人工智慧基础设施市场－全球产业规模、份额、趋势、机会和预测，按产品、部署、最终用户、地区和竞争细分，2020-2030F

2024 年全球人工智慧基础设施市场价值为 1,325.2 亿美元，预计到 2030 年将达到 3,713.7 亿美元，复合年增长率为 18.74%。全球人工智慧基础设施市场是指支援人工智慧应用开发、部署和扩展的硬体、软体和服务生态系统。这包括先进的运算硬件，如图形处理单元、中央处理器和专用积体电路，以及储存系统、网路解决方案和针对人工智慧最佳化的云端平台。这些元素共同实现了更快的资料处理、高效能分析以及复杂机器学习和深度学习模型的高效训练。随着全球各地的产业将人工智慧融入其运营，强大的人工智慧基础设施已成为推动创新、自动化和竞争力的基础。

高效能运算能力需求的激增以及资料产生的指数级增长，加速了人工智慧基础设施市场的成长。医疗保健、金融、汽车、零售和製造等领域的企业正在增加对人工智慧基础设施的投资，以支援预测分析、自主系统、个人化医疗和智慧客户互动等应用。此外，基于云端的人工智慧基础设施的扩展正在降低各种规模企业的进入门槛，提供可扩展且经济高效的解决方案，以适应不断变化的工作负载。物联网设备和 5G 技术的快速整合也刺激了需求，因为它们创建了大量资料集，需要先进的基础设施进行即时分析。

由于半导体设计的持续进步、边缘人工智慧的日益普及以及政府和私营部门对数位转型计画的投入，人工智慧基础设施市场将大幅成长。人工智慧在国家安全、智慧城市计画和气候变迁解决方案中日益重要的地位将进一步增强市场发展。科技巨头与基础设施供应商之间的策略合作也正在塑造一个确保可访问性、互通性和创新性的生态系统。随着企业追求效率和敏捷性，对支援人工智慧的资料中心、下一代处理器和整合软体工具的需求将持续增长，这使得人工智慧基础设施市场成为全球技术领域最具活力和高成长的领域之一。

关键市场驱动因素

人工智慧应用对高效能运算 (HPC) 的需求不断增长

主要市场挑战

高昂的资本投资和营运成本

主要市场趋势

产生人工智慧工作负载的快速扩展

目录

第 1 章：解决方案概述

• 市场定义
• 市场范围
  • 覆盖市场
  • 考虑学习的年限
  • 主要市场区隔

第二章：研究方法

第三章：执行摘要

第四章：顾客之声

第五章：全球人工智慧基础设施市场展望

• 市场规模和预测
  • 按价值
• 市场占有率和预测
  • 按产品（计算、记忆体、网路、储存、伺服器软体）
  • 按部署（本地端、云端、混合式）
  • 按最终用户（云端服务提供者、企业、政府组织）
  • 按地区（北美、欧洲、南美、中东和非洲、亚太地区）
• 按公司分类（2024 年）
• 市场地图

第六章：北美人工智慧基础设施市场展望

• 市场规模和预测
• 市场占有率和预测
• 北美：国家分析
  • 美国
  • 加拿大
  • 墨西哥

第七章：欧洲人工智慧基础设施市场展望

• 市场规模和预测
• 市场占有率和预测
• 欧洲：国家分析
  • 德国
  • 法国
  • 英国
  • 义大利
  • 西班牙

第八章：亚太地区人工智慧基础设施市场展望

• 市场规模和预测
• 市场占有率和预测
• 亚太地区：国家分析
  • 中国
  • 印度
  • 日本
  • 韩国
  • 澳洲

第九章：中东和非洲人工智慧基础设施市场展望

• 市场规模和预测
• 市场占有率和预测
• 中东和非洲：国家分析
  • 沙乌地阿拉伯
  • 阿联酋
  • 南非

第十章：南美洲人工智慧基础设施市场展望

• 市场规模和预测
• 市场占有率和预测
• 南美洲：国家分析
  • 巴西
  • 哥伦比亚
  • 阿根廷

第 11 章：市场动态

• 驱动程式
• 挑战

第 12 章：市场趋势与发展

• 合併与收购（如有）
• 产品发布（如有）
• 最新动态

第十三章：公司简介

• Microsoft Corporation
• NVIDIA Corporation
• Google LLC
• Advanced Micro Devices, Inc.
• Samsung Electronics Co., Ltd.
• Micron Technology, Inc.
• Meta Platforms, Inc.
• IBM Corporation
• Cerebras Systems, Inc.
• Astera Labs, Inc.

