Hyperscalers now represent the largest share of global data-center capacity. Synergy Research Group estimates that, at the end of Q4 2025, hyperscale operators accounted for 48% of worldwide capacity, compared with 20% for non-hyperscale colocation and 32% for enterprise on-premises facilities.
That is a capacity comparison—not a revenue, workload, electricity-use or ownership comparison. The distinction matters because hyperscalers both build facilities and lease space from colocation providers. The market is therefore not simply a contest in which hyperscalers replace colo and enterprise infrastructure. Hyperscalers are taking the fastest-growing share, colocation is becoming an important supply channel for them, and enterprise infrastructure is concentrating in workloads where control, latency, regulation or predictable utilization still justify ownership.
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The current global split
| Model | Share of global capacity | Direction of travel | Why customers use it |
|---|---|---|---|
| Hyperscale operators | 48% | Fastest growth | Global scale, managed services, cloud elasticity and AI infrastructure |
| Non-hyperscale colocation | 20% | Capacity growth, but likely share pressure | Physical control, connectivity, cloud adjacency and faster deployment |
| Enterprise on-premises | 32% | Declining share | Control, sovereignty, latency, industrial integration and existing assets |
These figures come from Synergy Research Group’s Q4 2025 capacity estimate. Synergy forecasts that hyperscalers could reach 67% of global capacity by 2031, while enterprise on-premises could fall to 19%. Those are forecasts, not settled outcomes.
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What each category actually includes
Hyperscalers
Hyperscalers are large cloud and internet companies operating extensive data-center fleets. The category can include public-cloud providers, search and social platforms, SaaS companies, e-commerce businesses, gaming platforms, digital-content providers and large AI infrastructure operators.
Most importantly, hyperscaler capacity is an operator category, not an ownership category. A hyperscaler may build and own a campus, or lease a wholesale hall from a colocation company. In Synergy’s framework, leased capacity can still count as hyperscaler capacity because the hyperscaler controls the infrastructure and uses it for its platform.
Synergy estimates that hyperscalers operated 1,360 large data centers at the end of 2025. It also reports that roughly 60% of hyperscaler capacity was in facilities they built and owned, meaning a substantial leased component remains.
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Colocation providers rent data-center space, power and related services to multiple customers. The segment includes retail colocation, wholesale campuses, carrier-neutral facilities, managed hosting and interconnection services.
Colocation does not mean “small enterprise servers.” Hyperscalers are major colo customers. In Uptime Institute’s 2025 survey, 62% of surveyed colocation facilities hosted hyperscale technology companies, and those facilities reported an average of 43% of space dedicated to hyperscale customers. The survey covers a sample, not every colocation facility worldwide.
That makes colo both a competitor to self-built infrastructure and a supplier to hyperscalers. A data-center investor can therefore gain exposure to hyperscale growth by owning colocation property, even when the hyperscaler does not own the building.
Enterprise on-premises
Enterprise infrastructure is company-owned or company-operated capacity primarily supporting that organization’s own workloads. It includes traditional corporate data centers, private-cloud facilities, regional and edge sites, and dedicated leased space managed by the enterprise.
Enterprise estates are often hybrid. A company may operate a private facility, rent cabinets in a colo, use public cloud for analytics and retain local systems near a factory. “On-premises” should therefore be understood as a control and operating model, not necessarily a building located on the company’s own property.
Why hyperscalers are gaining share
The shift reflects several forces working together:
- Cloud migration: Enterprises continue moving selected applications from company-operated facilities to public cloud and managed infrastructure.
- AI capacity: Training and inference require large, contiguous power blocks, specialized networking and high-density cooling.
- Capital access: Large platforms can sign long-term power, construction and capacity agreements and spread infrastructure spending across enormous customer bases.
- Economies of scale: Hyperscalers can standardize hardware, networking, procurement, software automation and operations.
- Global deployment: Customers need multiple regions for latency, resilience, sovereignty and regulatory requirements.
- Specialist AI demand: AI startups and neocloud GPU providers are adding capacity outside traditional enterprise IT.
JLL forecasts approximately 97 GW of additional global data-center capacity between 2025 and 2030, with total global capacity potentially reaching about 200 GW by 2030. It forecasts roughly 14% annual sector growth through 2030 and identifies cloud and AI demand as major drivers.
AI is an accelerator, not the entire explanation
AI is changing the physical design and economics of data centers, but it is not the only source of demand. Cloud applications, storage, digital services, networking and ordinary enterprise workloads continue to require capacity.
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JLL estimates that AI represented roughly one-quarter of data-center workloads in 2025 and could account for about half by 2030. It also expects inference to become increasingly important, potentially overtaking training as the dominant AI requirement around 2027. These are forecasts.
AI changes infrastructure requirements through:
- Higher rack densities and larger power blocks.
