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商品編碼

1654693

全球人工智慧資料中心市場 - 2025 至 2032 年

Global AI Data Centers Market - 2025-2032

出版日期: 2025年02月13日 | 出版商:

DataM Intelligence | 英文 205 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

2024 年全球人工智慧資料中心市場規模達到 136.7 億美元，預計到 2032 年將達到 789.1 億美元，2025-2032 年預測期間的複合年成長率為 24.50%。

全球人工智慧資料中心市場正在經歷顯著成長，這得益於支援人工智慧應用的運算能力需求的不斷成長。這些中心對於推動機器學習、自然語言處理和電腦視覺的進步至關重要。政府和企業都在大力投資人工智慧驅動的基礎設施，以提高效率和競爭力。

根據國際能源總署 (IEA) 的數據，2022 年全球資料中心的電力需求接近 460 太瓦時 (TWh)，預計到 2030資料，特定於 AI 的工作負載將大幅增加資料消耗。這一趨勢減少了延遲並增強了隱私，使其成為自動駕駛汽車和智慧城市應用的理想選擇。

由於對人工智慧基礎設施的大量投資和政府的支持舉措，亞太地區成為人工智慧資料中心成長最快的市場。中國、印度、日本等國家正在推動人工智慧策略，推動技術創新。中國工業和資訊化部（MIIT）成立了新的人工智慧（AI）投資基金，初始資本為 82 億美元。此外，到 2025 年，人工智慧預計將為印度經濟貢獻 5,000 億美元，並將徹底改變農業、醫療保健、城市規劃和製造業等關鍵產業。

動力學

數據和人工智慧應用呈指數級成長

數位資料的爆炸性成長是人工智慧資料中心成長的主要驅動力。 2023 年產生的 120 zetta位元組預計到 2025 年將成長 150% 以上，達到 181 zetta位元組。醫療保健、汽車和零售等行業迅速採用人工智慧，需要能夠管理大量資料集和執行複雜運算的強大資料中心基礎設施。

醫療保健領域的人工智慧應用，例如 IBM 的 Watson，需要大量即時資料處理以進行診斷和個人化醫療。同樣，特斯拉等公司的自動駕駛汽車依賴資料中心進行人工智慧模型訓練和即時決策。貿易和商業的數位轉型也增加了對大容量人工智慧資料中心的需求，以處理電子商務交易、物流和客戶洞察。

政府對人工智慧基礎設施的措施和投資

世界各國政府都優先發展人工智慧生態系統，直接推動先進資料中心的需求。例如，歐盟委員會宣布啟動新的「地平線歐洲」計劃，並設立超過1.16億美元的龐大資金池，用於資助尖端人工智慧和量子技術項目。同時，美國政府在2025年1月宣布撥款5,000億美元用於人工智慧基礎建設，強調資料中心對於實現國家人工智慧目標的重要性。

新興經濟體的政府也正在加大投資。印度政府支持的人工智慧創新中心應設立在二線和三線城市，以培養當地人才並促進創新，其中包括資料中心。這些措施正在創造一個有利於成長的環境，並強調人工智慧推動的經濟發展。人工智慧正在改變資料中心的能源管理，透過預測性維護和動態冷卻系統降低營運成本和碳足跡。

高能耗和環境問題

人工智慧資料中心是能源密集的，伺服器和冷卻系統佔其電力消耗的很大一部分。根據天然氣出口國論壇 (GECF) 的數據，到 2030 年，人工智慧工作負載將佔全球資料中心電力需求的 15%，從而引發環境擔憂和監管審查。能源使用也會直接影響成本。

此外，電力和冷卻的營運費用可能佔資料中心預算的 60-70％。此外，環保組織正在推動更嚴格的碳中和標準，這使得現有設施的運作變得複雜。現實生活中的例子，例如Google在丹麥投資 6 億美元建立碳中和資料中心，展示了緩解能源挑戰的努力，但也凸顯了實現永續發展的巨大財務負擔。

The global AI data centers market is witnessing remarkable growth, driven by the increasing demand for computational power to support AI applications. These centers are pivotal for enabling advancements in machine learning, natural language processing and computer vision. Governments and enterprises alike are investing heavily in AI-driven infrastructure to improve efficiency and competitiveness.

