세계의 AI 인프라 시장 예측(-2030년) : 제공별, 전개 모드별, 기술별, 용도별, 최종 사용자별, 지역별 분석

According to Stratistics MRC, the Global AI Infrastructure Market is accounted for $40.2 billion in 2025 and is expected to reach $263.3 billion by 2032 growing at a CAGR of 30.8% during the forecast period. AI Infrastructure encompasses the hardware and software systems required to develop, deploy, and scale artificial intelligence applications. This includes powerful GPUs, TPUs, and high-performance computing clusters for processing large datasets, alongside cloud platforms and frameworks like TensorFlow or PyTorch for model training and deployment. It supports data storage, networking, and management tools to ensure efficient, secure, and scalable AI operations, enabling industries like agriculture, healthcare, and finance to leverage AI for innovation and decision-making.

According to Cloudscene's recent data, there are 2,701 data centers in the United States, 487 in Germany, 456 in the United Kingdom, and 443 in China, creating a robust foundation for AI infrastructure expansion.

Market Dynamics:

Driver:

Advancements in AI chips

The evolution of AI-specific chips, such as GPUs and TPUs, is significantly enhancing processing capabilities. These chips allow for faster data processing, facilitating real-time AI applications across industries. Chipmakers are increasingly innovating with energy-efficient and high-performance designs, optimizing AI workloads. Enhanced chip architectures are empowering deep learning models, enabling complex algorithm executions with minimal latency. The continuous upgrade in AI chipsets is a major enabler for the scalability of AI infrastructure.

Restraint:

Data privacy & security concerns

The handling of vast volumes of sensitive data within AI systems raises critical privacy issues. Inadequate security protocols can expose infrastructure to data breaches and misuse. Compliance with global data regulations, such as GDPR and CCPA, remains a challenge for enterprises. These concerns can limit the adoption of AI technologies, particularly in sectors like healthcare and finance. Companies must invest heavily in secure frameworks to ensure user trust and regulatory compliance.

Opportunity:

Surge in generative AI and large language models

The growing popularity of generative AI models like GPT and DALL*E is driving demand for powerful backend infrastructure. Enterprises are increasingly investing in large-scale training environments to support model development. There is a rising need for high-throughput computing to manage model inference and tuning at scale. This trend creates opportunities for vendors offering AI-optimized servers, storage, and networking components. AI infrastructure providers can tap into new verticals requiring complex content generation and automation.

Threat:

Cybersecurity vulnerabilities in distributed AI systems

Decentralized AI frameworks are more exposed to malicious attacks due to dispersed data flows and endpoints. Inadequate encryption and access control mechanisms in edge devices increase susceptibility to cyber threats. Adversarial attacks can manipulate AI models, compromising their outputs and decision-making. The growing scale of AI networks makes real-time threat monitoring increasingly complex. Persistent security loopholes can hinder trust in AI deployment and system integrity.

Covid-19 Impact:

The pandemic initially disrupted hardware supply chains, delaying AI infrastructure rollouts across sectors. However, the crisis accelerated digital transformation, spurring investments in AI-enabled operations. Remote work and virtual services led to increased demand for cloud-based AI infrastructure. COVID-19 also triggered advancements in AI applications for healthcare diagnostics and contact tracing, highlighting infrastructure needs.

The machine learning segment is expected to be the largest during the forecast period

The machine learning segment is expected to account for the largest market share during the forecast period due to its widespread applicability across industries like finance, retail, and healthcare. Increasing adoption of supervised and unsupervised learning techniques is expanding ML use cases. Cloud platforms offering ML-as-a-Service (MLaaS) are simplifying deployment for organizations. Enterprises are leveraging ML for pattern recognition, recommendation systems, and automation. The scalability and cost-effectiveness of ML models make this segment dominant.

The inference segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the inference segment is predicted to witness the highest growth rate, inference engines are becoming vital for deploying trained models in real-world scenarios with low latency. The need for fast and energy-efficient inference in edge and embedded systems is driving growth. Technological advancements in hardware accelerators are boosting the segment's capabilities. The proliferation of AI-powered applications in consumer electronics and autonomous vehicles supports this trend. The demand for optimized inference across diverse environments is expected to fuel high growth.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share due to massive investments in smart city initiatives and digital transformation. Countries like China, Japan, and South Korea are actively deploying AI technologies across public and private sectors. Government-led innovation programs and funding are boosting AI infrastructure development. The presence of major semiconductor manufacturing hubs further supports the region's growth. Additionally, rapid enterprise cloud adoption is enhancing the market landscape.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR owing to its early adoption of advanced AI technologies. The presence of major tech giants and AI research institutions is fostering innovation. High R&D investments in AI infrastructure components are accelerating market penetration. Regulatory frameworks supporting AI integration in critical industries are also contributing to growth. The increasing focus on AI-driven automation across enterprises further amplifies market expansion.

