查看購物車
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
2149728

人工智慧資料中心基礎設施市場預測至2034年－全球分析（按基礎設施類型、冷卻基礎設施、資料中心類型、機架密度、部署模式、應用、最終用戶和地區分類）

AI Data Center Infrastructure Market Forecasts to 2034 - Global Analysis By Infrastructure Type, Cooling Infrastructure, Data Center Type, Rack Density, Deployment Model, Application, End User, and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球人工智慧資料中心基礎設施市場規模將達到 1,813 億美元，並在預測期內以 23.1% 的複合年成長率成長，到 2034 年將達到 9,560 億美元。

人工智慧資料中心基礎設施是指專為支援人工智慧工作負載（例如模型訓練、推理和生成式人工智慧應用）而設計的專用運算、網路、儲存和電力系統。該市場涵蓋運算基礎設施、網路基礎設施、儲存基礎設備基礎設施和電力基礎設施。這些系統部署在雲端服務供應商、超大規模技術公司、企業、政府機構和金融服務機構的超大規模資料中心、託管資料中心、企業級資料中心和邊緣資料中心。人工智慧的日益普及、模型複雜性的不斷提高以及資料中心容量的擴展是推動市場成長的主要因素。

人工智慧模型的複雜性和訓練需求正在爆炸性成長。

人工智慧模型（包括大規模語言模型和生成式人工智慧）的快速發展是人工智慧資料中心基礎設施市場的主要驅動力。現代人工智慧模型包含數十億甚至數兆個參數，訓練這些模型需要龐大的運算資源。訓練這些模型需要數千個專用人工智慧加速器並行運行，並透過高速網路連接，並由大規模儲存和電力基礎設施提供支援。推理工作負載也需要相當強大的運算能力。人工智慧能力和模型規模的指數級成長正在顯著提升對人工智慧最佳化型資料中心基礎設施的需求，從而支撐市場的持續成長。

巨額資本投資和電力限制

人工智慧資料中心基礎設施所需的巨額資本投資以及日益嚴格的電力限制是限制市場發展的主要因素。人工智慧最佳化型資料中心需要在加速器、網路、冷卻和電力基礎設施方面投入數十億美元。由於人工智慧資料中心消耗數兆瓦級電力，電力保障正成為一項關鍵限制因素。在某些地區，由於電力供給能力有限和輸電網限制，部署可能會被推遲。這些成本和電力方面的挑戰可能會限制市場成長，尤其是在能源基礎設施薄弱的地區。

開發先進的冷卻技術和節能架構

先進冷卻技術和節能架構的持續創新為人工智慧資料中心基礎設施市場的擴張帶來了巨大機會。包括晶片級直接冷卻和浸沒式冷卻在內的液冷解決方案，能夠提高機架密度。節能加速器和最佳化的系統設計降低了單次運算的能耗。透過整合可再生能源和先進的電源管理技術，永續性問題得以解決。隨著技術的進步，更有效率、更永續的人工智慧基礎設施正在不斷擴大市場佔有率。

供應鏈限制和零件短缺

人工智慧加速器、高頻寬記憶體和先進網路組件的供應鏈瓶頸對人工智慧資料中心基礎設施市場的成長構成重大威脅。人工智慧晶片的需求超過供應，導致分配難題。地緣政治緊張局勢正在影響半導體供應鏈。先進封裝產能的限制限制了GPU的生產。這些供應方面的限制可能會延緩資料中心的部署，並限制市場成長。

新型冠狀病毒（COVID-19）的影響：

新冠疫情加速了人工智慧資料中心基礎設施市場的成長，這主要得益於數位轉型和遠端服務擴展帶來的雲端運算和人工智慧能力需求的激增。疫情凸顯了數位基礎設施的重要性，並加速了企業對人工智慧的採用。儘管供應鏈中斷影響了零件的供應，但也刺激了對國內製造業的投資。即使在疫情之後，人工智慧的持續進步也保持了對人工智慧最佳化型資料中心基礎設施的強勁需求。

