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For many large AI deployments, the hardest part of securing colocation is no longer finding floor space. It is getting enough usable, reliable power to the racks on a date the provider can substantiate. In 2026, the stronger question is not simply “How many megawatts are available?” but “What kind of capacity is ready, where is it in the delivery process, and what will it cost to operate?”
That shift is especially important for hyperscalers, GPU-cloud operators and other large customers. It does not make buildings, fiber, cooling or location irrelevant. It makes power delivery the first test—and a source of both competitive advantage and project risk.
Why power has become the first question
Colocation has traditionally been compared by location, rack availability, carrier access, redundancy and price. Those remain important, particularly for enterprise customers with modest or latency-sensitive deployments. But AI training and other large-scale GPU workloads have changed the scale of the buying decision: customers may need large, contiguous blocks of capacity, high rack densities, liquid-cooling support and a credible path to energization.
Market figures illustrate the pressure, though they use different definitions and should not be treated as directly comparable. CBRE reported 1.6% vacancy in primary North American data-center markets in the first half of 2025. AFIRE, citing market data, reported 1.1% national vacancy in the first quarter of 2026; its national figure and methodology differ from CBRE’s primary-market measure. CBRE’s report also found the sharpest lease-rate increases among requirements of 10 MW or more in leading North American markets, including a reported 19% rise for such requirements in Silicon Valley during the period covered. That is a market- and period-specific figure, not a universal price trend. AFIRE’s presentation is a separate source for the Q1 2026 vacancy figure.
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Power constraints are particularly acute for large AI-oriented projects, not necessarily every colocation purchase. S&P Global, citing 451 Research estimates, put U.S. data-center grid power serving hyperscale, leased and crypto-mining facilities at about 64.4 GW in 2025, and projected about 183.2 GW by 2030. The first is an estimate, and the second a forecast—not a government census or a guaranteed outcome. S&P Global explains the estimate and forecast.
The practical conclusion is not that space no longer matters. It is that for many large deployments, power has become the scarce input that determines whether available space can become working compute.
“Available megawatts” can mean very different things
A provider’s capacity figure may describe any of several stages, and marketing language does not always make the distinction obvious:
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- Available shell space: a building or expansion area that is empty or unfinished.
- Available white space: fitted data-hall area, which may not have the electrical or cooling capacity for the customer’s intended load.
- Planned or allocated utility capacity: capacity expected, requested, reserved or discussed with a utility. The exact status matters; an application or letter is not the same as an energized service commitment.
- Commissioned capacity: electrical infrastructure installed and tested, but not necessarily ready for the customer’s specific equipment and operating profile.
- Customer-ready capacity: power, cooling, network, compliance and operating procedures are ready for the proposed deployment.
Ask the provider to define the quoted megawatts in writing. Do they mean utility service, total facility load, critical load, IT load or customer-contract capacity? Is the figure firm or conditional? Is it available now, after construction, after utility energization, or only if another customer does not take it?
Evidence is more useful than a headline number. Request the relevant utility agreements or approvals, the interconnection stage, substation status, energization milestones and commissioning plan. A nearby transmission line, announced generation project or preliminary utility letter does not by itself establish when a customer can run production workloads.
The entire path from grid to rack matters
Electricity must travel through a chain before it becomes reliable IT load. A simplified path is:
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- Generation: electricity is produced, whether by grid-connected plants or on-site sources.
- Transmission: high-voltage lines move electricity toward the region and site.
- Interconnection: the utility and relevant grid entities study and approve the connection, including its effects on the network.
- Substation and transformers: voltage is transformed and capacity is delivered to the campus.
- Site distribution: switchgear, breakers, busways and other equipment route power through the facility.
- UPS and backup: systems manage interruptions and provide continuity, subject to the design and operating plan.
- Cooling: the facility removes the heat generated by the IT load.
- Rack and workload: power and cooling reach the customer’s equipment, which must still be installed, commissioned and connected to the required network.
A delay at any point can postpone useful capacity. A site may have generation nearby but lack transmission or substation capacity. It may have a grid connection but be waiting for a transformer, switchgear or commissioning work. Wood Mackenzie warns that transmission build-outs can take five to ten years in some cases; that is a risk range cited by the firm, not a timeline that applies to every project. Its analysis discusses co-located generation and flexible interconnection as responses.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsFor this reason, the scarce asset may not be electricity in the abstract. It may be a completed, permitted and tested electrical path from the grid—or another supply source—to a particular set of racks.
AI changes what “good colocation” means
Traditional enterprise colocation often emphasized rack availability, carrier choice, redundancy and proximity to a city or business ecosystem. AI deployments add requirements that can reshape a facility:
- Large, contiguous blocks: a training cluster may need many racks in one coordinated deployment rather than small amounts of scattered capacity.
