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市場調查報告書
商品編碼
2021628

面向資料中心的人工智慧基礎設施市場：預測至 2034 年—按組件、部署模式、應用、最終用戶和地區分類的全球分析

AI Infrastructure for Data Centers Market Forecasts to 2034 - Global Analysis By Component (Hardware, Software and Services), Deployment, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 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，全球資料中心人工智慧基礎設施市場規模將達到 1,825 億美元，在預測期內將以 23.9% 的複合年成長率成長，到 2034 年將達到 1.0134 兆美元。

資料中心內的人工智慧基礎設施由先進的運算資源、軟體平台和網路解決方案組成，這些方案均針對複雜的人工智慧任務進行了最佳化。關鍵組件包括高效能處理器（例如GPU）、專用加速器、可擴展儲存和高速連接，以確保資料流暢傳輸。高效的溫度控管和電源系統對於持續應對不斷成長的運算負載至關重要。編配平台和人工智慧最佳化的軟體框架能夠提升訓練和推理速度，從而簡化部署。隨著人工智慧整合的不斷深入，現代資料中心正朝著智慧、可擴展且安全的系統演進，能夠高效管理大量數據，從而實現即時洞察和智慧營運。

根據 GRI 2026 年印度資料中心大會的報告，在人工智慧基礎設施超級週期的推動下，預計到 2027 年，印度資料中心產業的運作容量將從 1.3 GW 擴大到 1.7 GW。

巨量資料和分析技術的發展

互聯設備、線上平台和企業營運產生的資料量激增，正在加速對先進資料中心基礎設施的需求。處理大規模資料集需要能夠處理和分析結構化和非結構化資料的系統。人工智慧賦能的基礎架構能夠增強資料管理，並加速洞察生成速度。擴充性的運算和儲存解決方案對於支援這些資料密集型任務至關重要。隨著各組織優先考慮數據驅動的決策，對人工智慧資料中心能力的投資也不斷增加，圖提升了各行各業的數據處理和分析效能。

需要大量資金投入。

資料中心人工智慧基礎設施所需的大量前期投資限制了市場擴張。高效能設備，例如GPU、專用處理器和先進的網路技術，價格不菲。基礎設施升級、冷卻解決方案以及電力系統的額外支出進一步推高了成本。中小企業難以獲得如此龐大的預算，導致採用率低。大型企業也面臨證明投資回報的財務壓力。因此，人工智慧基礎設施的整體發展受到阻礙，尤其是在新興市場和預算限制在決策中起著重要作用的行業。

邊緣運算的擴展

邊緣運算的日益普及為人工智慧基礎設施的開發開闢了新的途徑。隨著連網設備產生的資料量不斷成長，在資訊來源附近進行處理變得至關重要。基於邊緣的人工智慧系統有助於最大限度地減少延遲，並提高即時應用程式的效能。這一趨勢正在推動部署規模更小、效率更高、功能更強大的資料中心。企業正在智慧環境和自動駕駛技術等應用場景中利用邊緣解決方案。隨著對更快處理速度的需求不斷成長，人工智慧基礎設施正在突破傳統資料中心的邊界，為分散式運算環境創造新的成長機會。

科技快速過時

人工智慧技術的快速發展對資料中心基礎設施構成重大風險。由於技術更新換代頻繁，處理器、加速器和其他設備可能迅速過時。這導致需要定期升級，從而增加了財務和營運負擔。未能採用新技術的企業將面臨性能和效率落後的風險。管理這些升級需要專業知識和策略規劃。快速變化的技術所帶來的不確定性使得企業難以進行長期基礎設施投資，進而威脅到市場的永續成長。

新冠疫情的影響：

新冠疫情在加速資料中心人工智慧基礎設施的部署方面發揮了決定性作用。隨著企業轉向數位化營運、遠距辦公和線上平台，對先進運算和數據處理能力的需求迅速成長。這促使企業加大對擴充性的、人工智慧賦能的基礎設施的投資。同時，供應鏈中斷、設備短缺和勞動力短缺等挑戰也影響了成長。儘管如此，疫情凸顯了對人工智慧驅動、適應性強且穩健的資料中心系統的必要性，最終支持了市場的持續擴張，並刺激了技術的進一步進步。