在預測期內，「計算基礎設施」細分市場預計將佔據最大佔有率。

預計在預測期內，運算基礎設施細分市場將佔據最大的市場佔有率，這主要得益於人工智慧加速器、伺服器和GPU系統在人工智慧工作負載中的關鍵作用。運算基礎設施是人工智慧資料中心最大的投資類別，其中人工智慧加速器是最昂貴的元件。該細分市場受益於晶片設計的持續創新和性能提升。隨著人工智慧模型規模的擴大和運算需求的成長，運算基礎設施在基礎設施類型細分市場中保持最大的佔有率。

預計在預測期內，「直接冷卻液流」細分市場將呈現最高的複合年成長率。

在預測期內，「晶片級液冷」細分市場預計將呈現最高的成長率，這主要得益於高功率人工智慧加速器高效冷卻的需求、機架密度的不斷提高以及傳統風冷方式的局限性。晶片級液冷為高密度人工智慧基礎設施提供了卓越的溫度控管。超大規模資料中心和託管服務供應商的日益普及推動了這一細分市場的發展。隨著人工智慧機架密度超過風冷的散熱能力，晶片級液冷正在冷卻基礎設施領域經歷最快的成長。

市佔率最大的地區：

在整個預測期內，北美預計將保持最大的市場佔有率，這得益於超大規模雲端服務供應商和人工智慧技術公司的集中佈局，以及大規模的資料中心投資。美國正透過領先科技公司建立大規模人工智慧資料中心來推動該地區的成長。高度集中的人工智慧研發活動也刺激了市場需求。成熟的技術生態系統為創新提供了支持。技術領先地位和強勁的投資確保了北美繼續保持其市場主導地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於中國、日本、韓國以及東南亞地區人工智慧的快速普及、雲端基礎設施的擴張以及資料中心投資的增加。該地區龐大且持續成長的數位經濟正在催生對人工智慧基礎設施的巨大需求。各國政府為促進人工智慧發展所採取的措施也為市場成長提供了支持。隨著人工智慧的普及和資料中心容量的擴張，亞太地區將成為全球人工智慧資料中心基礎設施市場成長最快的地區。

免費客製化服務：

所有購買此報告的客戶均可從以下免費自訂選項中選擇一項：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要公司進行SWOT分析（最多3家公司）
  • 區域細分
    • 根據客戶的興趣，我們將提供主要國家的市場估算和預測，以及複合年成長率（註：需經可行性確認）。
  • 競爭性標竿分析
    • 根據產品系列、企業發展和策略聯盟對重點公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧資料中心基礎設施市場：按基礎設施類型分類

  • 計算基礎設施
    • 人工智慧加速器
    • 人工智慧伺服器
    • GPU系統
    • CPU和異構運算系統
  • 網路基礎設施
    • 高速乙太網路
    • InfiniBand
    • 光纖網路
    • 網路交換器和路由器
  • 儲存基礎設備
    • NVMe儲存
    • 企業級固態硬碟
    • 網路附加儲存
    • 儲存區域網路
  • 電力基礎設施
    • UPS系統
    • 配電單元
    • 母線槽和配電系統
    • 應急電源系統

第6章：全球人工智慧資料中心基礎設施市場：按冷卻基礎設施分類

  • 空冷式
  • 直接滴液冷卻
  • 浸沒式冷卻
  • 後門式熱交換器
  • 混合冷卻系統

第7章 全球人工智慧資料中心基礎設施市場：按資料中心類型分類

  • 超大規模資料中心
  • 託管資料中心
  • 企業資料中心
  • 邊緣和模組化資料中心

第8章：全球人工智慧資料中心基礎建設市場：按機架密度分類

  • 每個機架功率小於 20 千瓦
  • 每機架 20-50 千瓦
  • 每機架 50-100 千瓦
  • 每個機架功率超過 100 千瓦

第9章：全球人工智慧資料中心基礎設施市場：按部署模式分類

  • 新人工智慧資料中心
  • 維修的AI資料中心
  • 模組化人工智慧資料中心

第10章：全球人工智慧資料中心基礎設施市場：按應用領域分類

  • 訓練人工智慧模型
  • 人工智慧推理
  • 人工智慧世代
  • 高效能運算
  • 大規模資料分析
  • 科學與研究計算

第11章 全球人工智慧資料中心基礎設施市場：按最終用戶分類

  • 雲端服務供應商
  • 超大規模技術公司
  • 託管服務提供者
  • 公司
  • 政府和研究機構
  • 金融服務公司
  • 醫療與生命科學相關組織

第12章 全球人工智慧資料中心基礎設施市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第13章 戰略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第14章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第15章：公司簡介

