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The Data Centre & HPC Market grew from USD 59.64 billion in 2025 to USD 64.70 billion in 2026. It is expected to continue growing at a CAGR of 9.76%, reaching USD 114.47 billion by 2032. Speak directly to the analyst to clarify any post sales queries you may have.
Data centre and HPC priorities are being rewritten by AI acceleration, energy constraints, and resilience demands across the full stack
Data centres and high-performance computing (HPC) have moved from being specialist back-end infrastructure to becoming the primary engines of digital competitiveness. The rapid mainstreaming of generative AI, the growth of AI inference at the edge, and the resurgence of large-scale scientific and engineering simulation have collectively raised expectations for compute density, interconnect performance, and end-to-end reliability. As a result, executive teams are no longer asking whether to invest in capacity and modernization, but how to do so without amplifying operational risk, energy exposure, and supply-chain dependency.At the same time, the definition of “performance” has broadened. Latency, power efficiency, carbon intensity, security posture, and resilience against component shortages are now treated as first-order design parameters. This has driven a shift toward purpose-built architectures-GPU-accelerated clusters, high-radix networking, liquid-cooled racks, and storage tiers designed for AI pipelines-while also intensifying the need for standardization and repeatability across sites.
This executive summary frames the market landscape through the lens of transformational technology shifts, policy and tariff pressures, segmentation and regional dynamics, and the strategic actions that leaders can take to build more adaptive, cost-resilient, and compliant infrastructure.
Workload-specific architectures, liquid cooling adoption, hybrid placement strategies, and supply-chain constraints are redefining modern HPC operations
The landscape is being reshaped by a pivot from general-purpose data centre expansion to workload-specific infrastructure. AI training and advanced simulation are driving demand for tightly coupled compute, high-bandwidth memory, and low-latency fabrics, which in turn elevates the importance of topology-aware networking and cluster orchestration. This is not simply an upgrade cycle; it is a structural change in how capacity is planned, purchased, and operated, with performance-per-watt and performance-per-dollar replacing raw compute counts as the most defensible executive metrics.Cooling has become a defining differentiator. As rack densities rise and thermal envelopes tighten, liquid cooling is transitioning from niche deployments to a mainstream design option, particularly in new builds and major retrofits. This shift cascades into facilities engineering, maintenance training, supply qualification, and insurance and warranty considerations. In parallel, operators are tightening thermal monitoring and adopting more granular telemetry to reconcile energy efficiency goals with strict uptime requirements.
Another transformative shift is the rebalancing of where compute runs. Cloud and colocation remain pivotal, but many organizations are adopting a portfolio approach that blends hyperscale resources, regional colocation, and on-premises HPC for data gravity, sovereignty, or predictable utilization. Consequently, procurement teams are emphasizing portability across environments, standard APIs, and consistent security controls. This also increases the value of software-defined infrastructure, containerized HPC, and scheduling layers that can span heterogeneous hardware.
Finally, the supply chain has become a design constraint rather than a background function. Lead times for critical components, export controls, and increasing scrutiny of provenance are pushing buyers to qualify alternate suppliers, adopt modular architectures, and negotiate stronger service-level and spares commitments. In this environment, platform choices are increasingly shaped by ecosystem maturity, firmware and lifecycle support, and the vendor’s capacity to ensure continuity under changing trade and regulatory conditions.
United States tariffs in 2025 are reshaping total landed cost, supplier leverage, and lifecycle strategies across the data centre and HPC supply chain
The cumulative effect of United States tariffs in 2025 is best understood as a compounding procurement and planning tax rather than a single line-item surcharge. For data centre and HPC buyers, tariffs can influence total landed cost across a broad set of imported inputs, including server subsystems, network equipment, power distribution components, racks, and certain categories of cooling hardware. Even where final assembly occurs domestically, upstream dependencies-such as PCBs, optical transceivers, connectors, and specialty metals-can carry embedded tariff exposure that surfaces later in the bill of materials.This environment changes buying behavior in several ways. First, it encourages earlier locking of configurations and longer commitment windows, as teams attempt to reduce price volatility and avoid repeated repricing events. Second, it increases the strategic value of multi-sourcing and regionally diversified manufacturing footprints, particularly for high-volume SKUs and parts with limited substitutes. Third, it elevates the importance of contract language around price adjustments, pass-through mechanisms, and definitions of force majeure and regulatory change.