- Greater use of liquid cooling.
- More demanding network topologies.
- Greater dependence on GPU supply and availability.
- Pressure on grid interconnection, transmission and substations.
- New demand from GPU-as-a-service providers and specialist clouds.
It also creates utilization risk. Announced GPU campuses are not the same as operational capacity, and a project can be delayed by power availability, equipment shortages, weaker demand or disappointing utilization.
Why colocation remains strategically important
Colocation can lose percentage share while adding substantial megawatts. That happens when the total data-center market grows faster than the colo segment.
For customers, colo remains attractive because it can provide:
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- Faster deployment than a greenfield enterprise facility.
- Access to established power, connectivity and carrier ecosystems.
- Direct interconnection with public-cloud and network providers.
- Physical control over hardware without owning the building.
- Retail cabinets through wholesale blocks, depending on the provider.
- Geographic flexibility and a practical bridge while new construction is delayed.
- Support for hybrid-cloud, multicloud and data-residency strategies.
The commercial challenge is availability. Hyperscale demand can crowd out smaller buyers in constrained markets, while power, cross-connects, remote hands, installation and migration charges can materially affect the total cost.
Colocation landlords also face customer-concentration risk. A provider may have strong contracted demand but depend heavily on a few hyperscale tenants. Investors should distinguish signed contracts, committed power, construction in progress and revenue-producing occupied capacity.
Why enterprise infrastructure is shrinking—but not disappearing
Enterprise on-premises capacity is losing share because public cloud and third-party infrastructure are growing faster. That does not make company-operated facilities obsolete.
Enterprise control can remain the better choice when workloads involve:
- Strict regulation, sovereignty or security requirements.
- Factories, hospitals, trading venues or branches that need very low latency.
- Operational technology and industrial systems difficult to refactor.
- Existing buildings with sunk capital and available power.
- High, predictable utilization that makes ownership economical.
- Specialized hardware or integration requirements.
- Cloud egress, licensing or data-transfer costs that undermine migration economics.
The likely result is a more specialized enterprise footprint: smaller as a percentage of global capacity, but more concentrated in high-control, low-latency and industrial workloads. Many enterprises will retain a hybrid estate rather than move everything to public cloud.
How to read “market share” correctly
There is no single universal data-center market-share number. Use the metric that matches the question.
| Metric | Best for | Limitation |
|---|---|---|
| MW or GW of capacity | Physical infrastructure footprint | Can hide utilization and regional differences |
| Occupied space | Real-estate demand | Does not represent power density equally |
| Facility count | Geographic presence | A 5-MW site and a 500-MW campus count equally |
| Revenue | Commercial market power | Business models have different pricing and margins |
| IT workload share | Where computing actually runs | Hard to measure consistently |
| Electricity consumption | Operating intensity | Favors high-utilization or high-density facilities |
| Rack count | Deployment scale | Poorly compares conventional and AI racks |
Uptime Institute’s 2026 survey illustrates the problem: third-party facilities and services account for a larger share of IT workloads than enterprise-owned data centers when measured by facility, but that does not automatically mean third parties hold more total capacity.
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Do not combine Synergy’s capacity percentages with JLL’s occupied-space estimate or Uptime’s facility survey as though they were one data series.
Ownership and control are two different axes
The cleanest way to analyze this market is to ask two separate questions:
- Who owns the physical facility?
- Who operates or controls the computing capacity?
Those answers can differ:
- A hyperscaler may own and operate a campus.
- A hyperscaler may control servers leased inside a colo building.
- A colocation provider may own the building while hosting hyperscaler, enterprise and service-provider customers.
- An enterprise may control equipment located in a third-party facility.
This explains why “hyperscaler versus colo” is an imperfect framing. Hyperscaler-controlled capacity can be delivered through colocation, while colo providers can benefit from the same hyperscale expansion.
Regional concentration and power constraints
The Americas remain the largest regional data-center market, representing approximately 50% of global capacity in JLL’s analysis. The United States accounts for about 90% of capacity in the Americas.
JLL projects APAC capacity to increase from 32 GW to 57 GW by 2030, with APAC colocation growing faster than on-premises capacity.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesMarket-level figures show why regional availability matters. In CBRE’s Q1 2026 comparison, Northern Virginia remained the largest global market and added approximately 1,135.9 MW year over year, a 37.3% increase. Dallas–Fort Worth reached approximately 1,249.4 MW of inventory and became the third-largest U.S. colocation market in that comparison. Chicago’s wholesale inventory reached approximately 910.6 MW, while Atlanta inventory reached approximately 1,465.2 MW.
These are local inventory figures, not global category shares. A provider’s ability to grow depends increasingly on whether it can obtain power, transmission, land, permits, transformers, switchgear and cooling equipment in the right location.
