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Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Enterprises use colocation as one option in a hybrid infrastructure strategy—not as a universal replacement for owned data centers or public cloud. They place each workload where performance, security, control, connectivity, cost, compliance and deployment needs best fit. Survey results show that colocation is part of the mix, while owned facilities and cloud services remain important too.
What colocation does in a hybrid infrastructure strategy
In a colocation arrangement, an organization places its equipment in a third-party data center. The organization retains control of its systems while relying on the facility for capabilities such as space, power and data-center operations. That makes colocation distinct from public cloud, where customers consume provider-managed computing services, and from an enterprise data center operated in-house.
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Hybrid infrastructure combines multiple venues. An enterprise might run some systems in its own facilities, some in public or private cloud, use SaaS for business applications, and place selected equipment in colocation. The point is not to move everything to one destination, but to match workloads to technical, financial and operational requirements.
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Two 2025 surveys illustrate why colocation should be understood as one part of a varied estate. Their populations and measures differ, so the figures should not be combined into a single market estimate.
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| Measure | Reported distribution | Source and scope |
|---|---|---|
| Where respondents estimated their organization’s IT ran | Enterprise data centers: 45%; colocation: 16%; public cloud: 10%; hosting, including private cloud: 10%; server closets or IT rooms: 6%; SaaS: 6%; micro or edge data centers: 4%. | Uptime Institute, 2025 Global Data Center Survey. Respondents estimated workload placement; figures are rounded and describe the survey sample, not all enterprise IT. |
| Current AI workload distribution reported by respondents | Public cloud: 49%; private cloud: 15%; third-party SaaS or web platforms: 15%; on-premises company-controlled data centers: 15%; colocation data centers: 7%. | DataBank, 2025 report survey. These are respondents’ reported current placements, not a market-wide census. |
The Uptime results show owned enterprise facilities as the largest reported venue in that survey, with colocation also a substantial part of the distribution. DataBank’s AI-specific results place a smaller reported share in colocation than in public cloud. The measures cover different questions and samples; neither establishes a universal pattern for every enterprise.
Why enterprises consider colocation for AI workloads
AI workloads can have demanding requirements for compute, data movement, power and response times. Colocation may suit a workload when a company wants to retain control of its hardware or data while locating systems in a professionally operated facility with useful network connections. But AI alone does not determine the venue: workload characteristics and organizational constraints do.
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- Performance and latency: Where systems sit, and how they connect to users, data sources and cloud services, can affect performance. CoreSite’s July 2026 release highlights direct, low-latency connectivity among cloud, colocation and on-premises environments.
- Security and control: Organizations may prefer greater control over infrastructure or data handling for particular workloads. That preference has to be weighed against the controls and operational responsibilities of each venue.
- Regulation and data location: Sovereignty and regulatory requirements can influence placement. Uptime Institute notes these concerns help explain why large organizations may retain owned facilities.
- Cost and utilization: IDC’s February 2025 brief identifies cost as one factor in decisions to buy or expand cloud environments. The relevant comparison depends on the workload and its usage, rather than a blanket assumption that colocation or cloud is always cheaper.
- Time to market and capacity: IDC’s brief also identifies time to market among decision factors. Available power, space and deployment timing can shape whether a particular facility is practical.
No single environment is established as best for every AI workload. Some may fit public cloud, private cloud, SaaS, on-premises infrastructure or colocation; organizations can also divide related workloads across venues.
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What the surveys and forecasts say about adoption
The available figures show interest and planned investment, but they measure different things. Current workload shares are not the same as plans or forecasts.
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| Finding | How to interpret it |
|---|---|
| IDC projected enterprise spending on AI-centric systems to grow at 27% annually from 2022 to 2026. | Forecast in IDC’s February 2025 brief, sponsored by Intel; it is not an observed growth result. |
| IDC said enterprise investments in generative AI solutions exceeded $20 billion in 2024. | Estimate cited in the Intel-sponsored IDC brief; it concerns AI investment, not colocation spending. |
| IDC projected that 75% of enterprise AI workloads would be deployed on hybrid, fit-for-purpose infrastructure by 2028. | Forecast, not a measured current share. The brief is sponsored by Intel. |
| DataBank reported that 22% of its survey respondents planned to expand colocated data-center deployments over the next five years; 31% planned to build more AI-dedicated private data centers. | Respondents’ stated plans in DataBank’s 2025 report, not independent forecasts of market-wide deployment. |
| Foundry/CoreSite reported that 98% of surveyed IT leaders had adopted or planned to adopt a hybrid IT model. | Finding in CoreSite’s 2025 State of the Data Center report; it combines adoption with planned adoption and is sponsor-associated research. |
These findings support a narrower conclusion than “enterprises are moving AI to colocation”: organizations are considering and using multiple infrastructure venues, and some report plans to expand colocation. They do not establish that most enterprise AI workloads are in colocation or that AI is the sole driver of colocation adoption.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to choose between colocation, cloud and owned facilities
Assess the workload and the operating constraints together. A useful comparison covers more than the headline cost of a service or facility.
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- Performance and latency: Identify response-time needs and where users, data and dependent systems are located.
- Security and control: Determine which party must control hardware, access, configurations and data handling.
- Regulation and sovereignty: Check applicable rules and required data locations before selecting a venue.
- Connectivity: Consider links to public-cloud services, other facilities and users, including the latency and resilience required.
- Cost and utilization: Compare the costs relevant to the actual workload and expected use, rather than assuming one model wins in every case.
- Power, capacity and deployment time: Confirm that the chosen location can support the workload and meet its schedule.
- Operating responsibility: Be clear about which tasks the organization retains and which are handled by cloud or facility providers.
Colocation can make sense when an organization needs a third-party facility but wants to keep control of its own equipment. Public cloud can be appropriate when its service model and capabilities fit the workload. Owned facilities may remain important where sovereignty, regulation, control or existing investments favor them. These are workload-level choices, not mutually exclusive enterprise-wide commitments.
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Integration is part of the placement decision
A hybrid estate only works well when its environments can communicate and be operated together. CoreSite’s July 2026 release emphasizes direct, low-latency connectivity among cloud, colocation and on-premises systems, alongside security and data control. Enterprises evaluating colocation should therefore assess connectivity to the services and locations their workload depends on—not just the facility itself.
As quoted in CoreSite’s July 2026 release, John Gallant, Enterprise Consulting Director at CIO, said enterprises preparing for the future are focused on optimizing workload placement across cloud, colocation and on-premises environments according to performance, security and control requirements. The statement reflects a provider-associated view; it is not an independent market-wide measurement.
What the evidence does—and does not—establish
Uptime Institute’s survey, IDC’s Intel-sponsored brief, DataBank’s report and Foundry/CoreSite’s research use different methods, populations and measures. Survey results describe their respondents; forecasts are projections; and company-associated findings should be read in that context. The figures are useful for understanding reported patterns and interest, but they do not add up to one definitive global adoption rate.
Together, they point to hybrid infrastructure as a mix of venues, with workload placement shaped by performance, cost, time to market, security, connectivity, control and regulatory concerns. Colocation is one option in that mix—not a synonym for cloud and not a wholesale replacement for enterprise data centers.
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