China Artificial Intelligence (AI) Optimised Data Center Market Size & Share Analysis - Growth Trends and Forecast (2025 - 2030)

China Artificial Intelligence (AI) Optimised Data Center Market Trends and Insights

Rapid deployment of high-density GPU clusters by Chinese hyperscalers

Hyperscale cloud providers have redesigned server halls for domestic AI accelerators that already power almost half of large-language-model (LLM) training tasks. Huawei alone has rolled out 2,500 petaflops of AI compute across 20 cities, and its Ascend 910B chips require liquid cooling and custom interconnects that differ from legacy GPU layouts. The shift is steering operators toward heterogeneous racks that pair multiple accelerator types inside the same power domain to guarantee supply continuity. Operators report 30-40% energy savings once immersion or cold-plate systems replace air cooling, freeing energy headroom for additional compute.^{[1]Huawei Technologies, “计算2030,” Huawei, huawei.com}

Government subsidies and green-DC incentives in tier-2 Chinese cities

The National Development and Reform Commission (NDRC) offers land, tax, and low-rate financing packages to data-center projects that co-locate with renewable-generation assets. Qinghai’s plan to lift photovoltaic self-consumption limits from 40 MW to 100 MW for single campuses illustrates how western provinces compete for AI workloads.^{[2]Qinghai Provincial People’s Congress, “关于清洁能源与算力融合发展的建议,” qhrd.gov.cn} The policy widens source-grid-load-storage integration zones to 500 km, enabling operators in Xining or Yushu to tap hydro-solar hybrids and achieve >80% green-power utilization mandated for 2025 builds.^{[3]National Development and Reform Commission, “关于新增算力布局的指导意见,” ndrc.gov.cn}

Surge in proprietary AI silicon driving demand for heterogeneous compute racks

Huawei Ascend, Baidu Kunlun, Cambricon, and Biren chips each impose unique power-draw and cooling envelopes, obliging facilities to adopt open-sled rack formats and programmable power-distribution units. Supply-chain uncertainties from foundry-yield variability push operators to diversify chip sourcing and over-provision capacity buffers. Software orchestration layers must juggle distinct toolchains while sustaining the low-latency, high-bandwidth links vital for distributed AI training.

Mandatory data-sovereignty rules repatriating AI workloads to domestic facilities

Security assessments for cross-border transfers now cover personal, financial, and public-sector datasets, forcing multinational firms to anchor AI workloads in mainland facilities. Sovereign-cloud offerings that bundle compliance audits, encryption key-management, and localized support gain preference among regulated industries. Distributed edge nodes ensure that inference for global apps stays inside Chinese territory without breaching latency budgets.

National energy-consumption caps limiting new permits in Beijing-Tianjin-Hebei

Local governments froze large-scale data-center approvals to meet dual-carbon targets, squeezing supply in China’s most lucrative rack market. Existing operators leverage efficiency retrofits and edge offloading to maximize authorized energy envelopes. Capacity scarcity lifts pricing premiums 20-30% above unconstrained provinces and accelerates migration of batch training jobs to western hubs.^{[4]Beijing Municipal Data Bureau, “培育壮大绿色算力,” data.beijing.gov.cn}

US GPU-export curbs lengthening AI-accelerator supply cycles

Export controls doubled procurement lead times to 6-12 months, compelling providers to lock in demand forecasts and maintain higher inventory buffers. Dual-sourcing strategies pair restricted foreign accelerators with domestic alternatives that now reach 80% of flagship performance. The policy accelerates capital allocation toward home-grown chip ecosystems but reduces short-term procurement flexibility.

Segment Analysis

By Data Center Type: Colocation Drives Infrastructure Sharing

Colocation facilities captured 23.23% of new capacity additions in 2024 and are forecast to outpace the wider China artificial intelligence data center market at a 23.23% CAGR. The pivot reflects budgets shifting from capital expenditure to predictable operating expense as enterprises prioritize rapid access to AI-ready racks and advanced cooling. Cloud Service Providers still dominate overall installed capacity with 55.82% China artificial intelligence data center market share, underwritten by hyperscalers’ vertically integrated cloud-to-chip stacks. 

