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Artificial intelligence (AI) is driving massive investments in data-center development. Data-center demand generally falls into three categories: non-AI demand, AI training, and AI inference. As enterprises increasingly incorporate AI into their operations, much of the resulting demand is expected to come from inference workloads, which are projected to grow at the fastest pace in the coming years and represent 43% of total data center demand in 2030.

Importantly, AI training and AI inference workloads carry distinct infrastructure requirements that have contributed to a degree of bifurcation within the data-center landscape. Companies in the Real Estate sector have exposure to both hyperscale data centers, which tend to house training workloads, and network-dense colocation data centers, which tend to house inference workloads and support direct interconnection between customers.

We remain favorable on the Data Center Real Estate Investment Trusts (REITs) sub-sector and believe investors should understand the differing infrastructure requirements, related business models, and potential risk and return characteristics of different types of data centers. More specifically, we view network-dense colocation assets as differentiated platforms with leverage to the monetization of AI through enterprise adoption.

Each asset class has its own risk and return characteristics. The level of risk associated with a particular investment or asset class generally correlates with the level of return the investment or asset class might achieve. Stock markets are volatile. Stock values may fluctuate in response to general economic and market conditions, the prospects of individual companies, and industry sectors. Sector investing can be more volatile than investments that are broadly diversified over numerous sectors of the economy and will increase a portfolio’s vulnerability to any single economic, political, or regulatory development affecting the sector. This can result in greater price volatility. Real estate has special risks including the possible illiquidity of underlying properties, credit risk, interest rate fluctuations and the impact of varied economic conditions.

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