7 trillion by 2030, largely because of the expansion of AI, the proliferation of edge computing, and advancements in high-performance computing (HPC). This increasing demand is changing the landscape for energy, real estate, and construction.

To meet the growing demand for data centers—and the power capacity needed—over the next five years, data center campuses will have to expand from providing tens of megawatts (MW) of power to hundreds, even expanding to accommodate a gigawatt (GW) scale (a scale of one gigawatt or more). Recent innovations, including the emergence of distilled and distributed training models for AI, could affect the build-out of data centers and intensify existing industry challenges with data center scale-ups. These new models and increasing compute demand require a reevaluation of the design and construction methods used to build data centers so that stakeholders can capitalize on economies of scale.

Capturing the scale-up opportunity will require data center players across the value chain to adopt new approaches and technologies while learning from other industries that have experienced similar breakthrough moments. This article details how data center stakeholders across the industry can keep up with the digital transformation by adopting innovative designs that will enable data centers to become bigger and faster.

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https://www.mckinsey.com/industries/private-capital/our-insights/scaling-bigger-faster-cheaper-data-centers-with-smarter-designs