人工智慧基礎設施市場－全球產業規模、佔有率、趨勢、機會和預測，按產品、部署、最終用戶、地區和競爭細分，2020-2030F

2024 年全球人工智慧基礎設施市場價值為 1,325.2 億美元，預計到 2030 年將達到 3,713.7 億美元，複合年成長率為 18.74%。全球人工智慧基礎設施市場是指支援人工智慧應用開發、部署和擴展的硬體、軟體和服務生態系統。這包括先進的運算硬體，如圖形處理單元、中央處理器和專用積體電路，以及儲存系統、網路解決方案和針對人工智慧最佳化的雲端平台。這些元素共同實現了更快的資料處理、高效能分析以及複雜機器學習和深度學習模型的高效訓練。隨著全球各地的產業將人工智慧融入其營運，強大的人工智慧基礎設施已成為推動創新、自動化和競爭力的基礎。

高效能運算能力需求的激增以及資料產生的指數級成長，加速了人工智慧基礎設施市場的成長。醫療保健、金融、汽車、零售和製造等領域的企業正在增加對人工智慧基礎設施的投資，以支援預測分析、自主系統、個人化醫療和智慧客戶互動等應用。此外，基於雲端的人工智慧基礎設施的擴展正在降低各種規模企業的進入門檻，提供可擴展且經濟高效的解決方案，以適應不斷變化的工作負載。物聯網設備和 5G 技術的快速整合也刺激了需求，因為它們創建了大量資料集，需要先進的基礎設施進行即時分析。

由於半導體設計的持續進步、邊緣人工智慧的日益普及以及政府和私營部門對數位轉型計畫的投入，人工智慧基礎設施市場將大幅成長。人工智慧在國家安全、智慧城市計畫和氣候變遷解決方案中日益重要的地位將進一步增強市場發展。科技巨頭與基礎設施供應商之間的策略合作也正在塑造一個確保可訪問性、互通性和創新性的生態系統。隨著企業追求效率和敏捷性，對支援人工智慧的資料中心、下一代處理器和整合軟體工具的需求將持續成長，這使得人工智慧基礎設施市場成為全球技術領域最具活力和高成長的領域之一。

關鍵市場促進因素

人工智慧應用對高效能運算 (HPC) 的需求不斷成長

主要市場挑戰

高昂的資本投資和營運成本

主要市場趨勢

產生人工智慧工作負載的快速擴展

目錄

第 1 章：解決方案概述

• 市場定義
• 市場範圍
  • 覆蓋市場
  • 考慮學習的年限
  • 主要市場區隔

第2章：研究方法

第3章：執行摘要

第4章：顧客之聲

第5章：全球人工智慧基礎設施市場展望

• 市場規模和預測
  • 按價值
• 市場佔有率和預測
  • 按產品（計算、記憶體、網路、儲存、伺服器軟體）
  • 按部署（本地端、雲端、混合式）
  • 按最終用戶（雲端服務提供者、企業、政府組織）
  • 按地區（北美、歐洲、南美、中東和非洲、亞太地區）
• 按公司分類（2024 年）
• 市場地圖

第6章：北美人工智慧基礎設施市場展望

• 市場規模和預測
• 市場佔有率和預測
• 北美：國家分析
  • 美國
  • 加拿大
  • 墨西哥

第7章：歐洲人工智慧基礎設施市場展望

• 市場規模和預測
• 市場佔有率和預測
• 歐洲：國家分析
  • 德國
  • 法國
  • 英國
  • 義大利
  • 西班牙

第8章：亞太地區人工智慧基礎設施市場展望

• 市場規模和預測
• 市場佔有率和預測
• 亞太地區：國家分析
  • 中國
  • 印度
  • 日本
  • 韓國
  • 澳洲

第9章：中東和非洲人工智慧基礎設施市場展望

• 市場規模和預測
• 市場佔有率和預測
• 中東和非洲：國家分析
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國
  • 南非

第10章：南美洲人工智慧基礎設施市場展望

• 市場規模和預測
• 市場佔有率和預測
• 南美洲：國家分析
  • 巴西
  • 哥倫比亞
  • 阿根廷

第 11 章：市場動態

• 驅動程式
• 挑戰

第 12 章：市場趨勢與發展

• 合併與收購（如有）
• 產品發布（如有）
• 最新動態

第13章：公司簡介

• 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：策略建議

第15章調查會社について,免責事項

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