According to the International Energy Agency (IEA), the global data center electricity demand in 2022 was closer to 460 terawatt-hours (TWh) and AI-specific workloads are projected to increase energy consumption significantly by 2030. Edge AI computing is revolutionizing the data center market by enabling real-time analytics closer to the data source. This trend reduces latency and enhances privacy, making it ideal for autonomous vehicles and smart city applications.

Asia-Pacific leads as the fastest-growing market for AI data centers due to substantial investments in AI infrastructure and supportive government initiatives. Countries such as China, India and Japan are advancing AI strategies to drive technological innovation. The Ministry of Industry and Information Technology (MIIT) in China has created a new artificial intelligence (AI) investment fund, with an initial capital of US$ 8.2 billion. Additionally, In India, with the potential to contribute US$ 500 billion to the economy by 2025, AI stands to revolutionize key sectors such as agriculture, healthcare, urban planning and manufacturing.

Dynamics

Exponential Growth of Data and AI Applications

The explosion of digital data is a major driver for AI data center growth. The 120 zettabytes generated in 2023 are expected to increase by over 150% in 2025, hitting 181 zettabytes. The rapid adoption of AI across industries, including healthcare, automotive and retail, requires robust data center infrastructure capable of managing massive datasets and performing complex computations.

AI applications in healthcare, such as IBM's Watson, require extensive real-time data processing for diagnostics and personalized medicine. Similarly, autonomous vehicles from companies like Tesla depend on data centers for AI model training and real-time decision-making. Digital transformation in trade and commerce has also escalated the need for high-capacity AI data centers to process e-commerce transactions, logistics and customer insights.

Government Initiatives and Investments in AI Infrastructure

Governments globally are prioritizing the development of AI ecosystems, directly fueling demand for advanced data centers. For example, the European Commission has announced the launch of new Horizon Europe calls, with a substantial funding pool of over US$ 116 million in funding for cutting-edge AI and quantum technology projects. Meanwhile, In January 2025, the government of the US announced US$ 500 billion to fund infrastructure for artificial intelligence, emphasizing the importance of data centers in achieving national AI ambitions.

Governments in emerging economies are also stepping up investments. India's government-backed AI innovation hubs should be set up in tier-2 and tier-3 cities to nurture local talent and foster innovation, which include data centers. Such initiatives are creating an environment ripe for growth, with an emphasis on AI-powered economic development. AI is transforming the energy management of data centers, with predictive maintenance and dynamic cooling systems reducing operational costs and carbon footprints.

High Energy Consumption and Environmental Concerns

AI data centers are energy-intensive, with servers and cooling systems accounting for a significant portion of their power consumption. According to the Gas Exporting Countries Forum (GECF), AI workloads will contribute 15% of the global data center electricity demand by 2030, leading to environmental concerns and regulatory scrutiny. Energy usage also has direct cost implications.

Furthermore, the operational expenses for power and cooling can account for up to 60-70% of a data center's budget. Moreover, environmental organizations are pushing for stricter carbon neutrality standards, complicating operations for existing facilities. Real-life instances, such as Google's US$ 600 million investment in carbon-neutral data centers in Denmark, showcase efforts to mitigate energy challenges but highlight the substantial financial burden of achieving sustainability.

Segment Analysis

The global AI data centers market is segmented based on component, deployment, mode, data center type, end-user and region.

Rising Demand for AI Training Data Centers Services

AI training workloads require enormous computational resources, making training-focused data centers the highest-demand segment. As AI models like OpenAI's GPT and Google DeepMind's AlphaFold advance, their training involves processing petabytes of data, requiring cutting-edge infrastructure.

The training-focused facilities now account for a substantial percentage of investment in global AI data center investments. These facilities prioritize high-density servers equipped with GPUs and TPUs, allowing parallel computations to expedite AI training. This demand is further fueled by advancements in industries such as pharmaceuticals, where AI is used for drug discovery, a process heavily reliant on extensive model training.

Geographical Penetration

Technological Leadership of North America

North America, particularly US, stands as the largest share for AI data centers, largely due to its technological leadership and substantial investments in research and development. The U.S. with nearly 6,300 patents filed since 2014, underscoring its critical role in the advancement of AI technologies. Silicon Valley serves as the heart of this innovation, attracting major players like Amazon Web Services, Microsoft Azure and Google Cloud, all of which are expanding their data center operations to accommodate the increasing demands of AI workloads.

