세계의 AI 인프라 시장 : 제공 제품, 전개, 최종 사용자별 예측(2025-2030년)

The AI Infrastructure Market was valued at USD 36.52 billion in 2023, expected to reach USD 45.11 billion in 2024, and is projected to grow at a CAGR of 24.08%, to USD 165.40 billion by 2030.

AI infrastructure encompasses the comprehensive setup of hardware and software systems, networks, data storage, and computing resources that underpin artificial intelligence applications. The necessity for AI infrastructure arises from the growing implementation of AI across different sectors, demanding high-performance computing capabilities to process large volumes of data effectively. Its applications span various industries, including healthcare, automotive, finance, and manufacturing, where AI drives innovation in product development, enhances operational efficiencies, and improves customer experiences. The end-use scope extends to enterprises looking to leverage AI for insightful data analysis, real-time decision-making, and automation of routine tasks, thereby accelerating digital transformation journeys.

Market growth is influenced by technological advancements in AI hardware, integration of AI with cloud computing, and the increasing adoption of AI by small and medium enterprises. Additionally, government initiatives supporting AI research and development further propel this growth. Emerging opportunities exist in developing energy-efficient and scalable AI infrastructure solutions, which address sustainability and decarbonization needs, presenting significant investment potential. To capitalize on these opportunities, companies should focus on enhancing AI capabilities through partnerships, acquisitions, and continuous innovation in AI chipsets, edge computing, and quantum computing technologies.

However, the AI infrastructure market faces limitations like high initial capital investment, complexity in implementing AI systems, and skill shortages in managing AI technologies. These challenges necessitate robust strategies for talent acquisition and training programs to harness AI's full potential. Innovating in cybersecurity to protect sensitive AI-driven data and addressing ethical concerns surrounding AI use will also be crucial for sustained growth. Research areas such as autonomous systems, neuro-symbolic AI, and AI explainability can unlock further business growth by providing insights into how AI can be more accessible and understandable for broader applications. The nature of the AI infrastructure market is dynamic and competitive, with rapid technological advancements paving the way for new market entrants and opportunities, emphasizing the importance of agility and foresight in business strategies.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving AI Infrastructure Market

The AI Infrastructure Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

• Market Drivers
  • Need for high-performance computing platforms to process large datasets
  • Government initiatives promoting smart manufacturing and industry 4.0 facilities
  • Rise of edge-to-cloud AI infrastructure worldwide
• Market Restraints
  • Complexity of designing, deploying, and maintaining AI infrastructure
• Market Opportunities
  • New technological integration and advancements in AI infrastructure
  • Emerging 5G network deployment in AI infrastructure
• Market Challenges
  • Vulnerability to cyberattacks and data breaches

Porter's Five Forces: A Strategic Tool for Navigating the AI Infrastructure Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the AI Infrastructure Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the AI Infrastructure Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the AI Infrastructure Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the AI Infrastructure Market

A detailed market share analysis in the AI Infrastructure Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the AI Infrastructure Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the AI Infrastructure Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Key Company Profiles

The report delves into recent significant developments in the AI Infrastructure Market, highlighting leading vendors and their innovative profiles. These include Samsung Electronics Co., Ltd., Cerebras Systems, SambaNova Systems, Inc, Accenture PLC, Nutanix, Inc., Hailo Technologies Ltd., Graphcore Limited, NVIDIA Corporation, Google LLC by Alphabet Inc., DataRobot, Inc., Microsoft Corporation, Toshiba Corporation, Amazon Web Services, Inc., Fortinet, Inc., Siemens AG, Intel Corporation, Lenovo Group Limited, International Business Machines Corporation, Oracle Corporation, Meta Platforms, Inc., SAP SE, Micron Technology Inc., G-Core Labs S.A., OpenAI OpCo, LLC, Cisco Systems, Inc., Sony Group Corporation, Groq, Inc., SenseTime Group Inc., Synopsys Inc., Hewlett Packard Enterprise Development LP, Mythic, Inc., Appinventiv Technology Pvt. Ltd., NEC Corporation, Salesforce, Inc., Advanced Micro Devices Inc., Huawei Technologies Co., Ltd., Pure Storage, Inc., and Lightmatter, Inc..