在預測期內，硬體領域預計將佔據最大佔有率。

預計在預測期內，硬體領域將佔據最大的市場佔有率，因為它為高階人工智慧應用提供了所需的基礎運算能力。處理器、加速器、記憶體和網路系統等關鍵組件支援資料分析、模型訓練和即時推理等複雜任務。晶片設計的持續創新和性能提升鞏固了其主導地位。隨著企業不斷擴大人工智慧的應用，對可靠、高容量硬體的需求持續成長。這種持續的需求確保了硬體將繼續保持其在人工智慧基礎設施生態系統中最重要的地位。

預計在預測期內，超大規模雲端服務供應商細分市場將呈現最高的複合年成長率。

在預測期內，受市場對雲端人工智慧解決方案需求不斷成長的推動，超大規模雲端服務供應商預計將呈現最高的成長率。這些公司正積極投資於現代化基礎設施，包括高效能處理器、可擴展儲存和先進的網路系統。各行業對人工智慧服務、分析和機器學習的廣泛應用也推動了這一快速成長。此外，超大規模雲端服務供應商優先考慮創新、能源效率和全球擴充性。這種高度重視使他們能夠滿足不斷成長的客戶需求，從而成為人工智慧基礎設施生態系統中成長最快的細分市場。

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，這得益於其先進的技術環境和創新解決方案的廣泛應用。主要雲端服務供應商、人工智慧公司和資料中心公司的存在正在推動持續的投資和發展。醫療保健、金融和電子商務等領域對人工智慧的強勁需求正在加速市場成長。該地區受益於完善的數位基礎設施、高素質的勞動力和持續的研究舉措。政府對人工智慧技術的支援和資金籌措不斷增加，將進一步鞏固其市場地位，確保北美繼續成為全球人工智慧基礎設施市場的主要貢獻者。

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，這主要得益於技術加速應用和數位化進程的推動。中國、印度和日本等國家正在人工智慧技術、雲端服務和資料中心設施方面進行大量投資。網際網路普及率的提高和連網設備的廣泛應用正在推動對先進基礎設施的需求。政府的支持政策以及電子商務和電信等行業的快速擴張進一步增強了成長前景。這些因素共同促成了亞太地區成為全球人工智慧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享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要企業進行SWOT分析（最多3家公司）
  • 區域細分
    • 應客戶要求，我們提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

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
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：全球資料中心人工智慧基礎設施市場：按組件分類

  • 硬體
  • 軟體
  • 服務

第6章：全球資料中心人工智慧基礎設施市場：依部署方式分類

  • 本地資料中心
  • 基於雲端的基礎設施
  • 混合模式

第7章：全球資料中心人工智慧基礎設施市場：按應用領域分類

  • AI訓練工作量
  • AI推理工作負載
  • 邊緣人工智慧整合
  • AI基礎架構管理與編配

第8章：全球資料中心人工智慧基礎設施市場：按最終用戶分類

  • 超大規模雲端供應商
  • 公司
  • 政府/國防
  • 電信和IT服務供應商
  • 研究機構和學術機構

第9章：全球資料中心人工智慧基礎設施市場：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10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11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12章：公司簡介

  • NVIDIA
  • Advanced Micro Devices（AMD）
  • Intel
  • Microsoft（Azure）
  • Amazon Web Services（AWS）
  • Google Cloud（Alphabet）
  • Meta
  • CoreWeave
  • Digital Realty
  • Equinix
  • Oracle
  • Vertiv
  • Hewlett Packard Enterprise（HPE）
  • Dell Technologies
  • Lenovo
  • IBM
  • Supermicro
  • Applied Digital
Product Code: SMRC34968

According to Stratistics MRC, the Global AI Infrastructure for Data Centers Market is accounted for $182.5 billion in 2026 and is expected to reach $1013.4 billion by 2034 growing at a CAGR of 23.9% during the forecast period. AI infrastructure within data centers comprises a combination of advanced computing resources, software platforms, and networking solutions tailored for demanding AI tasks. Key components include powerful processors like GPUs, dedicated accelerators, expandable storage, and fast connectivity to ensure smooth data flow. Efficient thermal and power systems are crucial for handling increased computational loads sustainably. Deployment is simplified through orchestration platforms and AI-optimized software frameworks that enhance training and inference speed. With rising AI integration, modern data centers are evolving into smart, scalable, and secure systems that efficiently manage large data volumes and enable real-time insights and intelligent operations.