JLL reports global occupancy of 97% at the end of 2025 and estimates that 77% of capacity under construction was precommitted. High occupancy and precommitment support pricing power, but they also mean customers may face long waits and limited choice.
What could slow hyperscaler dominance?
Synergy’s 67% forecast for 2031 should not be treated as inevitable. Potential constraints include:
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- Local opposition, zoning restrictions and permitting delays.
- Water availability and cooling limitations.
- Transformer, switchgear and other electrical-equipment shortages.
- Long construction cycles.
- Higher interest rates or capital-market stress.
- AI demand forecasts proving too optimistic.
- GPU utilization falling below expectations.
- Lease cancellations, project pauses or changes in hyperscaler deployment plans.
- Energy, emissions or water regulations.
Uptime Institute reports that hyperscaler project cancellations and lease changes occur, but interprets them as adjustments within a rapid build-out rather than conclusive evidence of a sector-wide retreat. That is an attributed interpretation, not a guaranteed forecast.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Three ways the next cycle could develop
Base case: hyperscale capture
Cloud migration and AI demand continue, hyperscalers secure power and capacity, and their share rises sharply. Colocation grows in absolute megawatts but loses percentage share. Enterprise capacity declines as a proportion of the global total while remaining important for specialized workloads.
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Power-constrained case
Demand remains strong, but grid connections and construction lag. Hyperscaler projects are delayed, allowing colocation providers with powered shells and existing interconnection ecosystems to capture more bridge demand.
AI-normalization case
AI demand grows, but GPU utilization and economics disappoint relative to aggressive forecasts. New projects are phased more cautiously, while ordinary cloud, storage and enterprise requirements continue to support a slower capacity cycle.
These last two are analytical scenarios, not published forecasts.
Which model is better for a buyer?
Choose hyperscaler infrastructure when:
- The workload is cloud-native and highly variable.
- Global reach and rapid provisioning matter.
- Managed databases, analytics, security and AI services reduce operating effort.
- The organization values operational offload more than physical control.
Review egress, inter-region transfer, service-specific pricing, long-term commitments and migration difficulty. Public-cloud pricing can be flexible, but a simple hourly compute comparison rarely captures the full bill.
Choose colocation when:
- You need physical control without building a facility.
- Cloud adjacency, carrier choice or interconnection is important.
- Workloads are stable enough for dedicated infrastructure.
- Compliance requires specific equipment or a particular location.
- You need a hybrid or multicloud architecture.
Price the complete package: space, power, cross-connects, remote hands, installation, hardware, network circuits, escalation clauses, minimum commitments and exit costs. AWS Direct Connect, for example, is only one component; the customer may also pay the colocation provider, carrier and cross-connect charges.
Choose enterprise-owned or dedicated infrastructure when:
- Low latency, sovereignty or physical control dominates.
- Utilization is high and predictable.
- Existing facilities have useful remaining life.
- Operational technology or specialized hardware is difficult to move.
Account for capital expenditure, staffing, resilience, cooling, power procurement, equipment lead times and the risk of stranded capacity. Ownership can offer a lower long-run unit cost at high utilization, but it transfers operational and investment risk to the enterprise.
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What this means for investors and financial readers
For data-center investors, the headline growth story favors hyperscaler demand, but the investable exposure may sit in several layers:
- Hyperscaler platforms: benefit from cloud and AI growth but face enormous capital requirements, power constraints and customer concentration in specialized capacity.
- Colocation operators: can earn from hyperscaler expansion while retaining diversified enterprise and service-provider demand, though concentration and power availability matter.
- Infrastructure and utilities: may benefit from rising electricity, transmission, cooling and equipment demand.
- Enterprise IT budgets: may shift from owned facilities toward cloud subscriptions, colo contracts, connectivity and managed services.
Do not treat capacity growth as automatic profit growth. Investors should examine utilization, contracted backlog, power availability, tenant concentration, capital expenditure, debt costs, lease obligations, construction timelines and the difference between announced and operating capacity.
The bottom-line market view
Hyperscalers are the clear capacity-share winner. Synergy’s Q4 2025 estimate puts them at 48% of worldwide capacity, ahead of enterprise on-premises at 32% and non-hyperscale colocation at 20%. Its 2031 forecast points to an even more hyperscaler-heavy market.
But the deeper conclusion is more nuanced. Colocation is not merely losing ground: it is also one of the mechanisms hyperscalers use to expand. Enterprise infrastructure is not disappearing: it is becoming more specialized. And no market-share percentage can answer every question unless it identifies whether it measures capacity, space, revenue, workload, facility count or electricity use.
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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →For buyers, the right decision remains workload-specific. Hyperscalers are strongest for elasticity and managed services; colocation for physical control and connectivity; enterprise-owned infrastructure for specialized, regulated, low-latency or consistently utilized workloads. A hybrid model will remain the practical answer for many organizations.
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