  • NVIDIA Corporation
  • Advanced Micro Devices, Inc.
  • Intel Corporation
  • Dell Technologies Inc.
  • Hewlett Packard Enterprise
  • Super Micro Computer, Inc.
  • Cisco Systems, Inc.
  • Arista Networks, Inc.
  • Broadcom Inc.
  • Vertiv Holdings Co.
  • Schneider Electric SE
  • Equinix, Inc.
  • Digital Realty Trust, Inc.
  • Lenovo Group Limited
  • Huawei Technologies Co., Ltd.
Product Code: SMRC40158

According to Stratistics MRC, the Global AI Data Center Infrastructure Market is accounted for $181.3 billion in 2026 and is expected to reach $956.0 billion by 2034 growing at a CAGR of 23.1% during the forecast period. AI data center infrastructure encompasses the specialized computing, networking, storage, and power systems designed to support artificial intelligence workloads including model training, inference, and generative AI applications. The market includes computing infrastructure, networking infrastructure, storage infrastructure, and power infrastructure. These systems are deployed in hyperscale, colocation, enterprise, and edge data centers across cloud service providers, hyperscale technology companies, enterprises, government institutions, and financial services organizations. Growing AI adoption, increasing model complexity, and expanding data center capacity are key drivers of market expansion.

Market Dynamics:

Driver:

Explosive growth in AI model complexity and training requirements

The rapid advancement of artificial intelligence models, including large language models and generative AI, is a primary driver for the AI data center infrastructure market. Modern AI models contain billions or trillions of parameters, requiring massive computational resources for training. Training these models demands thousands of specialized AI accelerators working in parallel, connected by high-speed networking and supported by massive storage and power infrastructure. Inference workloads also require significant compute capacity. As AI capabilities expand and model sizes grow exponentially, demand for AI-optimized data center infrastructure escalates dramatically, supporting sustained market growth.

Restraint:

Significant capital investment and power constraints

The enormous capital investment required for AI data center infrastructure and growing power constraints represent a major restraint for the market. AI-optimized data centers require billions in investment for accelerators, networking, cooling, and power infrastructure. Power availability is becoming a critical constraint, with AI data centers consuming megawatts of electricity. Utility capacity limitations and grid constraints in some regions may delay deployments. These cost and power challenges may constrain market growth, particularly in regions with limited energy infrastructure.

Opportunity:

Development of advanced cooling and power-efficient architectures

Continuous innovation in advanced cooling technologies and power-efficient architectures presents significant opportunities for AI data center infrastructure market expansion. Liquid cooling solutions including direct-to-chip and immersion cooling are enabling higher rack densities. Power-efficient accelerators and optimized system designs are reducing energy consumption per computation. Renewable energy integration and advanced power management are addressing sustainability concerns. As technology advances, more efficient and sustainable AI infrastructure captures growing market share.

Threat:

Supply chain constraints and component shortages

Supply chain constraints for AI accelerators, high-bandwidth memory, and advanced networking components pose significant threats to AI data center infrastructure market growth. Demand for AI chips exceeds supply, creating allocation challenges. Geopolitical tensions affect semiconductor supply chains. Advanced packaging capacity limitations constrain GPU production. These supply constraints may delay data center deployments and limit market growth.

Covid-19 Impact:

The COVID-19 pandemic accelerated AI data center infrastructure market growth as digital transformation and remote services increased demand for cloud computing and AI capabilities. The pandemic highlighted the importance of digital infrastructure and accelerated enterprise AI adoption. Supply chain disruptions affected component availability but also drove investment in domestic manufacturing. Post-pandemic, continued AI advancement has sustained strong demand for AI-optimized data center infrastructure.

The Computing Infrastructure segment is expected to be the largest during the forecast period

The Computing Infrastructure segment is expected to account for the largest market share during the forecast period, driven by the essential role of AI accelerators, servers, and GPU systems in AI workloads. Computing infrastructure represents the largest investment category for AI data centers, with AI accelerators being the most expensive components. The segment benefits from continuous innovation in chip design and performance improvements. As AI model sizes grow and computational requirements increase, computing infrastructure maintains the largest infrastructure type segment share.

