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AI infrastructure is now a corporate real-estate decision because computing capacity is constrained by physical assets. A site can have excellent network connectivity and still fail if it cannot secure enough electricity, obtain grid approval, install cooling and electrical systems, or deliver a building on the required date. For many companies, the practical response is not automatically to own a data center. It may be a lease, colocation agreement, cloud contract, energy partnership, or hybrid portfolio in which property, power and IT capacity are planned together.
The change is most visible in large AI campuses, but the planning lesson applies at smaller scales: treat power delivery, property control, permits, construction sequencing and technology deployment as one program rather than separate purchases.
Why is AI infrastructure becoming a real-estate issue?
AI workloads concentrate demand into facilities that run continuously and draw far more power than many conventional enterprise applications. That makes the physical location and legal control of capacity material to an IT roadmap. A company may need a building with contiguous electrical capacity, a credible utility-delivery date, heavy cooling equipment, secure fiber routes and room to expand. Those requirements are negotiated through leases, development agreements, utility contracts and construction schedules, not through software configuration alone.
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CBRE’s U.S. Real Estate Market Outlook 2026 says AI-related occupiers are seeking large blocks of contiguous capacity and that power cost and delivery speed can outweigh connectivity in site selection. Its analysis distinguishes the traditional 12-to-18-month schedule for sub-50-MW buildings from the multi-year schedule associated with campuses above 500 MW. These are market observations, not guaranteed timelines for every project.
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Deloitte’s April 2025 survey of 120 U.S.-based power-company and data-center executives illustrates why the issue reaches the boardroom. In that survey, 72% of respondents called power and grid capacity very or extremely challenging, 65% cited supply-chain disruption and 64% cited security. The same respondent group included 79% who expected widespread AI adoption to increase power demand through 2035. The percentages describe that surveyed population and should not be read as a statistic for every company or country.
How does power availability affect data-center site selection?
Power is useful only when it is deliverable at the required scale, reliability and date. A utility statement that a region has generation capacity is not the same as a firm interconnection agreement for a particular parcel. The site team must establish the path from the transmission or distribution network to the facility, identify studies and upgrades, and understand which party pays for and builds each improvement.
Capacity and delivery date
Ask for evidence of contracted or otherwise demonstrable megawatts, the expected energization date and the conditions attached to that date. CBRE’s 2026 outlook treats the ability to deliver 300 MW or more in under 36 months as a competitive site-selection threshold. It is a competitive benchmark in that outlook, not a universal engineering standard.
Interconnection and transmission work
When a project requires new high-voltage transmission or incremental generation, CBRE says interconnection timelines can extend to 24, 36 or 48-plus months. The range reflects different market conditions and project scopes; it is not a promise that a particular queue position will clear within one of those periods. A schedule should show utility studies, permits, equipment orders, construction and testing as separate milestones.
Cost structure and reliability
Compare the tariff or contract structure, demand charges, curtailment provisions, backup requirements and reliability commitments. A low energy price is not a complete value proposition if the site cannot provide the needed load when the AI cluster is ready. Conversely, a premium for firm capacity may be justified when delaying deployment would cost more than the power premium.
What should companies consider when choosing a data-center location?
Use a weighted decision model that keeps physical, contractual and technology factors visible. The following framework is an editorial synthesis of the issues identified by CBRE, Deloitte, the U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) and a company SEC filing.
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| Decision area | Questions to document | Evidence to request |
|---|---|---|
| Power | How many megawatts are available, at what reliability and cost, and on what date? | Utility correspondence, executed contracts, interconnection studies and a milestone schedule |
| Grid and generation | Are transmission upgrades, new substations or generation required? Who owns each dependency? | Queue position, study results, permits, equipment orders and responsibility matrix |
| Property control | Will the company own, lease, reserve phases or rely on a development partner? | Recorded title or lease rights, options, easements and termination conditions |
| Facility readiness | Can the building support contiguous halls, high-density cooling, electrical distribution and security controls? | Basis-of-design documents, equipment lead times, commissioning plan and expansion map |
| Portfolio fit | Which workloads belong on premises, in colocation, with a cloud provider or in a hybrid design? | Workload requirements, latency targets, resilience objectives and total-cost model |
| Evidence quality | Is the capacity operating, under construction, permitted, contracted, proposed or merely forecast? | Signed agreements, approvals, filings and independently verifiable milestones |
Property control is a technology dependency
Control can range from owning land and a completed facility to holding a phased lease or a capacity reservation. Each structure changes the company’s ability to alter cooling, add electrical rooms, install security systems or accelerate construction. A lease that promises future capacity should specify delivery tests, remedies for delay, expansion rights and what happens if the utility date moves.