第 14 章：策略建议

第15章调查会社について・免责事项

The Global AI Infrastructure Market was valued at USD 132.52 Billion in 2024 and is expected to reach USD 371.37 Billion by 2030 with a CAGR of 18.74% through 2030. The Global AI Infrastructure Market refers to the ecosystem of hardware, software, and services that support the development, deployment, and scaling of artificial intelligence applications. This includes advanced computing hardware such as graphics processing units, central processing units, and application-specific integrated circuits, as well as storage systems, networking solutions, and AI-optimized cloud platforms. These elements collectively enable faster data processing, high-performance analytics, and efficient training of complex machine learning and deep learning models. As industries worldwide integrate artificial intelligence into their operations, the role of robust AI infrastructure has become foundational in driving innovation, automation, and competitiveness.

The growth of the AI Infrastructure Market is being accelerated by surging demand for high-performance computing capabilities and the exponential rise in data generation. Enterprises in sectors such as healthcare, finance, automotive, retail, and manufacturing are increasingly investing in AI infrastructure to enable applications like predictive analytics, autonomous systems, personalized medicine, and intelligent customer engagement. Furthermore, the expansion of cloud-based AI infrastructure is lowering the entry barriers for businesses of all sizes, providing scalable and cost-effective solutions that can adapt to evolving workloads. The rapid integration of Internet of Things devices and 5G technology is also fueling demand by creating vast datasets that require advanced infrastructure for real-time analysis.

The AI Infrastructure Market will rise significantly due to ongoing advancements in semiconductor design, the growing popularity of edge AI, and government as well as private sector investments in digital transformation initiatives. The increasing importance of artificial intelligence in national security, smart city projects, and climate change solutions will further strengthen the market. Strategic collaborations between technology giants and infrastructure providers are also shaping an ecosystem that ensures accessibility, interoperability, and innovation. As organizations strive for efficiency and agility, the demand for AI-enabled data centers, next-generation processors, and integrated software tools will continue to accelerate, positioning the AI Infrastructure Market as one of the most dynamic and high-growth segments within the global technology landscape.

Key Market Drivers

Rising Demand for High-Performance Computing (HPC) in AI Applications

The Global AI Infrastructure Market is being propelled by the surging demand for high-performance computing systems capable of managing increasingly complex artificial intelligence workloads. Artificial intelligence models, particularly deep learning algorithms, require massive computing power for training and inference tasks. Industries such as healthcare, autonomous vehicles, and financial services are investing heavily in hardware accelerators like graphics processing units, tensor processing units, and application-specific integrated circuits to improve efficiency and reduce latency. As artificial intelligence continues to integrate into business operations, demand for computing systems that can deliver real-time insights and advanced predictive analytics has intensified, pushing organizations to upgrade their AI infrastructure capabilities.

The rise of generative artificial intelligence, natural language processing, and computer vision applications has amplified the need for robust computing architectures. Governments and enterprises are increasingly adopting artificial intelligence-enabled platforms to enhance public services, defense systems, and large-scale research projects, all of which rely heavily on high-performance computing. Data centers and cloud service providers are scaling their infrastructure to deliver these capabilities on a global scale. This trend not only drives innovation but also creates a competitive landscape where advanced processors and scalable infrastructure are becoming essential for business survival in the digital era. NVIDIA reported in its 2024 annual filing that demand for its data center GPUs, driven by artificial intelligence workloads, surged by 217% year-over-year, reflecting how computing-intensive generative artificial intelligence applications are directly fueling the expansion of AI Infrastructure Market.