The Direct-to-Chip Liquid Cooling segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the Direct-to-Chip Liquid Cooling segment is predicted to witness the highest growth rate, fueled by the need for efficient cooling of high-power AI accelerators, increasing rack densities, and the limitations of traditional air cooling. Direct-to-chip liquid cooling offers superior thermal management for high-density AI infrastructure. The segment benefits from growing adoption by hyperscale and colocation providers. As AI rack densities increase beyond air cooling capabilities, direct-to-chip liquid cooling delivers the fastest cooling infrastructure segment growth.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, supported by the concentration of hyperscale cloud providers, AI technology companies, and significant data center investment. The United States leads regional growth with substantial AI data center construction by major technology companies. High concentration of AI research and development drives demand. Well-established technology ecosystem supports innovation. With technology leadership and strong investment, North America maintains its dominant market position.

Region with highest CAGR:

Over the forecast period, the Asia-Pacific region is anticipated to exhibit the highest CAGR, driven by rapid AI adoption, expanding cloud infrastructure, and increasing data center investment across China, Japan, South Korea, and Southeast Asia. The region's large and growing digital economy creates substantial demand for AI infrastructure. Government initiatives promoting AI development support market growth. As AI adoption and data center capacity expand, Asia Pacific delivers the fastest AI data center infrastructure market growth globally.

Key players in the market

Some of the key players in AI Data Center Infrastructure Market include NVIDIA Corporation, Advanced Micro Devices, Inc., Intel Corporation, Dell Technologies Inc., Hewlett Packard Enterprise, Super Micro Computer, Inc., Cisco Systems, Inc., Arista Networks, Inc., Broadcom Inc., Vertiv Holdings Co., Schneider Electric SE, Equinix, Inc., Digital Realty Trust, Inc., Lenovo Group Limited, and Huawei Technologies Co., Ltd.

Key Developments:

In September 2026, NVIDIA introduced its "scale-in" infrastructure architecture alongside BlueField-4 and OpenShell, targeting secure resource partitioning and out-of-band monitoring for autonomous agentic workloads inside AI factories.

In September 2026, Vertiv partnered with NVIDIA during Vertiv Week to accelerate direct-to-chip liquid cooling and 800V high-voltage direct current (HVDC) architectures designed for next-generation megawatt AI server racks.

In June 2026, HPE unveiled next-generation ProLiant servers tailored for agentic AI workloads and hybrid multicloud compute orchestration at Computex.

In June 2026, Supermicro expanded global liquid-cooled rack production to exceed 5,000 racks per month across its North American and Asian facilities to resolve high-density delivery bottlenecks.

Infrastructure Types Covered:

  • Computing Infrastructure
  • Networking Infrastructure
  • Storage Infrastructure
  • Power Infrastructure

Cooling Infrastructure Covered:

  • Air Cooling
  • Direct-to-Chip Liquid Cooling
  • Immersion Cooling
  • Rear-Door Heat Exchangers
  • Hybrid Cooling Systems

Data Center Types Covered:

  • Hyperscale Data Centers
  • Colocation Data Centers
  • Enterprise Data Centers
  • Edge and Modular Data Centers

Rack Density Covered:

  • Below 20 kW per Rack
  • 20-50 kW per Rack
  • 50-100 kW per Rack
  • Above 100 kW per Rack

Deployment Models Covered:

  • New-Build AI Data Centers
  • Retrofitted AI Data Centers
  • Modular AI Data Centers

Applications Covered:

  • AI Model Training
  • AI Inference
  • Generative AI
  • High-Performance Computing
  • Large-Scale Data Analytics
  • Scientific and Research Computing

End Users Covered:

  • Cloud Service Providers
  • Hyperscale Technology Companies
  • Colocation Providers
  • Enterprises
  • Government and Research Institutions
  • Financial Services Organizations
  • Healthcare and Life Sciences Organizations

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI Data Center Infrastructure Market, By Infrastructure Type