Tariffs also create second-order impacts that are easy to underestimate. Suppliers may reallocate constrained inventory to markets with more predictable margins, which can elongate lead times for specific components. Integrators and resellers may adjust bundling strategies to optimize tariff classification, influencing how systems are packaged and serviced. Over time, these dynamics can nudge architecture decisions, for example favoring designs that reduce reliance on tariff-exposed components or standardize around platforms with broader sourcing options.
Operationally, the tariff environment strengthens the business case for lifecycle extension and refurbishment programs when they can be executed without compromising reliability or compliance. It also increases scrutiny on spares strategy: holding critical spares may appear costlier upfront, but it can reduce outage risk when replacement parts become more expensive or slower to procure. Taken together, the 2025 tariff landscape reinforces a central executive lesson-cost resilience is now inseparable from architectural resilience and supplier governance.
Segmentation reveals divergent buying triggers across offering, data centre type, workload, cooling approach, organization size, and end-user priorities
Segmentation across component, deployment, workload, and end-user context reveals why “one-size-fits-all” planning is failing in data centre and HPC programs. When viewed by offering, demand patterns diverge sharply between compute systems, storage platforms, networking, cooling and power infrastructure, and the software and services layers that bind them. Compute decisions increasingly hinge on accelerator availability, memory bandwidth, and validated configurations, while storage choices are being driven by AI pipeline requirements such as fast checkpointing, parallel file access, and tiered architectures that separate performance from capacity.Considering segmentation by data centre type, hyperscale, colocation, enterprise, and research environments exhibit different tolerance for customization and different optimization targets. Hyperscale operators push for standardization and supply assurance at scale, whereas enterprise deployments often prioritize integration with existing governance, identity, and compliance controls. Research and academic HPC environments can be early adopters of advanced interconnects and novel architectures, but they also face budget cycles and procurement constraints that shape upgrade cadence and vendor selection.
Looking through the lens of workload segmentation, AI training, AI inference, analytics, and traditional HPC simulation create distinct infrastructure signatures. AI training rewards dense accelerator nodes and high-bandwidth, low-latency fabrics; inference emphasizes throughput, cost efficiency, and placement close to data and users; analytics benefits from balanced compute and storage; and simulation often demands deterministic performance and tightly coupled node-to-node communication. This diversity encourages mixed clusters and composable designs, but it also increases the need for scheduling sophistication and performance isolation.
Segmentation by cooling approach further clarifies investment priorities. Air cooling remains prevalent for many deployments, yet the expansion of liquid cooling-direct-to-chip and immersion in particular-signals a shift toward facility designs that treat thermal management as a strategic capability. Meanwhile, segmentation by organization size and by vertical end user highlights how regulatory pressure, uptime expectations, and data sensitivity shape purchasing. Financial services, healthcare, government, telecommunications, manufacturing, and media each weigh sovereignty, latency, and security differently, leading to varied preferences across on-premises, colocation, and cloud-aligned solutions.
Across these segmentation lenses, a consistent insight emerges: competitive advantage increasingly comes from aligning architecture, procurement, and operations to the dominant workload and governance needs, rather than chasing generalized peak performance metrics.
Regional realities - from energy and sovereignty to connectivity and climate - are steering divergent data centre and HPC strategies worldwide
Regional dynamics are defined by an interplay of energy availability, regulatory requirements, connectivity maturity, and supply-chain accessibility. In the Americas, the buildout is heavily influenced by AI-driven capacity demand, expanding colocation ecosystems, and heightened attention to power procurement and grid interconnection timelines. Buyers also weigh resilience against climate events and seek geographic diversity, which elevates the role of multi-region architectures and standardized deployment templates.In Europe, the conversation is shaped by sustainability mandates, stringent data protection regimes, and growing interest in sovereign cloud and regional processing. These factors encourage investments in energy-efficient infrastructure, heat reuse, and stronger reporting on operational metrics. As a result, operators are often pressed to justify not only performance outcomes but also environmental and compliance alignment, which accelerates adoption of advanced monitoring, energy-aware scheduling, and carefully designed site selection strategies.