Key Market Challenges

High Capital Investment and Operational Costs

One of the foremost challenges restraining the Global AI Infrastructure Market is the substantial capital investment required to establish and maintain advanced artificial intelligence infrastructure. Building high-performance computing systems, next-generation semiconductor facilities, and scalable data centers demands billions of dollars in upfront costs. Hardware components such as graphics processing units, tensor processing units, and custom-designed accelerators come with high acquisition prices, while cloud services with artificial intelligence optimization also represent ongoing financial commitments. Furthermore, the cost of energy consumption associated with training large-scale artificial intelligence models is increasingly significant, as these systems require extensive power and cooling resources. This combination of hardware acquisition, facility expansion, and energy costs creates a high barrier to entry for small and medium enterprises, thereby concentrating the market among only the most financially capable players.

In addition to capital expenditure, operational costs add a persistent burden to market participants. Maintaining infrastructure for artificial intelligence requires specialized personnel with expertise in data science, machine learning engineering, and systems architecture, whose availability is both scarce and expensive. Organizations must also continuously upgrade their systems to keep pace with rapidly evolving artificial intelligence models, which often become obsolete within a short cycle. The lack of standardized frameworks across industries further amplifies operational inefficiency, as companies are compelled to customize infrastructure investments for their unique requirements. While large technology corporations and governments can absorb these costs, many enterprises struggle to justify the return on investment, thereby slowing down widespread adoption of artificial intelligence. Consequently, high capital investment and ongoing operational expenses remain a significant bottleneck for the expansion of the AI Infrastructure Market, particularly in emerging economies where financial and technical resources are limited.

Key Market Trends

Rapid Expansion of Generative Artificial Intelligence Workloads

The emergence of generative artificial intelligence is reshaping the trajectory of the Global AI Infrastructure Market. Models such as large language models, multimodal systems, and generative design applications require unparalleled computing capabilities and massive storage resources. Training these models involves billions of parameters and petabytes of data, demanding robust infrastructure supported by high-performance processors, advanced networking, and scalable cloud platforms. This exponential growth in generative artificial intelligence adoption across industries such as media, healthcare, and software development is accelerating the need for specialized infrastructure designed to support complex artificial intelligence workloads.

Generative artificial intelligence is moving beyond experimentation into commercial deployment, creating long-term infrastructure demand. Enterprises are increasingly relying on generative artificial intelligence to automate content creation, enhance customer engagement, and improve decision-making efficiency. Cloud providers and hardware manufacturers are responding by launching purpose-built platforms optimized for generative artificial intelligence training and inference. This trend underscores a fundamental shift in artificial intelligence infrastructure requirements, where performance, scalability, and reliability are becoming critical differentiators for market leaders.

Key Market Players

• Microsoft Corporation
• NVIDIA Corporation
• Google LLC
• Advanced Micro Devices, Inc.
• Samsung Electronics Co., Ltd.
• Micron Technology, Inc.
• Meta Platforms, Inc.
• IBM Corporation
• Cerebras Systems, Inc.
• Astera Labs, Inc.

Report Scope:

In this report, the Global AI Infrastructure Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

AI Infrastructure Market, By Offering:

• Compute
• Memory
• Network
• Storage
• Server Software

AI Infrastructure Market, By Deployment:

• On-Premises
• Cloud
• Hybrid

AI Infrastructure Market, By End User:

• Cloud Service Providers
• Enterprises
• Government Organizations

AI Infrastructure Market, By Region:

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa
• South America
  • Brazil
  • Colombia
  • Argentina

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global AI Infrastructure Market.

