Machine Center: The AI-Driven Transformation of Data Center Investment

Data centers have evolved from niche infrastructure into one of the most sought-after institutional investment classes.

The sector recorded more than $70 billion in M&A transactions in 2024 alone, including Blackstone’s record-breaking $16 billion acquisition of AirTrunk, signaling unprecedented institutional appetite for digital infrastructure.[1] McKinsey projects companies will need to invest $5.2 trillion globally in data center infrastructure by 2030 to meet AI demand, with the US requiring $1 trillion in capital expenditures over the next five years.[2]

These estimates raise a central question for institutions: do data centers warrant strategic allocation, and do investors have the scale, expertise, and capital to execute in what now functions more like large-scale infrastructure than traditional real estate?

Rapid growth is undeniable, but it also brings material constraints and unknowns—particularly around power availability, technology pathways, and regulatory responses—that call for a candid, risk-aware approach from the outset.

The transformation reflects a fundamental shift in how society creates, processes, and stores information. US data center power consumption is