Across the Middle East, data centre expansion is closely tied to national digital transformation programs and the desire to become regional compute hubs. Large greenfield projects and investments in connectivity corridors are enabling rapid scale, while heat and water considerations drive innovation in cooling design and facility engineering. In Africa, growth is uneven but strategic, with demand concentrating around major metro areas and submarine cable landings; reliability and power stability considerations place a premium on resilient designs, modular expansion, and strong managed services capabilities.
In Asia-Pacific, the landscape combines mature hyperscale activity in established markets with rapid expansion in emerging economies. Regulatory diversity and data localization requirements shape where workloads can run, while high urban density in some markets increases the appeal of high-efficiency footprints and advanced cooling. The region’s manufacturing ecosystem also influences procurement options and time-to-deploy, although geopolitical complexity and cross-border compliance add friction. Across all regions, the unifying trend is that infrastructure decisions are increasingly constrained by non-technical factors-permitting, energy contracts, sovereignty, and supply assurance-which makes regional strategy inseparable from technology strategy.
Key companies compete on full-stack integration, validated AI/HPC platforms, liquid-cooling readiness, and lifecycle software that simplifies operations
Competition among key companies is increasingly defined by platform completeness and the ability to deliver validated, serviceable systems at speed. Hardware leaders are differentiating through accelerator roadmaps, memory and interconnect innovation, and reference architectures tuned for AI and tightly coupled HPC. At the same time, network and optics specialists are gaining influence as fabric performance becomes a gating factor for cluster efficiency, particularly when scaling training workloads and managing east-west traffic.Infrastructure suppliers are also competing on their ability to support liquid cooling and high-density deployments with predictable operational outcomes. This includes not only cooling hardware but also the engineering services, commissioning playbooks, and ongoing maintenance models required to keep advanced thermal systems reliable. Companies that can provide integrated facility-to-rack solutions, along with clear warranty alignment across components, are better positioned as buyers seek to reduce integration complexity.
On the software side, differentiation is shifting toward orchestration, observability, and security controls that work across heterogeneous environments. Buyers increasingly expect workload schedulers, container platforms, and monitoring stacks to function consistently across on-premises clusters, colocation deployments, and cloud-adjacent environments. Vendors that provide strong lifecycle tooling-firmware management, vulnerability response, configuration drift control, and capacity analytics-are gaining credibility with enterprise and government buyers who must operationalize HPC at scale.
Service providers and integrators remain pivotal, especially for organizations that lack deep in-house expertise in cluster design, benchmarking, and day-two operations. The strongest players are those that can combine supply-chain navigation, performance tuning, and managed operations with governance and compliance support. As a result, partnerships and ecosystem alignment-between chip vendors, OEMs, cooling specialists, and software providers-are becoming as important as individual product specifications.
Industry leaders can win by aligning workloads to reference designs, building tariff-resilient supply chains, and elevating energy and security governance
Industry leaders should begin by treating workload characterization as a board-level prerequisite for capital allocation. Mapping dominant workloads-training, inference, analytics, and simulation-to measurable performance and efficiency targets reduces the risk of overbuilding the wrong capacity. From there, standardizing a small number of validated reference configurations can improve procurement leverage and speed deployments, while still allowing targeted exceptions for specialized research or latency-sensitive use cases.Next, leaders should harden supply-chain strategy with explicit design-for-substitution principles. This means qualifying multiple suppliers for critical components, favoring open and widely supported form factors where feasible, and negotiating contracts that clarify tariff pass-through, lead-time commitments, and spares availability. In parallel, organizations should modernize governance for hybrid infrastructure by enforcing consistent identity, policy, and observability across on-premises, colocation, and cloud environments, thereby reducing operational fragmentation.
Energy and cooling strategy should be elevated from facilities planning to enterprise risk management. Executives should align site selection, power procurement, and cooling roadmaps with long-term capacity plans, including realistic timelines for grid interconnection and permitting. Where high-density is unavoidable, investing early in liquid cooling readiness-skills, service processes, and monitoring-can prevent costly retrofits and reduce unplanned downtime.
Finally, leaders should operationalize security and resilience as continuous processes rather than project milestones. This includes disciplined firmware and patch management, supply-chain provenance validation, segmentation of management networks, and routine disaster recovery testing for both data and control planes. When paired with clear KPIs for efficiency, utilization, and service reliability, these actions create a practical operating system for scaling HPC and AI infrastructure under tightening constraints.