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AI racks can require a facility design different from a conventional enterprise data hall. Evaluate the cooling architecture, water or refrigerant requirements, electrical topology, fire protection, physical security and maintenance access before signing a property commitment. Long-lead transformers, switchgear, generators, chillers and network equipment can become the critical path. Construction labor and commissioning specialists also need to be available in the delivery region.
How long does it take to build an AI data-center campus?
There is no single schedule. A modest building using existing utility capacity may follow a very different path from a campus that needs transmission and generation. CBRE says the shift toward campuses over 500 MW makes multi-year construction schedules normal, while its 24-, 36- and 48-plus-month ranges describe possible interconnection delays when transmission or added generation is needed.
- Define the workload and capacity envelope. Convert model-training and inference plans into a phased megawatt requirement, rack density, cooling load, network design and resilience target.
- Screen markets and parcels. Eliminate locations that lack a credible power-delivery path, suitable zoning, fiber diversity, water or cooling solutions, or sufficient land for substations and expansion.
- Secure conditional property rights. Use an option, phased lease, purchase agreement or development partnership that preserves flexibility while utility studies and permits proceed.
- Advance interconnection and permits. Track utility studies, transmission or substation work, environmental reviews, zoning, building permits and generator approvals as linked dependencies.
- Order long-lead equipment. Align transformer, switchgear, cooling, backup-power and network-equipment orders with the approved design and realistic manufacturing dates.
- Build, commission and test. Complete the shell and electrical and mechanical systems, then test load performance, redundancy, controls, security and failover before installing production IT.
- Deploy IT in phases. Match GPU or accelerator deliveries, storage, networking and operations staffing to the portions of the facility that have passed commissioning.
Planning should include a date by which the company can exit, resize or shift workloads if a dependency slips. A schedule that lists only a building-completion date hides the risk that power or equipment arrives later.
Does on-site or behind-the-meter power solve the constraint?
On-site generation can shorten dependence on a congested grid connection, but it is an option rather than a default answer. CBRE reports accelerating behind-the-meter strategies involving on-site wind, solar and batteries, particularly in deregulated markets. The feasibility depends on fuel or renewable resource, land, emissions rules, interconnection requirements, noise, water, financing, operations capability and the legal right to operate generation at the site.
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Behind-the-meter supply does not automatically mean lower cost, cleaner energy, faster approval or higher reliability. A project may still need a grid connection for balancing, backup or future expansion. Model fuel-price exposure, maintenance, replacement cycles, carbon requirements, curtailment and the time required for environmental and construction permits.
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A concrete proposal, not a completed facility
On July 20, 2026, DOE/NNSA announced that Amentum had been selected to enter negotiations for a phased lease at the Savannah River Site in South Carolina. The proposal describes a 1-gigawatt data center paired with approximately 2 gigawatts of on-site generation, with natural gas described as a bridge to nuclear energy. The announcement says selection is not a final lease award, so the project should be described as a proposal under negotiation rather than an operating or completed data center.
How should executives evaluate project claims and pipeline capacity?
Development language carries different levels of commitment. Use a status register that records the exact evidence behind every megawatt and date.
| Status | What it means | What it does not prove |
|---|---|---|
| Announced | An organization has publicly described an intention or project. | That land, power, financing or permits are secured |
| Selected for negotiations | A party has been chosen to negotiate terms. | That a final lease or construction authorization exists |
| Signed agreement | A contract has been executed, subject to its conditions. | That all permits, financing or utility work are complete |
| Permitted | Specified approvals have been issued. | That construction or energization will meet the forecast date |
| Under construction | Physical work has started under an identified project scope. | That the facility is commissioned or fully leased |
| Operational | The facility has passed the organization’s stated readiness threshold. | That every planned phase or capacity block is online |
AIB Data Centers’ quarterly filing for the period ended June 30, 2026, shows why this distinction matters. The company reported about 570 MW of AI/HPC capacity across six sites, while stating that, apart from its CLT-01 campus, the described pipeline sites had no definitive lease, purchase or development agreement. The filing identifies land, power delivery, buildings, mechanical and electrical systems, cooling, IT infrastructure and long-lead equipment as major capital requirements, and cautions that timing, financing and execution are uncertain. This is a company-specific disclosure, not a measure of the entire market.