Available Customizations:

Global AI Infrastructure Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Solution Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, and Trends

4. Voice of Customer

5. Global AI Infrastructure Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Offering (Compute, Memory, Network, Storage, Server Software)
  • 5.2.2. By Deployment (On-Premises, Cloud, Hybrid)
  • 5.2.3. By End User (Cloud Service Providers, Enterprises, Government Organizations)
  • 5.2.4. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
• 5.3. By Company (2024)
• 5.4. Market Map

6. North America AI Infrastructure Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Offering
  • 6.2.2. By Deployment
  • 6.2.3. By End User
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States AI Infrastructure Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Offering
      • 6.3.1.2.2. By Deployment
      • 6.3.1.2.3. By End User
  • 6.3.2. Canada AI Infrastructure Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Offering
      • 6.3.2.2.2. By Deployment
      • 6.3.2.2.3. By End User
  • 6.3.3. Mexico AI Infrastructure Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Offering
      • 6.3.3.2.2. By Deployment
      • 6.3.3.2.3. By End User

7. Europe AI Infrastructure Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Offering
  • 7.2.2. By Deployment
  • 7.2.3. By End User
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany AI Infrastructure Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Offering
      • 7.3.1.2.2. By Deployment
      • 7.3.1.2.3. By End User
  • 7.3.2. France AI Infrastructure Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Offering
      • 7.3.2.2.2. By Deployment
      • 7.3.2.2.3. By End User
  • 7.3.3. United Kingdom AI Infrastructure Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Offering
      • 7.3.3.2.2. By Deployment
      • 7.3.3.2.3. By End User
  • 7.3.4. Italy AI Infrastructure Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Offering
      • 7.3.4.2.2. By Deployment
      • 7.3.4.2.3. By End User
  • 7.3.5. Spain AI Infrastructure Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Offering
      • 7.3.5.2.2. By Deployment
      • 7.3.5.2.3. By End User

8. Asia Pacific AI Infrastructure Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Offering
  • 8.2.2. By Deployment
  • 8.2.3. By End User
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China AI Infrastructure Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Offering
      • 8.3.1.2.2. By Deployment
      • 8.3.1.2.3. By End User
  • 8.3.2. India AI Infrastructure Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Offering
      • 8.3.2.2.2. By Deployment
      • 8.3.2.2.3. By End User
  • 8.3.3. Japan AI Infrastructure Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Offering
      • 8.3.3.2.2. By Deployment
      • 8.3.3.2.3. By End User
  • 8.3.4. South Korea AI Infrastructure Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Offering
      • 8.3.4.2.2. By Deployment
      • 8.3.4.2.3. By End User
  • 8.3.5. Australia AI Infrastructure Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Offering
      • 8.3.5.2.2. By Deployment
      • 8.3.5.2.3. By End User

9. Middle East & Africa AI Infrastructure Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Offering
  • 9.2.2. By Deployment
  • 9.2.3. By End User
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia AI Infrastructure Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Offering
      • 9.3.1.2.2. By Deployment
      • 9.3.1.2.3. By End User
  • 9.3.2. UAE AI Infrastructure Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Offering
      • 9.3.2.2.2. By Deployment
      • 9.3.2.2.3. By End User
  • 9.3.3. South Africa AI Infrastructure Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Offering
      • 9.3.3.2.2. By Deployment
      • 9.3.3.2.3. By End User

10. South America AI Infrastructure Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Offering
  • 10.2.2. By Deployment
  • 10.2.3. By End User
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil AI Infrastructure Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Offering
      • 10.3.1.2.2. By Deployment
      • 10.3.1.2.3. By End User
  • 10.3.2. Colombia AI Infrastructure Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Offering
      • 10.3.2.2.2. By Deployment
      • 10.3.2.2.3. By End User
  • 10.3.3. Argentina AI Infrastructure Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Offering
      • 10.3.3.2.2. By Deployment
      • 10.3.3.2.3. By End User

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends and Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Company Profiles

• 13.1. Microsoft Corporation
  • 13.1.1. Business Overview
  • 13.1.2. Key Revenue and Financials
  • 13.1.3. Recent Developments
  • 13.1.4. Key Personnel
  • 13.1.5. Key Product/Services Offered
• 13.2. NVIDIA Corporation
• 13.3. Google LLC
• 13.4. Advanced Micro Devices, Inc.
• 13.5. Samsung Electronics Co., Ltd.
• 13.6. Micron Technology, Inc.
• 13.7. Meta Platforms, Inc.
• 13.8. IBM Corporation
• 13.9. Cerebras Systems, Inc.
• 13.10. Astera Labs, Inc.

14. Strategic Recommendations

15. About Us & Disclaimer