AI 인프라 시장 : 세계 산업 규모, 점유율, 동향, 기회, 예측 - 제공별, 전개별, 최종사용자별, 지역별, 경쟁별(2020-2030년)
AI Infrastructure Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Offering, By Deployment, By End User, By Region, By Competition 2020-2030F
상품코드 : 1841737
리서치사 : TechSci Research
발행일 : 2025년 09월
페이지 정보 : 영문 185 Pages
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한글목차

세계의 AI 인프라 시장은 2024년에 1,325억 2,000만 달러로 평가되었으며, 2030년까지 CAGR 18.74%로 2030년에는 3,713억 7,000만 달러에 달할 것으로 예측됩니다.

세계 AI 인프라 시장은 인공지능 애플리케이션의 개발, 배포, 확장을 지원하는 하드웨어, 소프트웨어, 서비스 생태계를 의미합니다. 여기에는 그래픽 처리 장치, 중앙 연산 처리 장치, 특정 용도의 집적 회로와 같은 고급 컴퓨팅 하드웨어, 스토리지 시스템, 네트워킹 솔루션, AI에 최적화된 클라우드 플랫폼 등이 포함됩니다. 이러한 요소들이 결합되어 더 빠른 데이터 처리, 고성능 분석, 복잡한 머신러닝 및 딥러닝 모델의 효율적인 학습을 가능하게 합니다. 전 세계 산업계가 인공지능을 업무에 통합하는 가운데, 강력한 AI 인프라의 역할은 혁신, 자동화, 경쟁을 촉진하는 데 있어 기본이 되고 있습니다.

시장 개요
예측 기간 2026-2030년
시장 규모 : 2024년 1,325억 2,000만 달러
시장 규모 : 2030년 3,713억 7,000만 달러
CAGR : 2025-2030년 18.74%
급성장 부문 기업
최대 시장 북미

AI 인프라 시장의 성장은 고성능 컴퓨팅 기능에 대한 수요 급증과 데이터 생성량의 급격한 증가로 인해 가속화되고 있습니다. 헬스케어, 금융, 자동차, 소매, 제조 등 다양한 분야의 기업들은 예측 분석, 자율 시스템, 개인화된 의료, 지능형 고객 참여 등의 애플리케이션을 구현하기 위해 AI 인프라에 대한 투자를 늘리고 있습니다. 또한, 클라우드 기반 AI 인프라의 확장은 모든 규모의 기업에게 진입 장벽을 낮추고, 진화하는 워크로드에 적응할 수 있는 확장성과 비용 효율적인 솔루션을 제공하고 있습니다. 사물인터넷(Internet of Things) 기기와 5G 기술의 급속한 통합은 실시간 분석을 위해 고도의 인프라를 필요로 하는 방대한 데이터세트를 생성함으로써 수요를 촉진하고 있습니다.

AI 인프라 시장은 반도체 설계의 지속적인 발전, 엣지 AI의 인기 상승, 디지털 혁신 이니셔티브에 대한 정부 및 민간 부문의 투자로 인해 크게 성장할 것으로 예상됩니다. 국가 안보, 스마트 시티 프로젝트, 기후변화 대응에 있어 인공지능의 중요성이 높아짐에 따라 시장은 더욱 강화될 것입니다. 또한, 기술 대기업과 인프라 제공업체 간의 전략적 협업을 통해 접근성, 상호운용성, 혁신을 보장하는 생태계가 형성되고 있습니다. 기업이 효율성과 민첩성을 추구함에 따라 AI 지원 데이터센터, 차세대 프로세서, 통합 소프트웨어 도구에 대한 수요는 계속 가속화될 것이며, 시장 상황은 세계 기술 전망에서 가장 역동적이고 높은 성장세를 보이는 분야 중 하나로 자리매김할 것으로 보입니다.

시장 촉진요인

AI 애플리케이션에서 고성능 컴퓨팅(HPC)에 대한 수요 증가

주요 시장 과제

높은 설비 투자 및 운영 비용

주요 시장 동향

생성형 인공지능 워크로드의 급속한 확대

목차

제1장 솔루션 개요

제2장 조사 방법

제3장 주요 요약

제4장 고객의 소리

제5장 세계의 AI 인프라 시장 전망

제6장 북미의 AI 인프라 시장 전망

제7장 유럽의 AI 인프라 시장 전망

제8장 아시아태평양의 AI 인프라 시장 전망

제9장 중동 및 아프리카의 AI 인프라 시장 전망

제10장 남미의 AI 인프라 시장 전망

제11장 시장 역학

제12장 시장 동향과 발전

제13장 기업 개요

제14장 전략적 제안

제15장 조사 회사 소개 및 면책사항

KSM
영문 목차

영문목차

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.

Market Overview
Forecast Period2026-2030
Market Size 2024USD 132.52 Billion
Market Size 2030USD 371.37 Billion
CAGR 2025-203018.74%
Fastest Growing SegmentEnterprises
Largest MarketNorth America

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

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:

AI Infrastructure Market, By Deployment:

AI Infrastructure Market, By End User:

AI Infrastructure Market, By Region:

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

Table of Contents

1. Solution Overview

2. Research Methodology

3. Executive Summary

4. Voice of Customer

5. Global AI Infrastructure Market Outlook

6. North America AI Infrastructure Market Outlook

7. Europe AI Infrastructure Market Outlook

8. Asia Pacific AI Infrastructure Market Outlook

9. Middle East & Africa AI Infrastructure Market Outlook

10. South America AI Infrastructure Market Outlook

11. Market Dynamics

12. Market Trends and Developments

13. Company Profiles

14. Strategic Recommendations

15. About Us & Disclaimer

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