Landowners who have spent years navigating the grid interconnection process for projects like solar or wind are now pivoting. As they near approval, they repurpose their valuable grid connection rights for data centers, which can generate significantly higher financial returns than the originally planned energy projects.

To overcome energy bottlenecks, political opposition, and grid reliability issues, AI data center developers are building their own dedicated, 'behind-the-meter' power plants. This strategy, typically using natural gas, ensures a stable power supply for their massive operations without relying on the public grid.

The long queues for connecting projects to the power grid are misleadingly large. They are often inflated by multiple speculative applications for the same project. The real, viable projects are backed by investment-grade tenants, while many others are merely "PowerPoints" that will never actually be built.

The most critical component of a data center site is its connection to the power grid. A specialized real estate strategy is emerging where developers focus solely on acquiring land and navigating the multi-year process of securing a power interconnection, then leasing this valuable "powered land" to operators.

Despite staggering announcements for new AI data centers, a primary limiting factor will be the availability of electrical power. The current growth curve of the power infrastructure cannot support all the announced plans, creating a physical bottleneck that will likely lead to project failures and investment "carnage."

While semiconductor access is a critical choke point, the long-term constraint on U.S. AI dominance is energy. Building massive data centers requires vast, stable power, but the U.S. faces supply chain issues for energy hardware and lacks a unified grid. China, in contrast, is strategically building out its energy infrastructure to support its AI ambitions.

To secure the immense, stable power required for AI, tech companies are pursuing plans to co-locate hyperscale data centers with dedicated Small Modular Reactors (SMRs). These "nuclear computation hubs" create a private, reliable baseload power source, making the data center independent of the increasingly strained public electrical grid.

Most of the world's energy capacity build-out over the next decade was planned using old models, completely omitting the exponential power demands of AI. This creates a looming, unpriced-in bottleneck for AI infrastructure development that will require significant new investment and planning.

The primary constraint for scaling high-frequency trading operations has shifted from minimizing latency (e.g., shorter wires) to securing electricity. Even for a firm like Hudson River Trading, which is smaller than tech giants, negotiating for power grid access is the main bottleneck for building new GPU data centers.