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What changes when you choose colocation or build?
In colocation, a provider supplies facility infrastructure such as space, power, cooling, and connectivity. Your organization owns and operates its IT equipment. In a self-built data center, your organization takes on facility development and operations as well as its IT estate. These choices shift capital needs, operating duties, and risks between the customer and provider; they do not eliminate the cost of servers, accelerators, or electricity.
| Decision area | Colocation | Build your own |
|---|---|---|
| Facility investment | Typically less facility capital required at the start; payments depend on the provider’s proposal and contract. | Requires capital for site, facility, power and cooling infrastructure, and continuing facility investment. |
| Facility operations | The provider operates the facility infrastructure; the tenant operates its IT equipment. | The owner is responsible for developing and operating the facility as well as its IT estate. |
| Control | Bound by the provider’s available capacity, design, service terms, and expansion options. | Greater control over facility design and operation, subject to site, utility, permitting, staffing, and financing constraints. |
| Cost pattern | Can limit initial capital needs, but cumulative costs may rise over a long horizon. | Typically needs more upfront capital and periodic reinvestment; it may have lower long-run total cost if utilization is sustained. |
| Delivery dependency | Depends on the provider’s available capacity and committed delivery schedule, as well as power availability. | Depends on site readiness, permits, utility interconnection, equipment lead times, and construction delivery. |
Schneider Electric’s guidance frames ownership as typically lower in long-run total cost but higher in initial capital and reinvestment needs; outsourcing can reduce initial capital while raising cumulative costs over five to ten years. That is a general framework, not a guaranteed result for a specific project. McKinsey’s modeled colocation economics exclude customer-owned IT hardware, so facility comparisons must keep IT costs separate and consistent.
Why AI workloads make the facility decision harder
“AI workload” does not describe one standard facility requirement. Large-scale model training and advanced inference may require high-density racks, upgraded power delivery, liquid cooling, structural capacity, and close coordination between IT and facilities teams. Other AI workloads may not require all of those provisions. The accelerator model and count, workload profile, and planned growth determine what the facility must support.
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- 【Powerful Load-bearing】12U Network Rack Open Frame is constructed from durable cold rolled steel; Rack shelf supports enhance stability, wall-mounted capacity of 130lbs, the ground-mounted up to 260lbs
- 【Considerate Designs】Open-frame layout, including a top panel adding space, anti-slip shelf stops fixing devices and compatible racks for stack and expansion to meet requirements of home server rack
- 【Complete Accessories】A 12U open frame server rack, two ventilated shelves, four shelf stops, four velcro straps and a set of equipment mounting screws
- 【Versatile Application】Ideal for space-efficient multi-device setups in warehouses, retail, classrooms, offices and more; Excellent choices as AV Rack/IT Rack
- 【Effortless Setup】 Network Rack includes hardware, a comprehensive manual, mounting hole drilling template and an online assembly video to simplify setup
Training and high-density deployments
For large training clusters, assess the planned rack power, how quickly capacity must ramp, cooling method, network design, and the consequences of an interruption. Confirm that the facility can support the required density across the specific rooms and expansion phases you need; a provider’s general AI capability is not proof of capacity for your deployment.
Inference and mixed workloads
Inference requirements vary with model size, request volume, service-level targets, and whether users or systems need low-latency access. A mixed estate may combine high-density accelerator racks with less demanding compute. Size and price the actual rack mix and growth plan rather than assuming every AI workload needs the same cooling and power envelope.
Cooling is an economic as well as an engineering variable. The International Energy Agency (IEA) reports that cooling accounts for about 7% of electricity use in efficient hyperscale data centers and over 30% in less-efficient enterprise data centers. Those percentages describe different facility types and efficiencies; they are not a prediction for a particular AI site.
Rank #2
- Space Saving: Maximum depth: 14.8". Use the wall mount network cabinet to maximize available space for retail locations, classrooms, back offices, network cabinets, and other locations where space is limited.
- Fast Heat Dissipation: The server cabinet is designed with vents to optimize airflow and avoid critical IT equipment overheating. Heat sink holes in the top, bottom, and rear panels are more conducive to heat dissipation.
- Sturdy Construction: Robust welded frame construction for durability and long service life. With 100 lbs wall-mounted load capacity and 200 lbs ground-mounted load capacity, you can place multiple devices in the server rack cabinet as needed.
- High Security: The locked glass door ensures the security of data and equipment. Wall mount rack enclosure server cabinet is ideal for use in public places such as offices, effectively protecting the security of your devices.
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Is it cheaper to build a data center or use colocation?
There is no general workload-size threshold at which building becomes cheaper. The answer depends on location, financing, power cost and availability, utilization, build and delivery timing, staffing, facility design, contract terms, and the period over which costs are compared. A single global benchmark cannot replace local provider proposals and site-specific engineering estimates.
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For a fair five-to-ten-year comparison, use the same workload forecast, location, capacity ramp, service level, deployment date, and time horizon. Define the cost boundary before comparing totals. Include the facility and IT costs that apply to your organization, rather than comparing a colocation fee with a build budget that leaves out essential costs.
- Facility development or colocation charges, including the capacity and service commitments in the actual proposal.
- IT hardware, energy, financing, staffing, maintenance, and facility upgrades.
- Taxes or incentives that apply to the specific location and ownership structure.
- Costs and risks of delayed capacity, unused or stranded capacity, and residual asset value at the end of the comparison period.