According to the GRI Data Centre India 2026 conference, India's data center sector is scaling from 1.3 GW to 1.7 GW of operational capacity before 2027, driven by an AI infrastructure super-cycle.

Market Dynamics:

Driver:

Growth of big data and analytics

The surge in data produced by connected devices, online platforms, and enterprise operations is accelerating the need for advanced data center infrastructure. Handling large-scale datasets requires systems capable of processing and analyzing both structured and unstructured information. AI-enabled infrastructure enhances data management and enables faster insights generation. Scalable computing and storage solutions are critical to support these data-intensive tasks. As organizations prioritize data-driven decision-making, investments in AI-powered data center capabilities are increasing, ensuring efficient data handling and improved analytical performance across various industries.

Restraint:

High capital investment requirements

The substantial initial investment needed for AI infrastructure in data centers restricts market expansion. High-performance equipment like GPUs, specialized processors, and advanced networking technologies involves considerable expense. Additional spending on infrastructure upgrades, cooling solutions, and power systems further increases costs. Smaller businesses find it challenging to allocate such budgets, reducing adoption rates. Larger enterprises also face financial pressure to justify returns. As a result, the overall growth of AI infrastructure is hindered, especially in emerging markets and sectors where budget limitations play a significant role in decision-making.

Opportunity:

Expansion of edge computing

The growing adoption of edge computing is opening new avenues for AI infrastructure development. With increasing data from connected devices, processing information near its origin is becoming crucial. Edge-based AI systems help minimize delays and improve performance for real-time applications. This trend is encouraging the deployment of smaller, efficient data centers with advanced capabilities. Businesses are leveraging edge solutions for use cases such as smart environments and autonomous technologies. As demand for faster processing grows, AI infrastructure is expanding beyond traditional data centers, creating new growth opportunities in distributed computing environments.

Threat:

Rapid technological obsolescence

The continuous evolution of AI technology presents a major risk for data center infrastructure. Equipment like processors and accelerators may lose relevance quickly due to frequent innovations. This leads to the need for regular upgrades, which increases financial and operational strain. Organizations that do not adopt new technologies risk falling behind in performance and efficiency. Managing these upgrades requires expertise and strategic planning. The uncertainty associated with rapidly changing technology makes it difficult for businesses to make long-term infrastructure investments, posing a threat to sustained growth in the market.

Covid-19 Impact:

The outbreak of COVID-19 played a crucial role in boosting the adoption of AI infrastructure within data centers. As businesses shifted to digital operations, remote working, and online platforms, the demand for advanced computing and data processing capabilities increased rapidly. This led to higher investments in scalable AI-enabled infrastructure. At the same time, challenges such as disrupted supply chains, equipment shortages, and limited workforce availability impacted growth. Nevertheless, the pandemic emphasized the need for adaptable and robust data center systems powered by AI, ultimately supporting sustained market expansion and encouraging further technological advancements.

The hardware segment is expected to be the largest during the forecast period

The hardware segment is expected to account for the largest market share during the forecast period because it provides the fundamental computing power required for advanced AI applications. Key components, including processors, accelerators, memory, and networking systems, support complex tasks such as data analysis, model training, and real-time inference. Ongoing innovations in chip design and performance improvements contribute to its leading position. As businesses expand their use of artificial intelligence, the need for reliable and high-capacity hardware continues to grow. This sustained demand ensures that hardware remains the most significant segment within the AI infrastructure ecosystem.

The hyperscale cloud providers segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the hyperscale cloud providers segment is predicted to witness the highest growth rate, driven by rising demand for cloud-enabled AI solutions. These companies are heavily investing in modern infrastructure, including powerful processors, scalable storage, and advanced networking systems. The growing use of AI services, analytics, and machine learning across industries supports this rapid expansion. Furthermore, hyperscale providers prioritize innovation, energy efficiency, and global scalability. This strong focus enables them to meet increasing customer needs, making them the fastest-growing segment within the AI infrastructure ecosystem.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, supported by its advanced technology landscape and widespread adoption of innovative solutions. The presence of key cloud providers, AI firms, and data center companies fuels continuous investment and development. Strong demand for AI across sectors like healthcare, finance, and e-commerce accelerates market growth. The region benefits from well-established digital infrastructure, a skilled workforce, and ongoing research initiatives. Government backing and rising funding for AI technologies further enhance its position, ensuring North America remains the leading contributor to the global AI infrastructure market.

