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市场调查报告书

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1654693

全球人工智慧资料中心市场 - 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个工作天内

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简介目录

2024 年全球人工智慧资料中心市场规模达到 136.7 亿美元，预计到 2032 年将达到 789.1 亿美元，2025-2032 年预测期间的复合年增长率为 24.50%。

全球人工智慧资料中心市场正在经历显着成长，这得益于支援人工智慧应用的运算能力需求的不断增长。这些中心对于推动机器学习、自然语言处理和电脑视觉的进步至关重要。政府和企业都在大力投资人工智慧驱动的基础设施，以提高效率和竞争力。

根据国际能源总署 (IEA) 的数据，2022 年全球资料中心的电力需求接近 460 太瓦时 (TWh)，预计到 2030资料，特定于 AI 的工作负载将大幅增加资料消耗。这一趋势减少了延迟并增强了隐私，使其成为自动驾驶汽车和智慧城市应用的理想选择。

由于对人工智慧基础设施的大量投资和政府的支持倡议，亚太地区成为人工智慧资料中心成长最快的市场。中国、印度、日本等国家正在推动人工智慧策略，推动技术创新。中国工业和资讯化部（MIIT）成立了新的人工智慧（AI）投资基金，初始资本为 82 亿美元。此外，到 2025 年，人工智慧预计将为印度经济贡献 5,000 亿美元，并将彻底改变农业、医疗保健、城市规划和製造业等关键产业。

动力学

数据和人工智慧应用呈指数级增长

数位资料的爆炸性成长是人工智慧资料中心成长的主要驱动力。 2023 年产生的 120 zetta位元组预计到 2025 年将成长 150% 以上，达到 181 zetta位元组。医疗保健、汽车和零售等行业迅速采用人工智慧，需要能够管理大量资料集和执行复杂运算的强大资料中心基础设施。

医疗保健领域的人工智慧应用，例如 IBM 的 Watson，需要大量即时资料处理以进行诊断和个人化医疗。同样，特斯拉等公司的自动驾驶汽车依赖资料中心进行人工智慧模型训练和即时决策。贸易和商业的数位转型也增加了对大容量人工智慧资料中心的需求，以处理电子商务交易、物流和客户洞察。

政府对人工智慧基础设施的措施和投资

世界各国政府都优先发展人工智慧生态系统，直接推动先进资料中心的需求。例如，欧盟委员会宣布启动新的「地平线欧洲」计划，并设立超过1.16亿美元的庞大资金池，用于资助尖端人工智慧和量子技术项目。同时，美国政府在2025年1月宣布拨款5,000亿美元用于人工智慧基础建设，强调资料中心对于实现国家人工智慧目标的重要性。

新兴经济体的政府也正在加大投资。印度政府支持的人工智慧创新中心应设立在二线和三线城市，以培养当地人才并促进创新，其中包括资料中心。这些措施正在创造一个有利于成长的环境，并强调人工智慧推动的经济发展。人工智慧正在改变资料中心的能源管理，透过预测性维护和动态冷却系统降低营运成本和碳足迹。

高能耗和环境问题

人工智慧资料中心是能源密集的，伺服器和冷却系统占其电力消耗的很大一部分。根据天然气出口国论坛 (GECF) 的数据，到 2030 年，人工智慧工作负载将占全球资料中心电力需求的 15%，从而引发环境担忧和监管审查。能源使用也会直接影响成本。

此外，电力和冷却的营运费用可能占资料中心预算的 60-70％。此外，环保组织正在推动更严格的碳中和标准，这使得现有设施的运作变得复杂。现实生活中的例子，例如Google在丹麦投资 6 亿美元建立碳中和资料中心，展示了缓解能源挑战的努力，但也凸显了实现永续发展的巨大财务负担。

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