  • 5.1 Computing Infrastructure
    • 5.1.1 AI Accelerators
    • 5.1.2 AI Servers
    • 5.1.3 GPU Systems
    • 5.1.4 CPU and Heterogeneous Computing Systems
  • 5.2 Networking Infrastructure
    • 5.2.1 High-Speed Ethernet
    • 5.2.2 InfiniBand
    • 5.2.3 Optical Networking
    • 5.2.4 Network Switches and Routers
  • 5.3 Storage Infrastructure
    • 5.3.1 NVMe Storage
    • 5.3.2 Enterprise SSDs
    • 5.3.3 Network-Attached Storage
    • 5.3.4 Storage Area Networks
  • 5.4 Power Infrastructure
    • 5.4.1 UPS Systems
    • 5.4.2 Power Distribution Units
    • 5.4.3 Busways and Power Distribution Systems
    • 5.4.4 Backup Power Systems

6 Global AI Data Center Infrastructure Market, By Cooling Infrastructure

  • 6.1 Air Cooling
  • 6.2 Direct-to-Chip Liquid Cooling
  • 6.3 Immersion Cooling
  • 6.4 Rear-Door Heat Exchangers
  • 6.5 Hybrid Cooling Systems

7 Global AI Data Center Infrastructure Market, By Data Center Type

  • 7.1 Hyperscale Data Centers
  • 7.2 Colocation Data Centers
  • 7.3 Enterprise Data Centers
  • 7.4 Edge and Modular Data Centers

8 Global AI Data Center Infrastructure Market, By Rack Density

  • 8.1 Below 20 kW per Rack
  • 8.2 20-50 kW per Rack
  • 8.3 50-100 kW per Rack
  • 8.4 Above 100 kW per Rack

9 Global AI Data Center Infrastructure Market, By Deployment Model

  • 9.1 New-Build AI Data Centers
  • 9.2 Retrofitted AI Data Centers
  • 9.3 Modular AI Data Centers

10 Global AI Data Center Infrastructure Market, By Application

  • 10.1 AI Model Training
  • 10.2 AI Inference
  • 10.3 Generative AI
  • 10.4 High-Performance Computing
  • 10.5 Large-Scale Data Analytics
  • 10.6 Scientific and Research Computing

11 Global AI Data Center Infrastructure Market, By End User

  • 11.1 Cloud Service Providers
  • 11.2 Hyperscale Technology Companies
  • 11.3 Colocation Providers
  • 11.4 Enterprises
  • 11.5 Government and Research Institutions
  • 11.6 Financial Services Organizations
  • 11.7 Healthcare and Life Sciences Organizations

12 Global AI Data Center Infrastructure Market, By Geography

  • 12.1 North America
    • 12.1.1 United States
    • 12.1.2 Canada
    • 12.1.3 Mexico
  • 12.2 Europe
    • 12.2.1 United Kingdom
    • 12.2.2 Germany
    • 12.2.3 France
    • 12.2.4 Italy
    • 12.2.5 Spain
    • 12.2.6 Netherlands
    • 12.2.7 Belgium
    • 12.2.8 Sweden
    • 12.2.9 Switzerland
    • 12.2.10 Poland
    • 12.2.11 Rest of Europe
  • 12.3 Asia Pacific
    • 12.3.1 China
    • 12.3.2 Japan
    • 12.3.3 India
    • 12.3.4 South Korea
    • 12.3.5 Australia
    • 12.3.6 Indonesia
    • 12.3.7 Thailand
    • 12.3.8 Malaysia
    • 12.3.9 Singapore
    • 12.3.10 Vietnam
    • 12.3.11 Rest of Asia Pacific
  • 12.4 South America
    • 12.4.1 Brazil
    • 12.4.2 Argentina
    • 12.4.3 Colombia
    • 12.4.4 Chile
    • 12.4.5 Peru
    • 12.4.6 Rest of South America
  • 12.5 Rest of the World (RoW)
    • 12.5.1 Middle East
      • 12.5.1.1 Saudi Arabia
      • 12.5.1.2 United Arab Emirates
      • 12.5.1.3 Qatar
      • 12.5.1.4 Israel
      • 12.5.1.5 Rest of Middle East
    • 12.5.2 Africa
      • 12.5.2.1 South Africa
      • 12.5.2.2 Egypt
      • 12.5.2.3 Morocco
      • 12.5.2.4 Rest of Africa