Market Segmentation & Coverage

This research report categorizes the AI Infrastructure Market to forecast the revenues and analyze trends in each of the following sub-markets:

• Based on Offering, market is studied across Hardware, Services, and Software. The Hardware is further studied across CPU & GPU, Memory & Storage, and Networking Equipment. The Services is further studied across Data Ingestion & Integration, Data Preprocessing & Feature Engineering, Data Storage & Management, Machine Learning Frameworks & Libraries, Model Deployment & Serving, Model Training & Validation, Monitoring & Maintenance, and Security & Compliance.
• Based on Deployment, market is studied across On-Cloud and On-Premise.
• Based on End-Users, market is studied across Cloud Service Providers, Enterprises, and Government.
• Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Market Dynamics
  • 5.1.1. Drivers
    • 5.1.1.1. Need for high-performance computing platforms to process large datasets
    • 5.1.1.2. Government initiatives promoting smart manufacturing and industry 4.0 facilities
    • 5.1.1.3. Rise of edge-to-cloud AI infrastructure worldwide
  • 5.1.2. Restraints
    • 5.1.2.1. Complexity of designing, deploying, and maintaining AI infrastructure
  • 5.1.3. Opportunities
    • 5.1.3.1. New technological integration and advancements in AI infrastructure
    • 5.1.3.2. Emerging 5G network deployment in AI infrastructure
  • 5.1.4. Challenges
    • 5.1.4.1. Vulnerability to cyberattacks and data breaches
• 5.2. Market Segmentation Analysis
  • 5.2.1. Offering: Innovative solution and services catering to specific needs of the AI ecosystem
  • 5.2.2. Deployment: Increasing utilization of the cloud-based AI infrastructure focusing on the agility and swift deployment of AI-powered services
  • 5.2.3. End-Users: Rising deployment of the AI infrastructure into the enterprises and Government entities
• 5.3. Porter's Five Forces Analysis
  • 5.3.1. Threat of New Entrants
  • 5.3.2. Threat of Substitutes
  • 5.3.3. Bargaining Power of Customers
  • 5.3.4. Bargaining Power of Suppliers
  • 5.3.5. Industry Rivalry
• 5.4. PESTLE Analysis
  • 5.4.1. Political
  • 5.4.2. Economic
  • 5.4.3. Social
  • 5.4.4. Technological
  • 5.4.5. Legal
  • 5.4.6. Environmental

6. AI Infrastructure Market, by Offering

• 6.1. Introduction
• 6.2. Hardware
  • 6.2.1. CPU & GPU
  • 6.2.2. Memory & Storage
  • 6.2.3. Networking Equipment
• 6.3. Services
  • 6.3.1. Data Ingestion & Integration
  • 6.3.2. Data Preprocessing & Feature Engineering
  • 6.3.3. Data Storage & Management
  • 6.3.4. Machine Learning Frameworks & Libraries
  • 6.3.5. Model Deployment & Serving
  • 6.3.6. Model Training & Validation
  • 6.3.7. Monitoring & Maintenance
  • 6.3.8. Security & Compliance
• 6.4. Software

7. AI Infrastructure Market, by Deployment

• 7.1. Introduction
• 7.2. On-Cloud
• 7.3. On-Premise

8. AI Infrastructure Market, by End-Users

• 8.1. Introduction
• 8.2. Cloud Service Providers
• 8.3. Enterprises
• 8.4. Government

9. Americas AI Infrastructure Market

• 9.1. Introduction
• 9.2. Argentina
• 9.3. Brazil
• 9.4. Canada
• 9.5. Mexico
• 9.6. United States

10. Asia-Pacific AI Infrastructure Market

• 10.1. Introduction
• 10.2. Australia
• 10.3. China
• 10.4. India
• 10.5. Indonesia
• 10.6. Japan
• 10.7. Malaysia
• 10.8. Philippines
• 10.9. Singapore
• 10.10. South Korea
• 10.11. Taiwan
• 10.12. Thailand
• 10.13. Vietnam