A rigorous methodology combines stakeholder interviews, technical and policy validation, and triangulated analysis to reflect real deployment constraints
The research methodology for this report is designed to produce decision-grade insight into the data centre and HPC landscape by combining structured primary engagement with rigorous secondary validation. Primary research incorporates interviews and discussions with stakeholders across the ecosystem, including infrastructure buyers, data centre operators, system integrators, technology vendors, and subject-matter experts involved in compute, networking, storage, cooling, and operations. These conversations are used to test assumptions, clarify adoption drivers, and surface practical constraints that shape purchasing and deployment.Secondary research draws on publicly available technical documentation, standards publications, regulatory and policy materials, company disclosures, product briefs, and credible industry literature to establish a consistent baseline for technology capabilities and market context. Information is cross-checked across multiple independent references to reduce the risk of bias, and emphasis is placed on the most current materials available to reflect rapidly evolving AI infrastructure requirements.
Analytical work includes segmentation mapping, qualitative competitive assessment, and thematic trend analysis focused on architecture shifts, operational practices, and procurement risk. Where conflicting signals appear, the methodology prioritizes triangulation-validating claims through multiple stakeholder perspectives and corroborating evidence-before incorporating them into final conclusions. This approach ensures that insights remain grounded in real-world deployment considerations and are actionable for executives managing complex infrastructure portfolios.
Sustained advantage will come from operational coherence that unites architecture, regional constraints, procurement resilience, and day-two excellence
Data centre and HPC strategy is entering a period where the strongest outcomes will come from coherence rather than sheer scale. AI and advanced computing are pushing infrastructure toward higher density, tighter coupling, and more specialized designs, while energy constraints, sustainability requirements, and supply-chain volatility are narrowing the margin for error. Consequently, organizations that align architecture decisions with operational reality-cooling capability, power availability, staffing models, and security governance-will be better positioned to expand capacity without compromising reliability.At the same time, the market’s diversity is not a complication to be ignored but a signal to refine decision-making. Differences in workload profiles, deployment environments, and regulatory conditions demand segmented strategies that can still be executed with standardized playbooks. Leaders who can balance flexibility with repeatability-through validated designs, consistent software layers, and disciplined lifecycle management-will reduce integration risk and improve time-to-value.
Ultimately, the path forward favors organizations that treat procurement resilience, regional strategy, and day-two operations as strategic levers. By integrating these elements into a single operating model, executives can navigate policy shifts, accelerate deployment, and sustain performance as AI and HPC become foundational to competitive advantage.
Table of Contents
1. Preface
2. Research Methodology
3. Executive Summary
4. Market Overview
5. Market Insights
7. Cumulative Impact of Artificial Intelligence 2025
8. Data Centre & HPC Market, by Infrastructure Type
9. Data Centre & HPC Market, by Deployment Mode
10. Data Centre & HPC Market, by Rack Unit
11. Data Centre & HPC Market, by Application
12. Data Centre & HPC Market, by End User
13. Data Centre & HPC Market, by Region
14. Data Centre & HPC Market, by Group
15. Data Centre & HPC Market, by Country
17. China Data Centre & HPC Market
18. Competitive Landscape
List of Figures
List of Tables
Companies Mentioned
The key companies profiled in this Data Centre & HPC market report include:- Advanced Micro Devices, Inc.
- Atos SE
- Cisco Systems, Inc.
- CyrusOne Inc.
- Dell Technologies Inc.
- Digital Realty Trust, Inc.
- Eaton Corporation plc
- Equinix, Inc.
- Fujitsu Limited
- Hewlett Packard Enterprise Company
- Huawei Technologies Co., Ltd.
- Inspur Group Co., Ltd.
- Intel Corporation
- International Business Machines Corporation
- Iron Mountain Incorporated
- Legrand S.A.
- Lenovo Group Limited
- Microsoft Corporation
- NEC Corporation
- NVIDIA Corporation
- Oracle Corporation
- Penguin Computing, Inc.
- Schneider Electric SE
- Vertiv Holdings Co.
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 183 |
| Published | January 2026 |
| Forecast Period | 2026 - 2032 |
| Estimated Market Value ( USD | $ 64.7 Billion |
| Forecasted Market Value ( USD | $ 114.47 Billion |
| Compound Annual Growth Rate | 9.7% |
| Regions Covered | Global |
| No. of Companies Mentioned | 25 |