How do leases, colocation and cloud capacity fit the real-estate decision?
Owning a facility provides control but commits capital and exposes the company to construction, utility and equipment risk. A colocation arrangement can transfer some development responsibility while limiting physical control and potentially constraining expansion. Cloud capacity can provide faster access to computing, but the company still needs to examine regional availability, reservation terms, workload economics, data-governance requirements and the provider’s ability to add power.
A hybrid portfolio is often a scheduling tool: run urgent or variable workloads in contracted capacity while a controlled site is developed for predictable, high-density demand. Compare alternatives using the same assumptions for megawatts, utilization, latency, resilience, migration effort, contract duration and exit rights. Do not compare a firm, delivered block with an uncommitted pipeline block as if they were equivalent.
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- Real estate: land or lease rights, easements, zoning, expansion phases and landlord or developer obligations.
- Energy and utilities: tariff, interconnection, transmission, generation, renewable claims, reliability and delivery milestones.
- Facilities and engineering: electrical distribution, cooling, water, fire protection, security, maintainability and commissioning.
- IT and architecture: accelerator demand, network topology, storage, latency, software deployment and workload migration.
- Finance and procurement: capital approval, contract protections, equipment deposits, operating-cost exposure and contingency reserves.
- Legal, risk and compliance: permits, environmental obligations, data location, insurance, force majeure and remedies for delay.
Hold a recurring integrated review in which a change in one area updates the others. For example, a utility delay should trigger a property-phase decision, an IT deployment change, a financing reforecast and a review of temporary capacity.
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Choosing connectivity while ignoring deliverable power
Symptom: A site wins a network-comparison exercise but cannot obtain a firm energization date. Fix: Make deliverable megawatts and the utility milestone schedule a gate before final site selection.
Treating a forecast as a commitment
Symptom: A presentation counts proposed capacity as available capacity. Fix: Label every block by status and attach the underlying agreement, approval or filing.
Assuming behind-the-meter generation is automatically better
Symptom: The plan omits fuel, emissions, permitting, maintenance or backup costs. Fix: Compare on-site generation with grid, colocation and hybrid alternatives on a full lifecycle basis.
Using a building date as the only schedule
Symptom: Construction is complete but transformers, utility service or IT equipment are late. Fix: Track property, interconnection, equipment, commissioning and IT milestones separately, with a critical-path owner for each.
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Symptom: The company reserves a large campus before model demand, financing and customer commitments are stable. Fix: Use phased capacity, expansion options and workload portability so later phases are earned by actual demand.
A decision checklist for the next site review
- What power capacity is contractually or otherwise demonstrably available, and on what date?
- Which transmission, generation, substation and permitting tasks remain open?
- Who pays for each upgrade, and what remedy applies if it is late?
- What property right gives the company control of the required halls, support areas and expansion land?
- Can the electrical, cooling, water, security and network designs support the planned rack density?
- Which transformers, switchgear, cooling units, generators and network components have the longest lead times?
- What portion of the plan is owned, leased, colocated, cloud-based or hybrid?
- How are resilience, latency, data governance and workload migration reflected in the comparison?
- Which claims are forecasts, proposals, signed agreements, permits, construction milestones or operating facts?
- What is the fallback if power delivery, financing, equipment or demand misses the target?
What this means for corporate strategy
AI infrastructure does not turn every company into a data-center developer. It does make physical capacity a planning variable that can determine whether an AI roadmap is affordable and timely. The strongest plans connect property control, power contracts, grid approvals, cooling and electrical design, construction sequencing and IT capacity in one evidence-based schedule. Companies that make those dependencies explicit can choose when to own, lease, colocate, use cloud capacity or combine the options—and can recognize early when an attractive site is not actually deliverable.
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