Key players in the market

Some of the key players in AI Infrastructure Market include Advanced Micro Devices, Inc, Amazon Web Services, Cadence Design Systems, Cisco, Dell, Google, Graphcore, Gyrfalcon Technology, Hewlett Packard Enterprise Development LP, IBM, Imagination Technologies, Intel, Micron Technology, Microsoft and NVIDIA.

Key Developments:

In March 2025, NVIDIA unveiled the DGX H200 AI Supercomputer, a high-performance infrastructure solution optimized for large-scale generative AI model training with enhanced energy efficiency.

In March 2025, Intel launched the Xeon 7 Series AI Accelerator, a next-generation processor with integrated AI cores for edge and data center applications, improving performance for real-time AI analytics.

In February 2025, Amazon Web Services announced the AWS Graviton4 Processor, a new AI-optimized chip designed for cost-effective, high-throughput inference workloads in cloud-based AI infrastructure.

Offerings Covered:

• Hardware
• Software
• AI Frameworks
• Middleware & Management Tools

Deployment Modes Covered:

• On-Premise
• Cloud-Based

Technologies Covered:

• Machine Learning
• Deep Learning
• Natural Language Processing (NLP)
• Computer Vision
• Reinforcement Learning

Applications Covered:

• Training
• Inference
• Data Management
• Model Deployment
• Monitoring & Orchestration
• Other Applications

End Users Covered:

• Healthcare & Life Sciences
• BFSI (Banking, Financial Services, and Insurance)
• Retail & E-commerce
• Automotive
• Telecommunications
• Government & Defense
• Other End Users

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 Technology Analysis
• 3.7 Application Analysis
• 3.8 End User Analysis
• 3.9 Emerging Markets
• 3.10 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global AI Infrastructure Market, By Offering

• 5.1 Introduction
• 5.2 Hardware
  • 5.2.1 CPUs, GPUs, ASICs, FPGAs
  • 5.2.2 Storage Systems
  • 5.2.3 Networking Components
• 5.3 Software
• 5.4 AI Frameworks
• 5.5 Middleware & Management Tools

6 Global AI Infrastructure Market, By Deployment Mode

• 6.1 Introduction
• 6.2 On-Premise
• 6.3 Cloud-Based

7 Global AI Infrastructure Market, By Technology

• 7.1 Introduction
• 7.2 Machine Learning
• 7.3 Deep Learning
• 7.4 Natural Language Processing (NLP)
• 7.5 Computer Vision
• 7.6 Reinforcement Learning

8 Global AI Infrastructure Market, By Application

• 8.1 Introduction
• 8.2 Training
• 8.3 Inference
• 8.4 Data Management
• 8.5 Model Deployment
• 8.6 Monitoring & Orchestration
• 8.7 Other Applications

9 Global AI Infrastructure Market, By End User

• 9.1 Introduction
• 9.2 Healthcare & Life Sciences
• 9.3 BFSI (Banking, Financial Services, and Insurance)
• 9.4 Retail & E-commerce
• 9.5 Automotive
• 9.6 Telecommunications
• 9.7 Government & Defense
• 9.8 Other End Users

10 Global AI Infrastructure Market, By Geography

• 10.1 Introduction
• 10.2 North America
  • 10.2.1 US
  • 10.2.2 Canada
  • 10.2.3 Mexico
• 10.3 Europe
  • 10.3.1 Germany
  • 10.3.2 UK
  • 10.3.3 Italy
  • 10.3.4 France
  • 10.3.5 Spain
  • 10.3.6 Rest of Europe
• 10.4 Asia Pacific
  • 10.4.1 Japan
  • 10.4.2 China
  • 10.4.3 India
  • 10.4.4 Australia
  • 10.4.5 New Zealand
  • 10.4.6 South Korea
  • 10.4.7 Rest of Asia Pacific
• 10.5 South America
  • 10.5.1 Argentina
  • 10.5.2 Brazil
  • 10.5.3 Chile
  • 10.5.4 Rest of South America
• 10.6 Middle East & Africa
  • 10.6.1 Saudi Arabia
  • 10.6.2 UAE
  • 10.6.3 Qatar
  • 10.6.4 South Africa
  • 10.6.5 Rest of Middle East & Africa

11 Key Developments

• 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 11.2 Acquisitions & Mergers
• 11.3 New Product Launch
• 11.4 Expansions
• 11.5 Other Key Strategies

12 Company Profiling

• 12.1 Advanced Micro Devices, Inc
• 12.2 Amazon Web Service
• 12.3 Cadence Design Systems
• 12.4 Cisco
• 12.5 Dell
• 12.6 Google
• 12.7 Graphcore
• 12.8 Gyrfalcon Technology
• 12.9 Hewlett Packard Enterprise Development LP
• 12.10 IBM
• 12.11 Imagination Technologies
• 12.12 INTEL
• 12.13 Micron Technology
• 12.14 Microsoft
• 12.15 NVIDIA