Additionally, initiatives such as Canada's Pan-Canadian Artificial Intelligence Strategy illustrate regional efforts to promote ethical and scalable growth in AI infrastructure. The rapid expansion of AI data centers is driven by the need for high-performance computing capabilities that support advanced AI applications. This growth necessitates innovative designs and significant power resources to meet rising demand.

As industries increasingly adopt AI technologies, the demand for data storage and processing is projected to soar, prompting substantial investments from tech giants. These developments not only highlight the competitive landscape of AI infrastructure but also raise challenges related to energy consumption and community acceptance of new data center projects.

Competitive Landscape

The major global players in the market include Schneider Electric, Amazon.com, Inc, Microsoft, IBM Corp, NVIDIA Corporation, Cisco Systems, Inc, Cadence Design Systems, Inc, Advanced Micro Devices, Inc, CyrusOne and Juniper Networks, Inc.

Sustainable Analysis

Sustainability in the AI data center market is increasingly focused on minimizing carbon footprints and optimizing energy consumption. Major companies are making significant investments in renewable energy sources, with reports indicating that 100% of Google's data center operations were powered by renewable energy as of 2023, according to the Google's sustainability reports.

Innovative cooling techniques, such as liquid immersion cooling, are also being adopted to enhance energy efficiency. For instance, Microsoft's Project Natick, an underwater data center initiative, showcased a remarkable improvement in energy efficiency. These advancements align with global sustainability initiatives like the Paris Agreement, which promote environmentally responsible practices across industries.

The integration of artificial intelligence (AI) plays a crucial role in enhancing the sustainability of data centers. AI technologies facilitate real-time monitoring and optimization of energy usage, particularly in cooling systems, which are traditionally energy-intensive. By employing predictive analytics, AI can dynamically adjust cooling needs based on workload demands and external conditions, thereby conserving energy and extending equipment lifespan.

Key Developments

January 2025, Reliance's proposed data center is set to outscale the world's largest existing facilities, currently operating under one gigawatt, with plans to be three times larger. By acquiring Nvidia's advanced AI chips, Reliance aims to efficiently process massive data volumes, powering AI applications in machine learning, automation and large-scale data analytics across industries.
January 2024, The UK plans to establish "AI Growth Zones" to promote technology growth and bolster the AI ecosystem, starting with the first zone in Culham, home to the UK Atomic Energy Authority. These zones will offer streamlined planning approvals for data centers and enhanced electricity access. As part of the initiative, the government will create an energy council comprising public and private officials to explore powering data centers with small modular nuclear reactors.
September 2024, BlackRock, Global Infrastructure Partners (GIP), Microsoft and MGX have announced the formation of the Global AI Infrastructure Investment Partnership (GAIIP), aimed at addressing the growing demand for computing power required to support advanced AI capabilities.

By Component

Hardware
- Processors
- Networking Equipment
- Storage
- Others
Software
- AI/ML Frameworks
- Data Management and Orchestration Tools
- Security Tools
- Others
Services
- Installation and Integration.
- Managed Services
- Consulting Services

By Deployment Mode

On-Premises
Cloud-Based
Hybrid

By Data Center Type

Hyperscale Data Center
Colocation Data Center
Edge Data Center
Others (Enterprise, Hybrid, etc.)

By End-User

Healthcare
Retail
IT and Telecom
BFSI
Automotive
Media & Entertainment
Manufacturing
Others

By Region

North America
- US
- Canada
- Mexico
Europe
- Germany
- UK
- France
- Italy
- Spain
- Rest of Europe
South America
- Brazil
- Argentina
- Rest of South America
Asia-Pacific
- China
- India
- Japan
- Australia
- Rest of Asia-Pacific
Middle East and Africa

Why Purchase the Report?

To visualize the global AI data centers market segmentation based on component, deployment mode, data center type, end-user and region.
Identify commercial opportunities by analyzing trends and co-development.
Excel data sheet with numerous data points at the AI data center market level for all segments.
PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
Product mapping available as excel consisting of key products of all the major players.

The global AI data centers market report would provide approximately 70 tables, 68 figures and 205 pages.