Enterprises increasingly mix colocation nodes with public-cloud control planes to sidestep Beijing energy-permit constraints while preserving low-latency interconnects for real-time inference. Providers such as GDS Holdings pre-install liquid-cooled AI pods, enabling customers to spin up 8-GPU blocks within days. The China artificial intelligence data center market size for colocation deployments is projected to more than triple by 2030 as regulatory complexity and technology refresh cycles shorten.

Note: Segment shares of all individual segments available upon report purchase

By Component: Hardware Acceleration Drives Infrastructure Transformation

Hardware spending will expand at a 22.67% CAGR, faster than the broader China artificial intelligence data center market, as generative-AI training pushes rack power envelopes past 30 kW. Although Software held 45.83% revenue share in 2024, the shift toward proprietary AI silicon and low-latency fabrics elevates server, network, and cooling outlays. 

Power-delivery and cooling subsystems collectively represent the fastest-growing hardware slice, mirroring PUE mandates and rack-density trends. High-bandwidth memory, silicon photonics, and 800 Gbps switches enter mainstream bill-of-materials lists. Services revenue follows hardware complexity: integration firms bundle chip-level tuning, workload migration, and compliance documentation as managed offerings, sustaining a steady mid-teens CAGR inside the China artificial intelligence data center industry.

By Tier Standard: Tier III Gains Ground Through Cost Optimization

Tier IV remained the preferred choice for mission-critical AI model training, accounting for 61.63% of 2024 capacity. Yet Tier III is forecast to post a brisk 23.77% CAGR, narrowing the gap as checkpointing, distributed training, and redundancy features built into software temper outage risk. The China artificial intelligence data center market size tied to Tier III is expected to nearly quintuple by 2030. 

Operators realize 30-40% capex savings by downgrading one redundancy level without sacrificing customer service-level agreements for less latency-sensitive tasks. Regulators have clarified tier-classification criteria, giving enterprises a transparent risk-budgeting framework and allowing edge-zone sites to standardize on Tier III with regional grid-backup overlays.

By End-user Industry: Digital Media Accelerates AI Adoption

Digital-media platforms register the highest growth velocity at 22.45% CAGR, narrowing the lead held by IT and ITES, which commanded 33.82% China artificial intelligence data center market share in 2024. Video-generation workflows, personalized feeds, and real-time moderation demand GPU-dense clusters and high-throughput object-storage arrays. 

Manufacturing and Industrial IoT deployments emphasize edge inference for quality control and predictive maintenance, spawning micro-data-center footprints inside factory grounds. BFSI and Healthcare maintain steady double-digit growth as regulatory-compliant sovereign-cloud services mature, while Government and Defense workloads gravitate toward domestic silicon stacks for security assurances mandated by national policy.

Geography Analysis

East China remains the largest regional contributor to the China artificial intelligence data center market size, thanks to dense enterprise footprints, skilled labor pools, and mature connectivity. Strict land-use and energy caps motivate upgrades to liquid cooling and 2-story rack arrangements that add capacity without breaching allocated megawatts. The region also acts as a control plane for AI compute executed in western provinces via low-latency UHV lines. 

North China, anchored by Beijing-Tianjin-Hebei, commands premium pricing because capacity additions lag demand under regional carbon quotas. Operators push PUE values below 1.15 through heat-recovery loops that feed municipal heating grids, while edge nodes in neighboring provinces handle overflow batch training. 

South China, notably Guangdong, leverages manufacturing synergies to adopt AI for supply-chain optimization. Proximity to Hong Kong supports hybrid architectures that segregate international workloads from domestic data, a compliance pattern gaining traction among export-oriented enterprises. 

Southwest provinces such as Sichuan and Guizhou capture hyperscale builds with abundant hydro-power and cooler climates that favor free-air economization. Local authorities streamline permits, grant land concessions, and guarantee renewable-energy allocation, helping the sub-region post the highest installed-rack growth rate nationwide. Northwest hubs in Ningxia mirror these advantages but battle grid-stability concerns that call for integrated storage solutions. 

Northeast China lags in absolute capacity but presents growth optionality as provincial governments court digital infrastructure to revitalize industrial bases. Improved fiber backbones and preferential tariffs are beginning to attract second-wave operators aiming to diversify geographic risk.