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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsEnterprises use colocation as one option in a hybrid infrastructure strategy—not as a universal replacement for company-owned data centers or public cloud. They decide where each workload belongs by weighing performance, cost, security, control, connectivity, regulation, available capacity and deployment time. Current surveys show AI workloads spread across several environments, while forecasts point to greater use of hybrid infrastructure.
What enterprise colocation adoption looks like
Colocation means placing an organization’s servers and other equipment in a third-party data center, where the provider supplies facility services such as space, power and cooling. The organization retains more direct control over its hardware than it typically does in public cloud, while relying on the provider for the data-center environment and often for network connections.
It is one part of a broader infrastructure mix. Uptime Institute’s 2025 Global Data Center Survey asked respondents to estimate where their organization’s IT ran. The rounded shares were 45% in enterprise data centers, 16% in colocation, 10% in public cloud, 10% in hosting (including private cloud), 6% in server closets or IT rooms, 6% in SaaS, and 4% in micro or edge data centers. These are estimates from the survey sample, not a census of enterprise IT. The largest reported venue remained company-owned enterprise facilities. Uptime Institute’s 2025 survey
The figures do not establish that all enterprises are moving to colocation. They show that organizations use multiple venues and choose among them according to workload requirements and financial considerations. Sovereignty and regulatory concerns can also contribute to decisions to retain owned facilities.
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Why AI and hybrid cloud bring colocation into the discussion
AI workloads have varied infrastructure needs
AI is not a single workload with one ideal location. Training, inference, data preparation and supporting applications can have different needs for compute capacity, response time, data access, security and control. An organization may use cloud services for some tasks, company-controlled facilities for others, and colocation where it needs dedicated equipment or connectivity without building a data center of its own.
An IDC brief sponsored by Intel identifies performance, time to market, cost and security as considerations when enterprises buy or expand cloud environments. It forecasts enterprise spending on AI-centric systems growing at 27% annually from 2022 to 2026, enterprise investment in generative AI solutions exceeding $20 billion in 2024, and 75% of enterprise AI workloads deployed on hybrid fit-for-purpose infrastructure by 2028. These are IDC estimates and a forecast presented in a sponsored brief; the 2028 figure is not a measurement of current deployments. IDC’s February 2025 brief
Current placement is not the same as planned expansion
DataBank’s 2025 report gives a different view, focused specifically on its survey respondents’ current AI workload distribution: 49% in public cloud, 15% in private cloud, 15% on third-party SaaS or web platforms, 15% in on-premises company-controlled data centers, and 7% in colocation data centers. In the same report, 22% of respondents planned to expand colocated data-center deployments over the next five years, while 31% planned to build more AI-dedicated private data centers. These are survey results and reported plans, not market-wide forecasts. DataBank’s 2025 report
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The contrast matters: a relatively small current colocation share can coexist with interest in future expansion. Neither measure means colocation is becoming the destination for every AI workload.
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Foundry/CoreSite’s 2025 State of the Data Center report says 98% of surveyed IT leaders had adopted or planned to adopt a hybrid IT model. The report also describes increased colocation use across several workload types and interest in moving selected public-cloud workloads to colocation. Its findings are sponsor-associated survey results, not a universal measure of enterprise adoption. Foundry/CoreSite’s 2025 report
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CoreSite’s July 2026 release describes hybrid IT as a standard enterprise operating model and says organizations are focusing on which workloads belong in cloud, colocation or on-premises environments. It highlights direct, low-latency connectivity, security and data control, including for sensitive or regulated workloads. This is a provider’s account of its report and market view. John Gallant, Enterprise Consulting Director at CIO, put the placement question this way in that release: “What stands out in this year’s research is that enterprises have moved beyond hybrid adoption and the ones preparing for the future are now focused on optimizing workload placement across cloud, colocation and on-premises environments based on performance, security and control requirements.” CoreSite’s July 2026 release
How to decide where an AI workload should run
Compare venues workload by workload rather than choosing one infrastructure model for the whole organization. A practical evaluation includes:
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- Performance and latency: Determine how quickly the workload must respond and how close its compute needs to be to users, data sources and connected services.
- Security and control: Establish the organization’s requirements for physical and operational control, access management, and responsibility for the environment.
- Regulation and data location: Check where data must reside and whether sovereignty or regulatory obligations favor a particular venue.
- Connectivity: Assess network paths to users, public-cloud services, other facilities and business partners. Low-latency links may be important when systems span multiple environments.
- Cost and utilization: Compare the cost of the required capacity and its expected use, including the financial implications of operating or renting infrastructure.
- Power and capacity: Confirm that the chosen location can support the workload’s power and space requirements.
- Time to deploy: Consider how quickly the organization needs the environment and what it must build, procure or configure to make it operational.
Colocation may fit when an organization wants to operate its own equipment in a third-party facility and needs particular facility, location or interconnection characteristics. Public cloud, private cloud, SaaS and owned data centers each offer different operating arrangements. The right answer depends on the workload and the organization’s constraints; the cited findings do not identify one environment as best for every AI use case.
Why connectivity is part of the architecture
A hybrid design is not simply a list of places where systems run. Applications, data and services must communicate across those places. CoreSite’s 2026 release highlights direct, low-latency connectivity among cloud, colocation and on-premises environments as organizations manage more complex infrastructure. Network interconnection can therefore affect the practical performance and operating fit of a placement decision.
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That is an architectural requirement, not a specification for a particular cable or retail networking product. The cited sources establish connectivity as a consideration but do not prescribe a cable type or other implementation detail.
How to read enterprise adoption figures
The available percentages describe different populations, questions and measures, so they should not be combined into a single estimate of colocation adoption. Uptime reports respondents’ estimates of where organizational IT ran; DataBank reports its respondents’ current AI workload distribution and plans; IDC provides forecasts in an Intel-sponsored brief; and the CoreSite material reports sponsor-associated findings, with the 2025 report attributing survey data to Foundry.
Those distinctions explain why the figures answer different questions. A workload share is not the share of companies using a venue; a plan to expand is not a deployment already completed; and a forecast is not an observed outcome. Taken together, the material supports a narrower conclusion: enterprises are evaluating colocation as one element of hybrid infrastructure, with workload placement shaped by performance, cost, security, control, connectivity and operational constraints.
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