Target Audience 2024

Manufacturers/ Buyers
Industry Investors/Investment Bankers
Research Professionals
Emerging Companies

1. Methodology and Scope

1.1. Research Methodology
1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

3.1. Snippet by Component
3.2. Snippet by Deployment Mode
3.3. Snippet by Data Center Type
3.4. Snippet by End-User
3.5. Snippet by Region

4. Dynamics

4.1. Impacting Factors
- 4.1.1. Drivers
  - 4.1.1.1. Exponential Growth of Data and AI Applications
  - 4.1.1.2. Government Initiatives and Investments in AI Infrastructure
- 4.1.2. Restraints
  - 4.1.2.1. High Energy Consumption and Environmental Concerns
- 4.1.3. Opportunity
- 4.1.4. Impact Analysis

5. Industry Analysis

5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Sustainable Analysis
5.6. DMI Opinion

6. By Component

6.1. Introduction
- 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 6.1.2. Market Attractiveness Index, By Component
6.2. Hardware*
- 6.2.1. Introduction
- 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
- 6.2.3. Processors
- 6.2.4. Networking Equipment
- 6.2.5. Storage
- 6.2.6. Others
6.3. Software
- 6.3.1. AI/ML Frameworks
- 6.3.2. Data Management and Orchestration Tools
- 6.3.3. Security Tools
- 6.3.4. Others
6.4. Services
- 6.4.1. Installation and Integration.
- 6.4.2. Managed Services
- 6.4.3. Consulting Services

7. By Deployment Mode

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 7.1.2. Market Attractiveness Index, By Deployment Mode
7.2. On-Premises*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Cloud-Based
7.4. Hybrid

8. By Data Center Type

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Center Type
- 8.1.2. Market Attractiveness Index, By Data Center Type
8.2. Hyperscale Data Centers*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Colocation Data Center
8.4. Edge Data Center
8.5. Others

9. By End-User

9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 9.1.2. Market Attractiveness Index, By End-User
9.2. Healthcare*
- 9.2.1. Introduction
- 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. Retail
9.4. IT and Telecom
9.5. BFSI
9.6. Automotive
9.7. Media & Entertainment
9.8. Manufacturing
9.9. Others

10. Sustainability Analysis

10.1. Environmental Analysis
10.2. Economic Analysis
10.3. Governance Analysis

11. By Region

11.1. Introduction
- 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 11.1.2. Market Attractiveness Index, By Region
11.2. North America
- 11.2.1. Introduction
- 11.2.2. Key Region-Specific Dynamics
- 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Components
- 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Center Type
- 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 11.2.7.1. US
  - 11.2.7.2. Canada
  - 11.2.7.3. Mexico
11.3. Europe
- 11.3.1. Introduction
- 11.3.2. Key Region-Specific Dynamics
- 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Components
- 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Center Type
- 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 11.3.7.1. Germany
  - 11.3.7.2. UK
  - 11.3.7.3. France
  - 11.3.7.4. Italy
  - 11.3.7.5. Spain
  - 11.3.7.6. Rest of Europe
11.4. South America
- 11.4.1. Introduction
- 11.4.2. Key Region-Specific Dynamics
- 11.4.3. Key Region-Specific Dynamics
- 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Components
- 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Center Type
- 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 11.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 11.4.8.1. Brazil
  - 11.4.8.2. Argentina
  - 11.4.8.3. Rest of South America
11.5. Asia-Pacific
- 11.5.1. Introduction
- 11.5.2. Key Region-Specific Dynamics
- 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Components
- 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Center Type
- 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 11.5.7.1. China
  - 11.5.7.2. India
  - 11.5.7.3. Japan
  - 11.5.7.4. Australia
  - 11.5.7.5. Rest of Asia-Pacific
11.6. Middle East and Africa
- 11.6.1. Introduction
- 11.6.2. Key Region-Specific Dynamics
- 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Components
- 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Data Center Type
- 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

12. Competitive Landscape

12.1. Competitive Scenario
12.2. Market Positioning/Share Analysis
12.3. Mergers and Acquisitions Analysis

13. Company Profiles

13.1. Schneider Electric*
- 13.1.1. Company Overview
- 13.1.2. Product Portfolio and Description
- 13.1.3. Financial Overview
- 13.1.4. Key Developments
13.2. Amazon.com, Inc
13.3. Microsoft
13.4. IBM corp
13.5. NVIDIA Corporation
13.6. Cisco Systems, Inc
13.7. Cadence Design Systems, Inc.
13.8. Advanced Micro Devices, Inc.
13.9. CyrusOne
13.10. Juniper Networks, Inc.

LIST NOT EXHAUSTIVE