Dallas-Fort Worth is experiencing a data center boom that's leaving mid-market AI operators, healthcare systems, and financial firms almost entirely shut out. While the region is one of North America's fastest-growing data center markets, colocation vacancy has dropped to an all-time low of 1.8%, and roughly 88% of the more than 700 megawatts currently under construction is already leased before groundbreaking. The result is a structural mismatch between what's being built and who actually needs it.

Why Are Mid-Market Operators Getting Squeezed Out?

The problem isn't a shortage of ambition or investment. It's that new data center developments are being designed around anchor tenants that need tens of megawatts at a time. Mid-market operators typically need one to five megawatts, a requirement that rarely gets picked up by developers focused on hyperscale deals. Even when retail colocation space does become available, it's largely designed for traditional enterprise IT loads, not for the specialized cooling and power requirements of GPU clusters running artificial intelligence workloads.

This creates a three-layer barrier for mid-market buyers. First, deal sizes are too large. Second, the majority of new supply is pre-leased before it even launches, so capacity never reaches the open market. Third, when space does exist, the infrastructure doesn't match the needs of modern AI operators.

"The mid-market has been structurally excluded from the infrastructure buildout happening in DFW. Hyperscalers are building for hyperscale. The minimums are too large, the architecture is shared, and the compliance posture doesn't hold for regulated industries," said Dennis Finster, Chief Executive Officer of EG AI Corp.

Dennis Finster, Chief Executive Officer, EG AI Corp

What's the Real Technical Bottleneck?

The cooling challenge is more severe than most people realize. Traditional air-cooled data halls were built to handle racks drawing 5 to 15 kilowatts, and even optimized air-cooling designs fail beyond 30 to 40 kilowatts per rack. Modern GPU servers, however, push rack densities to 80 to 130 kilowatts, sometimes higher. This fundamental mismatch means that existing retail colocation facilities simply cannot support next-generation AI workloads, no matter how much space is available.

Immersion cooling offers a solution. By submerging servers in a dielectric fluid that transfers heat far more efficiently than air, immersion systems support extreme rack densities while reducing cooling energy consumption and eliminating evaporative water use. For companies running continuous AI training or inference, this translates to more compute power per square meter and much more predictable thermal performance.

"Immersion cooling isn't a feature, it's an architectural decision that determines what the facility can actually do. Air-cooled environments have a ceiling on rack density that makes them structurally incompatible with next-generation GPU workloads," explained Conrad Eaton, Chief Revenue Officer of EG AI Corp.

Conrad Eaton, Chief Revenue Officer, EG AI Corp

How to Address the Mid-Market Data Center Gap

• Single-Tenant Architecture: Build dedicated facilities for individual operators rather than shared colocation halls, providing complete data isolation and avoiding third-party data exposure, which is essential for HIPAA, SEC, and fintech compliance workloads.
• Immersion-Cooled Design: Engineer facilities from the ground up with immersion cooling systems that eliminate the thermal ceiling of air-cooled systems and support GPU densities of 80 to 130 kilowatts per rack.
• Compliance-First Infrastructure: Design physical security perimeters, audit boundaries, and dedicated power and network paths specifically for regulated industries, making compliance a property of the building itself rather than a negotiated afterthought.

For regulated industries like healthcare systems and financial services firms, thermal capacity is only part of the problem. Frameworks such as HIPAA (Health Insurance Portability and Accountability Act), GLBA (Gramm-Leach-Bliley Act), and PCI DSS (Payment Card Industry Data Security Standard) require demonstrable control over physical access, audit boundaries, and data environments. In a shared colocation hall, those boundaries are negotiated around other tenants' operations, creating complex auditing processes that many compliance teams find unworkable.

A small number of projects are beginning to target this gap. In Dallas, EG AI Corp broke ground in late May on a 5,000-square-meter single-tenant, immersion-cooled GPU data center, with completion targeted for 2027. The facility is being built to address the two main bottlenecks: immersion cooling architecture that eliminates the thermal ceiling of air-cooled systems, and a single-tenant model that provides complete data isolation. Similar single-tenant, high-density models are likely to follow in other supply-constrained markets.

While the industry's attention remains fixed on gigawatt-scale hyperscale campuses, the middle market is where regional hospital networks train diagnostic models, where community financial institutions deploy AI under regulatory scrutiny, and where daily applied AI actually takes place. Meeting that demand will require infrastructure built specifically for it, not whatever capacity is left over after hyperscalers secure their anchor leases.