McKinsey Global Institute’s 2026 model for a 100 MW Tier 3-equivalent AI colocation facility, excluding IT hardware, found modeled levelized facility-energy costs from roughly $200/MWh in some high-demand Chinese markets to close to $380/MWh in London. These are model-specific pretax results, not retail electricity tariffs, project quotes, or a universal comparison of building against leasing.
Rank #3
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- Strong Load Capacity: Ground-Mounted Load Capacity: 500 lbs, Wall-Mounted Load Capacity: 150 lbs. The av rack is made of carbon steel for better weldability performance and can help save space while meeting your need to place multiple devices.
- User-friendly Design: Ergonomic design makes the open frame av rack easier to use. The additional top panel is able to place other items with more available space. Roller design moves anywhere and anytime, is convenient, and is more energy-saving.
- Complete Accessories: We provide the accessories you need, including 2 x Pallets, 145 x M5*10 Cross Head Screws, 4 x Casters, 4 x M10*50 Expansion Screws,10 x M6*12 Cage Nuts, 1 x Grounding Wire, 1 x User Manual.
- Wide Application: The server rack wall mount maximizes the use of available space, suitable for retail venues, classrooms, offices, and other places where space is limited.
Test the assumptions that can reverse the result
Run the comparison under more than one utilization, electricity-price, and deployment-delay case. A build can look attractive at steady, high utilization but leave the owner carrying idle capacity if demand or deployment is delayed. Colocation can reduce the initial facility investment, but contracted capacity and terms can still expose the customer to cost if demand changes. Use the same assumptions for each option and show which ones drive the outcome.
Power, location, and delivery time can outweigh nominal facility cost
Power availability and price are central to an AI facility decision. The IEA estimated global data-center electricity consumption at around 415 TWh in 2024, about 1.5% of global electricity consumption, and projects roughly 945 TWh in its 2030 base case. These are estimates and a projection for data centers overall, not AI-only demand or a sizing rule for an individual project.
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For either route, verify the available utility capacity, expected interconnection date, power price and terms, and the schedule for any required upgrades. Grid connection delays and equipment lead times can constrain delivery. A facility with a lower quoted cost is not useful if it cannot provide the required energized capacity when the workload needs to launch.
Rank #4
- An intelligent fan system designed for cooling audio video, DJ, server, network, and IT equipment racks.
- Protects rack-mount equipment from overheating, performance issues, and shortened lifespans.
- Programmable thermostat controller with automated speed control, alarm warnings, and backup memory.
- Premium anodized aluminum construction with CNC-machined detailing for a professional appearance.
- Size: 1U Rack Space | Design: Top Exhaust | Airflow: 60 to 300 CFM | Noise: 12 to 38 dBA | Bearings: Dual Ball
- Location: Check latency to users and systems, fiber availability, interconnection options, and any data-residency or sovereignty requirements.
- Site and facility fit: Validate rack density, power delivery, cooling method, structural capacity, redundancy, and the feasibility of later expansion.
- Reliability: Match the facility’s service commitments and redundancy to the workload’s actual availability needs.
- Delivery evidence: Distinguish available capacity from planned capacity, and require clear commitments for energization and expansion dates.
What current market evidence can—and cannot—tell you
Colocation is used for hyperscale capacity, but broad market indicators are not project quotes. Uptime Institute’s 2025 survey found that 62% of surveyed colocation facilities hosted hyperscale technology companies. That is a survey result for its sample, not a measured share of every facility worldwide.
CBRE Research reported that in primary North American wholesale markets, asking rates for 250–500 kW rose 6.6% year over year to $196.25/kW/month in H2 2025. For 3–10 MW, asking rates rose 12.5% year over year over the same period. These geographically and capacity-scoped asking-rate indicators do not establish the price, availability, or terms of a particular AI deployment.
Should you build or lease a data center for AI?
Use a workload-led comparison rather than choosing from a generic build-versus-lease rule. Start with the facility envelope and delivery schedule; then compare the economics using the same assumptions.
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- Characterize the workload. Record training versus inference, accelerator count and generation, power profile, network and latency needs, growth forecast, and service-level requirements.
- Specify the facility envelope. Set required megawatts and ramp schedule, rack density, cooling method, redundancy, fiber needs, and site constraints.
- Establish deliverability. Verify utility capacity and interconnection dates, permits, equipment lead times, and written provider delivery commitments.
- Set consistent cost boundaries. Include facility capital and operating costs, IT hardware, energy, financing, staffing, maintenance, upgrades, taxes or incentives, and residual or stranded-asset risk as applicable.
- Model several cases. Compare utilization, power prices, and deployment delays over the same time horizon instead of relying on one forecast.
- Evaluate an existing-site retrofit. Treat it as a third option if a suitable site has adequate space, power, cooling, and structural integrity.
When each option is more plausible
Colocation may fit when
- You need to reduce upfront facility capital or avoid taking on facility development and operations.
- A provider can confirm capacity, power density, cooling, location, and delivery timing that fit the workload.
- Your demand or deployment schedule is uncertain enough that committing to a self-built facility would create substantial stranded-capacity risk.
Building may fit when
- You can secure suitable land or an existing site, utility capacity, permits, financing, equipment, and experienced operating staff.
- You need facility design or control that available colocation options cannot meet.
- Your forecast supports sustained utilization and the long-run cost case remains favorable after including staffing, maintenance, upgrades, and financing.
Neither set of conditions guarantees the outcome. Validate provider capacity and contract terms against a local engineering and financial model before committing.
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