- High density: GPU systems can require far more power per rack than conventional enterprise equipment. There is no single universal AI rack-density figure; hardware, configuration and cooling design vary.
- Cooling matched to the equipment: a provider should specify whether liquid cooling is installed and operational, planned, or unavailable, and what architecture it supports.
- Power and thermal coordination: electrical distribution, cooling capacity and rack limits must work together. A megawatt allocation alone says little if the hall cannot safely handle the customer’s density.
- Deployment speed: customers may value time to usable compute more than a lower long-term property cost.
Facility power is not the same as IT power. As a simple illustration, 10 MW of IT load at a power-usage effectiveness (PUE) of 1.3 would imply about 13 MW of total facility power: 10 MW multiplied by 1.3. That is a conceptual calculation, not a benchmark for every data center. Ask which load figure a provider is quoting and how much of the allocation can reach IT equipment.
The relevant density questions include maximum supported kilowatts per rack; whether the power block is contiguous; cooling type and capacity; floor loading and rack-weight limits; distribution design; and whether planned growth can be accommodated without disruptive retrofits or derating.
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Time-to-power should mean more than the date a provider expects to make capacity available. Track the stages separately: site control or lease signing, utility application, interconnection approval, substation and transmission work, building energization, data-hall commissioning, rack deployment and first production use.
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A useful buyer-oriented extension is time-to-token: the time from selecting a site to the first useful AI workload running in production. The phrase has appeared as an emerging industry framing, not as a universal standard. It highlights that an energized building is not yet productive compute; cooling, network, GPU procurement, software and commissioning also affect the date. TechRadar has described the framing.
When a provider says capacity will be available in a particular year or quarter, ask which milestone that date represents and what dependencies remain. Put material dates, customer remedies and conditions into the contract rather than relying on a sales presentation.
Established hubs versus power-advantaged markets
Established markets such as Northern Virginia, Chicago, London, Frankfurt and Silicon Valley offer advantages that a low electricity price cannot reproduce: dense fiber and carrier ecosystems, nearby customers, experienced operating vendors, skilled labor and established business infrastructure. They can also face high land and construction costs, congestion, long interconnection queues, community opposition and limits on cooling resources. CBRE identifies infrastructure and grid constraints in established markets including Northern Virginia, Chicago, London and Frankfurt in its 2026 global data-center trends report.
Secondary or tertiary markets may offer more land, lower competition for sites, access to power or generation, cooler climates and potentially faster delivery. McKinsey has highlighted interest in regions such as the Nordics, including for power availability, climate and scalability. Its analysis considers the changing geography of colocation.
But “secondary market” does not mean “easy power.” Generation may be available while transmission is constrained; fiber routes may lack diversity; maintenance talent may be scarce; permitting may be uncertain; and latency to users, cloud services or counterparties may be unacceptable. The better comparison is the full bundle: deliverable power, transmission path, cooling resources, connectivity, permitting, operating capability and total cost.
Different customers will value that bundle differently. A 500 MW AI campus, a 10 MW neocloud deployment, a 1 MW enterprise customer and a latency-sensitive financial-services workload do not have the same site-selection answer. Small and mid-sized buyers should not assume they need to control land, generation or a wholesale-scale utility agreement: a GPU-cloud service may meet an urgent need while a facility is being built. Larger customers may find direct colocation or dedicated campus capacity better suited to their scale, control and multi-year economics.
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Bringing power to the site is not a universal fix
Operators are exploring natural-gas generation, fuel cells, solar paired with storage, batteries, co-located generation, microgrids, existing power-plant conversions, renewable-energy contracts, flexible interconnection and utility-managed demand response. Each option addresses a different part of the problem.
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On-site or co-located generation may shorten a project’s path to some supply, but it does not automatically make power cheaper, cleaner or firm. Projects may need fuel infrastructure, emissions permits, environmental review, maintenance agreements and backup arrangements. They can be exposed to fuel prices and equipment availability, and may still require a grid connection for startup, maintenance or reliability. Batteries can help with short-duration support, but they do not automatically replace firm generation.
Keep five questions separate: physical supply (what produces the electricity), grid capacity (what can be delivered through the network), energy procurement (what the customer buys and at what price), carbon accounting (what emissions claims can be made), and reliability (what happens through outages, maintenance or curtailment). A renewable power-purchase agreement or certificate does not mean renewable electricity is physically powering a facility every hour.
