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Data Centers as an Asset Class: The Investment Case for GCC AI Infrastructure

Authors: Adya, Chennakeshav;

Data Centers as an Asset Class: The Investment Case for GCC AI Infrastructure

Abstract

For the allocator, the artificial intelligence (AI) boom has created a new real-asset class: data centers, the facilities that house the computation on which AI runs. This paper makes the investment case for data centers as an asset class for Gulf Cooperation Council (GCC) family offices and institutional investors, complementing a companion paper that addressed their financing. Using an indicative dataset calibrated to 2026 conditions, it positions data centers within the real-asset spectrum, sets out the forms of investment from direct ownership through platforms to listed exposure, examines the return drivers and the distinctive risks, and develops a framework for an allocator to access the asset class. It finds that data centers offer an attractive combination of contracted, long-lease income, capital growth driven by AI demand, and relatively low correlation to the economic cycle, but that they carry distinctive risks, technology obsolescence and power dependence, that distinguish them from conventional real assets and that an allocator must understand. The investment case is strong for an allocator that can access quality, well-contracted assets and that understands and prices the distinctive risks. Three indicative case studies, a sensitivity analysis, an international comparison and an implementation roadmap support the analysis, which is intended for GCC allocators considering an allocation to data centers.

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