13 Strategic Market Intelligence

  • 13.1 Industry Value Network and Supply Chain Assessment
  • 13.2 White-Space and Opportunity Mapping
  • 13.3 Product Evolution and Market Life Cycle Analysis
  • 13.4 Channel, Distributor, and Go-to-Market Assessment

14 Industry Developments and Strategic Initiatives

  • 14.1 Mergers and Acquisitions
  • 14.2 Partnerships, Alliances, and Joint Ventures
  • 14.3 New Product Launches and Certifications
  • 14.4 Capacity Expansion and Investments
  • 14.5 Other Strategic Initiatives

15 Company Profiles

  • 15.1 NVIDIA Corporation
  • 15.2 Advanced Micro Devices, Inc.
  • 15.3 Intel Corporation
  • 15.4 Dell Technologies Inc.
  • 15.5 Hewlett Packard Enterprise
  • 15.6 Super Micro Computer, Inc.
  • 15.7 Cisco Systems, Inc.
  • 15.8 Arista Networks, Inc.
  • 15.9 Broadcom Inc.
  • 15.10 Vertiv Holdings Co.
  • 15.11 Schneider Electric SE
  • 15.12 Equinix, Inc.
  • 15.13 Digital Realty Trust, Inc.
  • 15.14 Lenovo Group Limited
  • 15.15 Huawei Technologies Co., Ltd.