Flexible or interruptible interconnection may let a project connect before all network upgrades are complete, but it can involve curtailment rights or other operating conditions. A buyer needs to understand what service is firm, what can be curtailed, how notice works and whether the workload can tolerate an interruption. The details are project-specific.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Pricing power is not the same as earning a good return
Scarcity can support higher lease rates, particularly for large requirements, but it can also raise an operator’s costs. Substations, transformers, switchgear and cooling systems can require substantial capital. Utility rates, demand charges, energy pass-throughs, financing costs and construction delays can all affect economics. Under a fixed-price customer contract, an operator may carry more energy-price risk; under a pass-through model, the customer may face volatile or unexpectedly high bills.
Read the commercial terms for energy tariffs, demand charges, minimum power commitments, connection and construction fees, escalation, renewable-energy charges, curtailment provisions and delay remedies. Consider whether the contract gives the customer expansion options and a right to exit or receive compensation if capacity is late.
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Strong demand and high headline rents do not guarantee strong margins. S&P Global has identified changing credit risks for data-center operators as they face exposure to power availability and cost, equipment, permitting, capital markets and uncertainty about AI adoption. Its analysis examines those risks. A project built around a single large tenant may have revenue visibility, but also customer-concentration, financing and specialized-infrastructure risks.
Grid expansion is also a public-policy question
Large data-center loads affect utility planning and local politics. Buyers and operators should ask who pays for incremental grid upgrades, whether the utility requires minimum-take commitments, what happens during grid emergencies, whether special tariffs apply and whether service is subject to curtailment. Those terms can determine whether a project’s power is both deliverable and commercially defensible.
The U.S. Department of Energy’s July 2026 National Transmission Needs Study identifies hyperscale AI data centers among sources of load growth that the grid must accommodate and discusses congestion and transmission needs in regions including MISO, SPP, PJM and ERCOT. The cited document was a draft as of July 2026; it should not be read as final policy. DOE’s study page provides the document and status.
Communities may scrutinize electricity-price effects, water use, noise, backup-generator emissions, land use, tax incentives and promised local jobs. A Bloom Energy-sponsored survey of 156 decision-makers across the data-center ecosystem found that respondents viewed power availability as a major constraint and reported heightened community scrutiny. It is a vendor-sponsored survey, not a neutral census of the market. The report’s sponsorship and findings should be considered in that light. Local zoning, environmental review, utility-commission action, emissions permits or public opposition can delay a project even after a power plan is announced.
A practical colocation due-diligence checklist
Before choosing a provider, get specific answers to these questions and, where possible, documentary support:
- Delivery: What is the utility-approved capacity? What interconnection stage has been completed? Is the service firm or conditional? What is the energization date, and what could delay it?
- Definition: Does the quoted MW figure mean utility service, total facility power, critical load, IT load or contracted customer load? How much is already committed?
- Electrical path: Is the substation built and energized? Are transformers and switchgear on site or on order? What commissioning and testing remain?
- Density and cooling: What maximum kW per rack and contiguous block can the hall support? Is liquid cooling operational now? What cooling architectures, floor loads and rack weights are supported?
- Reliability: What are the UPS, generator and fuel arrangements? What redundancy is provided? What are the maintenance procedures and test results? How does the facility handle utility curtailment?
- Power quality: How are power-quality requirements and load changes addressed for this specific design? Are filtering, UPS behavior and load-ramp limits documented? Do not assume that every GPU cluster creates the same electrical profile.
- Costs and contract: What energy and demand charges apply? Which costs are passed through? Are there minimum-take commitments, escalation clauses, delay remedies, liquidated damages, expansion rights and exit rights?
- Network and location: Which carriers and cloud on-ramps are available? Are fiber routes diverse? What are the relevant latencies, cross-connect costs and data-residency requirements?
- Execution: Who coordinates facility commissioning, GPU delivery, network turn-up and cooling integration? Is there a credible operating and maintenance team at the site?
Do not rely on a “Tier III” or “Tier IV” label alone. Ask which standard is meant, who certified it and whether the certification applies to design documents, constructed infrastructure or operational performance. A label cannot answer whether the customer’s specific load will arrive on time.
Who is best positioned—and who carries the risk?
Operators with already-energized capacity, credible utility relationships, completed electrical infrastructure and high-density cooling are positioned to serve customers faster. Utilities and developers able to coordinate large loads and transmission investment may also benefit, as may markets that combine real power deliverability with adequate fiber, permitting and operating talent.
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Scarcity also creates overbuild risk. If AI demand, GPU economics or tenant credit conditions change, specialized high-density halls, generation assets or power contracts may be underused or difficult to repurpose. Today’s scarcity can create pricing leverage, but it is not proof that every planned project will earn an attractive return.
In 2026, “power, not space” is useful as a strategic shorthand—not a claim that space, fiber or location have stopped mattering. For large AI deployments, the best colocation site is the one that can show, with evidence and contractual clarity, when the right amount of reliable, affordable power will reach the customer’s racks.
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