11. Europe, Middle East & Africa AI Infrastructure Market

• 11.1. Introduction
• 11.2. Denmark
• 11.3. Egypt
• 11.4. Finland
• 11.5. France
• 11.6. Germany
• 11.7. Israel
• 11.8. Italy
• 11.9. Netherlands
• 11.10. Nigeria
• 11.11. Norway
• 11.12. Poland
• 11.13. Qatar
• 11.14. Russia
• 11.15. Saudi Arabia
• 11.16. South Africa
• 11.17. Spain
• 11.18. Sweden
• 11.19. Switzerland
• 11.20. Turkey
• 11.21. United Arab Emirates
• 11.22. United Kingdom

12. Competitive Landscape

• 12.1. Market Share Analysis, 2023
• 12.2. FPNV Positioning Matrix, 2023
• 12.3. Competitive Scenario Analysis
  • 12.3.1. Saudi Arabia Partners with China to Create Arabic-based AI System
  • 12.3.2. AMD to Acquire Open-Source AI Software Expert Nod.ai
  • 12.3.3. SambaNova Unveils the SN40L, Powering its Full Stack AI Platform
  • 12.3.4. EY Announces Launch of Artificial Intelligence Platform EY.ai Following USD 1.4 Billion Investment
  • 12.3.5. Partnership to Launch UAE as the World's First AI Nation
  • 12.3.6. Jio Platforms Ties up with NVIDIA to Build Cloud-based AI Infrastructure
  • 12.3.7. Tata Partners With NVIDIA to Build Large-Scale AI Infrastructure
  • 12.3.8. Microsoft Expands UAE's G42 Partnership to Include Cloud, AI Tools
  • 12.3.9. Google Cloud and NVIDIA Expand Partnership to Advance AI Computing, Software and Services
  • 12.3.10. Contextual AI and Google Cloud Partner to Bring Generative AI to the Enterprise
  • 12.3.11. Nutanix Simplifies Adoption of Generative AI with New Nutanix GPT-in-a-Box Solution
  • 12.3.12. VAST Data Launches Unified Data Platform for the Age of AI
  • 12.3.13. AMD Announces Plan to Invest USD 135 Million to Expand Adaptive Computing Research, Development and Engineering Operations in Ireland
  • 12.3.14. Lenovo to Invest USD 1 Billion over 3 Years on Expansion and Optimisation of AI Infrastructure
  • 12.3.15. Hewlett Packard Enterprise acquires Pachyderm to expand AI-at-scale capabilities with reproducible AI

Companies Mentioned

• 1. Samsung Electronics Co., Ltd.
• 2. Cerebras Systems
• 3. SambaNova Systems, Inc
• 4. Accenture PLC
• 5. Nutanix, Inc.
• 6. Hailo Technologies Ltd.
• 7. Graphcore Limited
• 8. NVIDIA Corporation
• 9. Google LLC by Alphabet Inc.
• 10. DataRobot, Inc.
• 11. Microsoft Corporation
• 12. Toshiba Corporation
• 13. Amazon Web Services, Inc.
• 14. Fortinet, Inc.
• 15. Siemens AG
• 16. Intel Corporation
• 17. Lenovo Group Limited
• 18. International Business Machines Corporation
• 19. Oracle Corporation
• 20. Meta Platforms, Inc.
• 21. SAP SE
• 22. Micron Technology Inc.
• 23. G-Core Labs S.A.
• 24. OpenAI OpCo, LLC
• 25. Cisco Systems, Inc.
• 26. Sony Group Corporation
• 27. Groq, Inc.
• 28. SenseTime Group Inc.
• 29. Synopsys Inc.
• 30. Hewlett Packard Enterprise Development LP
• 31. Mythic, Inc.
• 32. Appinventiv Technology Pvt. Ltd.
• 33. NEC Corporation
• 34. Salesforce, Inc.
• 35. Advanced Micro Devices Inc.
• 36. Huawei Technologies Co., Ltd.
• 37. Pure Storage, Inc.
• 38. Lightmatter, Inc.