Region with highest CAGR:

Over the forecast period, the Asia-Pacific region is anticipated to exhibit the highest CAGR, driven by accelerating technological adoption and digitalization. Countries like China, India, and Japan are heavily investing in AI technologies, cloud services, and data center facilities. Increasing internet penetration and the widespread use of connected devices are boosting demand for advanced infrastructure. Supportive government policies and rapid expansion of sectors such as e-commerce and telecom further enhance growth prospects. These factors collectively position Asia-Pacific as the most rapidly expanding region in the global AI infrastructure landscape.

Key players in the market

Some of the key players in AI Infrastructure for Data Centers Market include NVIDIA, Advanced Micro Devices (AMD), Intel, Microsoft (Azure), Amazon Web Services (AWS), Google Cloud (Alphabet), Meta, CoreWeave, Digital Realty, Equinix, Oracle, Vertiv, Hewlett Packard Enterprise (HPE), Dell Technologies, Lenovo, IBM, Supermicro and Applied Digital.

Key Developments:

In April 2026, Intel Corp plans to invest an additional $15 million in AI chip startup SambaNova Systems, according to a Reuters review of corporate records, as the semiconductor company deepens its focus on artificial intelligence infrastructure. The proposed investment, which is subject to regulatory approval, would raise Intel's ownership stake in SambaNova to approximately 9%.

In March 2026, NVIDIA and Marvell Technology, Inc. announced a strategic partnership to connect Marvell to the NVIDIA AI factory and AI-RAN ecosystem through NVIDIA NVLink Fusion(TM), offering customers building on NVIDIA architectures greater choice and flexibility in developing next-generation infrastructure. The companies will also collaborate on silicon photonics technology.

In January 2026, Microsoft Corp has been awarded a $170,444,462 firm-fixed-price task order for the Cloud One Program by the U.S. Department of War. The contract will provide Microsoft Azure cloud service offerings to support the Air Force's Cloud One Program and its customers. Work on the project will be performed at Microsoft's designated facilities across the contiguous United States.

Components Covered:

  • Hardware
  • Software
  • Services

Deployments Covered:

  • On-premises Data Centers
  • Cloud-based Infrastructure
  • Hybrid Models

Applications Covered:

  • AI Training Workloads
  • AI Inference Workloads
  • Edge AI integration
  • AI Infrastructure Management & Orchestration

End Users Covered:

  • Hyperscale Cloud Providers
  • Enterprises
  • Government & Defense
  • Telecom & IT Service Providers
  • Research & Academia

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 Infrastructure for Data Centers Market, By Component

  • 5.1 Hardware
  • 5.2 Software
  • 5.3 Services

6 Global AI Infrastructure for Data Centers Market, By Deployment

  • 6.1 On-premises Data Centers
  • 6.2 Cloud-based Infrastructure
  • 6.3 Hybrid Models

7 Global AI Infrastructure for Data Centers Market, By Application

  • 7.1 AI Training Workloads
  • 7.2 AI Inference Workloads
  • 7.3 Edge AI integration
  • 7.4 AI Infrastructure Management & Orchestration

8 Global AI Infrastructure for Data Centers Market, By End User

  • 8.1 Hyperscale Cloud Providers
  • 8.2 Enterprises
  • 8.3 Government & Defense
  • 8.4 Telecom & IT Service Providers
  • 8.5 Research & Academia

9 Global AI Infrastructure for Data Centers Market, By Geography

  • 9.1 North America
    • 9.1.1 United States
    • 9.1.2 Canada
    • 9.1.3 Mexico
  • 9.2 Europe
    • 9.2.1 United Kingdom
    • 9.2.2 Germany
    • 9.2.3 France
    • 9.2.4 Italy
    • 9.2.5 Spain
    • 9.2.6 Netherlands
    • 9.2.7 Belgium
    • 9.2.8 Sweden
    • 9.2.9 Switzerland
    • 9.2.10 Poland
    • 9.2.11 Rest of Europe
  • 9.3 Asia Pacific
    • 9.3.1 China
    • 9.3.2 Japan
    • 9.3.3 India
    • 9.3.4 South Korea
    • 9.3.5 Australia
    • 9.3.6 Indonesia
    • 9.3.7 Thailand
    • 9.3.8 Malaysia
    • 9.3.9 Singapore
    • 9.3.10 Vietnam
    • 9.3.11 Rest of Asia Pacific
  • 9.4 South America
    • 9.4.1 Brazil
    • 9.4.2 Argentina
    • 9.4.3 Colombia
    • 9.4.4 Chile
    • 9.4.5 Peru
    • 9.4.6 Rest of South America
  • 9.5 Rest of the World (RoW)
    • 9.5.1 Middle East
      • 9.5.1.1 Saudi Arabia
      • 9.5.1.2 United Arab Emirates
      • 9.5.1.3 Qatar
      • 9.5.1.4 Israel
      • 9.5.1.5 Rest of Middle East
    • 9.5.2 Africa
      • 9.5.2.1 South Africa
      • 9.5.2.2 Egypt
      • 9.5.2.3 Morocco
      • 9.5.2.4 Rest of Africa