List of Tables

  • Table 1 Global AI Data Center Infrastructure Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI Data Center Infrastructure Market Outlook, By Infrastructure Type (2023-2034) ($MN)
  • Table 3 Global AI Data Center Infrastructure Market Outlook, By Computing Infrastructure (2023-2034) ($MN)
  • Table 4 Global AI Data Center Infrastructure Market Outlook, By AI Accelerators (2023-2034) ($MN)
  • Table 5 Global AI Data Center Infrastructure Market Outlook, By AI Servers (2023-2034) ($MN)
  • Table 6 Global AI Data Center Infrastructure Market Outlook, By GPU Systems (2023-2034) ($MN)
  • Table 7 Global AI Data Center Infrastructure Market Outlook, By CPU and Heterogeneous Computing Systems (2023-2034) ($MN)
  • Table 8 Global AI Data Center Infrastructure Market Outlook, By Networking Infrastructure (2023-2034) ($MN)
  • Table 9 Global AI Data Center Infrastructure Market Outlook, By High-Speed Ethernet (2023-2034) ($MN)
  • Table 10 Global AI Data Center Infrastructure Market Outlook, By InfiniBand (2023-2034) ($MN)
  • Table 11 Global AI Data Center Infrastructure Market Outlook, By Optical Networking (2023-2034) ($MN)
  • Table 12 Global AI Data Center Infrastructure Market Outlook, By Network Switches and Routers (2023-2034) ($MN)
  • Table 13 Global AI Data Center Infrastructure Market Outlook, By Storage Infrastructure (2023-2034) ($MN)
  • Table 14 Global AI Data Center Infrastructure Market Outlook, By NVMe Storage (2023-2034) ($MN)
  • Table 15 Global AI Data Center Infrastructure Market Outlook, By Enterprise SSDs (2023-2034) ($MN)
  • Table 16 Global AI Data Center Infrastructure Market Outlook, By Network-Attached Storage (2023-2034) ($MN)
  • Table 17 Global AI Data Center Infrastructure Market Outlook, By Storage Area Networks (2023-2034) ($MN)
  • Table 18 Global AI Data Center Infrastructure Market Outlook, By Power Infrastructure (2023-2034) ($MN)
  • Table 19 Global AI Data Center Infrastructure Market Outlook, By UPS Systems (2023-2034) ($MN)
  • Table 20 Global AI Data Center Infrastructure Market Outlook, By Power Distribution Units (2023-2034) ($MN)
  • Table 21 Global AI Data Center Infrastructure Market Outlook, By Busways and Power Distribution Systems (2023-2034) ($MN)
  • Table 22 Global AI Data Center Infrastructure Market Outlook, By Backup Power Systems (2023-2034) ($MN)
  • Table 23 Global AI Data Center Infrastructure Market Outlook, By Cooling Infrastructure (2023-2034) ($MN)
  • Table 24 Global AI Data Center Infrastructure Market Outlook, By Air Cooling (2023-2034) ($MN)
  • Table 25 Global AI Data Center Infrastructure Market Outlook, By Direct-to-Chip Liquid Cooling (2023-2034) ($MN)
  • Table 26 Global AI Data Center Infrastructure Market Outlook, By Immersion Cooling (2023-2034) ($MN)
  • Table 27 Global AI Data Center Infrastructure Market Outlook, By Rear-Door Heat Exchangers (2023-2034) ($MN)
  • Table 28 Global AI Data Center Infrastructure Market Outlook, By Hybrid Cooling Systems (2023-2034) ($MN)
  • Table 29 Global AI Data Center Infrastructure Market Outlook, By Data Center Type (2023-2034) ($MN)
  • Table 30 Global AI Data Center Infrastructure Market Outlook, By Hyperscale Data Centers (2023-2034) ($MN)
  • Table 31 Global AI Data Center Infrastructure Market Outlook, By Colocation Data Centers (2023-2034) ($MN)
  • Table 32 Global AI Data Center Infrastructure Market Outlook, By Enterprise Data Centers (2023-2034) ($MN)
  • Table 33 Global AI Data Center Infrastructure Market Outlook, By Edge and Modular Data Centers (2023-2034) ($MN)
  • Table 34 Global AI Data Center Infrastructure Market Outlook, By Rack Density (2023-2034) ($MN)
  • Table 35 Global AI Data Center Infrastructure Market Outlook, By Below 20 kW per Rack (2023-2034) ($MN)
  • Table 36 Global AI Data Center Infrastructure Market Outlook, By 20-50 kW per Rack (2023-2034) ($MN)
  • Table 37 Global AI Data Center Infrastructure Market Outlook, By 50-100 kW per Rack (2023-2034) ($MN)
  • Table 38 Global AI Data Center Infrastructure Market Outlook, By Above 100 kW per Rack (2023-2034) ($MN)
  • Table 39 Global AI Data Center Infrastructure Market Outlook, By Deployment Model (2023-2034) ($MN)
  • Table 40 Global AI Data Center Infrastructure Market Outlook, By New-Build AI Data Centers (2023-2034) ($MN)
  • Table 41 Global AI Data Center Infrastructure Market Outlook, By Retrofitted AI Data Centers (2023-2034) ($MN)
  • Table 42 Global AI Data Center Infrastructure Market Outlook, By Modular AI Data Centers (2023-2034) ($MN)
  • Table 43 Global AI Data Center Infrastructure Market Outlook, By Application (2023-2034) ($MN)
  • Table 44 Global AI Data Center Infrastructure Market Outlook, By AI Model Training (2023-2034) ($MN)
  • Table 45 Global AI Data Center Infrastructure Market Outlook, By AI Inference (2023-2034) ($MN)
  • Table 46 Global AI Data Center Infrastructure Market Outlook, By Generative AI (2023-2034) ($MN)
  • Table 47 Global AI Data Center Infrastructure Market Outlook, By High-Performance Computing (2023-2034) ($MN)
  • Table 48 Global AI Data Center Infrastructure Market Outlook, By Large-Scale Data Analytics (2023-2034) ($MN)
  • Table 49 Global AI Data Center Infrastructure Market Outlook, By Scientific and Research Computing (2023-2034) ($MN)
  • Table 50 Global AI Data Center Infrastructure Market Outlook, By End User (2023-2034) ($MN)
  • Table 51 Global AI Data Center Infrastructure Market Outlook, By Cloud Service Providers (2023-2034) ($MN)
  • Table 52 Global AI Data Center Infrastructure Market Outlook, By Hyperscale Technology Companies (2023-2034) ($MN)
  • Table 53 Global AI Data Center Infrastructure Market Outlook, By Colocation Providers (2023-2034) ($MN)
  • Table 54 Global AI Data Center Infrastructure Market Outlook, By Enterprises (2023-2034) ($MN)
  • Table 55 Global AI Data Center Infrastructure Market Outlook, By Government and Research Institutions (2023-2034) ($MN)
  • Table 56 Global AI Data Center Infrastructure Market Outlook, By Financial Services Organizations (2023-2034) ($MN)
  • Table 57 Global AI Data Center Infrastructure Market Outlook, By Healthcare and Life Sciences Organizations (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.