
Global real estate investment is rapidly shifting from traditional assets to data centers, driven by escalating AI demand, with 95% of major investors planning increased allocations and significant power demand growth projected. This pivot, however, is creating a substantial funding gap, as the multi-billion-dollar cost of hyperscale AI-driven data center development strains traditional lenders, even as the broader commercial real estate market faces a slower rebound and developers contend with financing constraints.
A significant structural shift is underway in global real estate, with investor capital rapidly pivoting from traditional commercial assets like offices and retail to 'invisible' infrastructure, primarily data centers. This reallocation is driven by surging demand from AI workloads, as evidenced by a CBRE survey where 95% of major investors plan to increase their data center exposure and 41% intend to allocate over $500 million in 2025. The scale of this demand is underscored by Goldman Sachs' forecast for a 50% rise in data center power consumption by 2027, potentially reaching 165% by 2030. However, this boom is creating a critical funding gap. The multi-billion-dollar cost of modern hyperscale facilities—estimated at $12 million per megawatt—is straining the capacity of traditional lenders, with panelists noting that banks are feeling 'challenged' and 'strained' by the sheer volume of capital required, which Boston Consulting Group projects at $1.8 trillion by 2030. This dynamic contrasts sharply with the broader commercial real estate market, where Savills has revised its 2025 investment growth forecast down from 27% to just 8%, citing financing constraints and rising costs for developers.
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