10 Strategic Market Intelligence

  • 10.1 Industry Value Network and Supply Chain Assessment
  • 10.2 White-Space and Opportunity Mapping
  • 10.3 Product Evolution and Market Life Cycle Analysis
  • 10.4 Channel, Distributor, and Go-to-Market Assessment

11 Industry Developments and Strategic Initiatives

  • 11.1 Mergers and Acquisitions
  • 11.2 Partnerships, Alliances, and Joint Ventures
  • 11.3 New Product Launches and Certifications
  • 11.4 Capacity Expansion and Investments
  • 11.5 Other Strategic Initiatives

12 Company Profiles

  • 12.1 NVIDIA
  • 12.2 Advanced Micro Devices (AMD)
  • 12.3 Intel
  • 12.4 Microsoft (Azure)
  • 12.5 Amazon Web Services (AWS)
  • 12.6 Google Cloud (Alphabet)
  • 12.7 Meta
  • 12.8 CoreWeave
  • 12.9 Digital Realty
  • 12.10 Equinix
  • 12.11 Oracle
  • 12.12 Vertiv
  • 12.13 Hewlett Packard Enterprise (HPE)
  • 12.14 Dell Technologies
  • 12.15 Lenovo
  • 12.16 IBM
  • 12.17 Supermicro
  • 12.18 Applied Digital

List of Tables

  • Table 1 Global AI Infrastructure for Data Centers Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI Infrastructure for Data Centers Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI Infrastructure for Data Centers Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 4 Global AI Infrastructure for Data Centers Market Outlook, By Software (2023-2034) ($MN)
  • Table 5 Global AI Infrastructure for Data Centers Market Outlook, By Services (2023-2034) ($MN)
  • Table 6 Global AI Infrastructure for Data Centers Market Outlook, By Deployment (2023-2034) ($MN)
  • Table 7 Global AI Infrastructure for Data Centers Market Outlook, By On-premises Data Centers (2023-2034) ($MN)
  • Table 8 Global AI Infrastructure for Data Centers Market Outlook, By Cloud-based Infrastructure (2023-2034) ($MN)
  • Table 9 Global AI Infrastructure for Data Centers Market Outlook, By Hybrid Models (2023-2034) ($MN)
  • Table 10 Global AI Infrastructure for Data Centers Market Outlook, By Application (2023-2034) ($MN)
  • Table 11 Global AI Infrastructure for Data Centers Market Outlook, By AI Training Workloads (2023-2034) ($MN)
  • Table 12 Global AI Infrastructure for Data Centers Market Outlook, By AI Inference Workloads (2023-2034) ($MN)
  • Table 13 Global AI Infrastructure for Data Centers Market Outlook, By Edge AI integration (2023-2034) ($MN)
  • Table 14 Global AI Infrastructure for Data Centers Market Outlook, By AI Infrastructure Management & Orchestration (2023-2034) ($MN)
  • Table 15 Global AI Infrastructure for Data Centers Market Outlook, By End User (2023-2034) ($MN)
  • Table 16 Global AI Infrastructure for Data Centers Market Outlook, By Hyperscale Cloud Providers (2023-2034) ($MN)
  • Table 17 Global AI Infrastructure for Data Centers Market Outlook, By Enterprises (2023-2034) ($MN)
  • Table 18 Global AI Infrastructure for Data Centers Market Outlook, By Government & Defense (2023-2034) ($MN)
  • Table 19 Global AI Infrastructure for Data Centers Market Outlook, By Telecom & IT Service Providers (2023-2034) ($MN)
  • Table 20 Global AI Infrastructure for Data Centers Market Outlook, By Research & Academia (2023-2034) ($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.