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시장보고서
상품코드
1681023
세계의 AI 가속기 시장(2025-2035년)Global AI Accelerator Market 2025-2035 |
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AI 가속기 시장 규모는 2024년 236억 달러에 달했고, 2035년 3,952억 달러에 이를 것으로 예측되며, 예측 기간(2025년-2035년)의 CAGR은 29.4%를 나타낼 것으로 예상됩니다. 인공지능과 머신러닝에 대한 수요는 의료, 금융, 자동차 및 소매 업계에서 높아지고 있습니다. 대규모 데이터 세트에는 AI 가속기가 필요한데 보다 정교한 모델에는 AI의 진화와 빠른 실행을 위한 특정 하드웨어가 필요하기 때문입니다. 아마존, 마이크로소프트, 구글과 같은 주요 클라우드 서비스 제공업체는 실시간 처리 수요를 수용하기 위해 AI 가속기를 클라우드 컴퓨팅 및 에지 컴퓨팅에 통합합니다. 직접 투자 외에도 정부 이니셔티브는 AI 개발을 가속화하고 있으며 AI 가속기 수요를 뒷받침하고 있습니다. AWS, Microsoft Azure, Google Cloud 등을 포함한 여러 클라우드 서비스 제공업체는 AI 워크로드의 성능을 향상시키는 데 도움이 되는 가속 서비스를 제공합니다.
AI 가속기는 AI 워크로드를 가속화하기 위해 클라우드 컴퓨팅에 사용되어 머신러닝 모델을 신속하게 교육하고 추론할 수 있습니다. AI 가속기는 AI를 클라우드 환경에 통합할 때 딥러닝과 같은 컴퓨팅 집약적인 작업에 대한 성능과 효율성 향상을 제공합니다. 2024년 11월 IBM과 AMD는 협력하여 Gen AI 모델 및 고성능 컴퓨팅 용도을 위해 성능 및 전력 효율성을 선호하는 AMD Instinct MI300X 가속기를 IBM Cloud에서 서비스로 제공합니다. 이 협업은 IBM의 Watson AI 및 데이터 플랫폼과 Red Hat Enterprise Linux의 AI 추론 내에서 AMD Instinct MI300X 가속기를 지원했습니다.
에지 컴퓨팅 확장
세계의 AI 가속기 시장은 AI 기반 용도에 필요한 하드웨어와 처리 능력을 제공함으로써 에지 컴퓨팅의 발전에 관여하고 있습니다. GPU, TPU, FPGA와 같은 디바이스는 현장에서 효과적인 AI 처리를 촉진하고 클라우드 리소스에 대한 의존성을 줄이고 대기 시간을 단축합니다. AI 가속기 수요는 자율 시스템, IoT, 스마트 시티 개념 등의 분야에서 AI 인프라에 대규모 지출의 결과로 증가하고 있습니다. 엣지 컴퓨팅은 자율 주행 차량과 스마트 시티 등에서 실시간 데이터 분석을 가능하게 하고 데이터의 긴밀한 처리로 시장 성장을 가속합니다. 2024년 5월 Couchbase는 500명의 상위 IT 의사결정자를 대상으로 한 조사를 발표하고 기업이 AI와 엣지 컴퓨팅 등의 신기술을 활용하여 생산성 향상의 요구에 부응하려고 하기 때문에 IT 근대화에 대한 투자는 2024년 27% 증가할 것으로 추정하고 있습니다.
이 보고서는 세계의 AI 가속기 시장에 대해 조사했으며, 시장 개요와 함께 유형별, 기술 통합별, 최종 사용자별, 지역별 동향, 시장 진출기업 프로파일 등의 정보를 제공합니다.
목차
제1장 보고서 요약
제2장 시장 개요와 인사이트
제3장 시장의 결정 요인
- 시장 성장 촉진요인
- 시장의 문제점과 과제
- 시장 기회
제4장 경쟁 구도
- 경쟁 대시보드-AI 가속기 시장의 제조업체별 수익과 점유율
- AI 가속기 제품 비교 분석
- 시장의 주요 참가 기업의 랭킹 매트릭스
- 주요 기업 분석
- Advanced Micro Devices, Inc.
- IBM Corp
- Intel Corp
- NVIDIA Corp.
- 시장 진출기업에 의한 주요 성공 전략
- 합병과 인수
- 제품 발매
- 파트너십과 협업
제5장 세계의 AI 가속기 시장(100만 달러), 유형별
- 그래픽 프로세싱 유닛(GPU)
- 텐서 프로세싱 유닛(TPU)
- 특정 용도용 집적 회로(ASIC)
- 중앙처리장치(CPU)
- 필드 프로그래머블 게이트 어레이(FPGA)
제6장 세계의 AI 가속기 시장(100만 달러), 기술 통합별
- 클라우드 기반 AI 가속기
- 엣지 AI 가속기
제7장 세계의 AI 가속기 시장(100만 달러), 최종 사용자별
- IT 및 통신
- 헬스케어
- 자동차
- 금융
- 소매
- 기타(정부 및 방위)
제8장 지역 분석
- 북미
- 유럽
- 아시아태평양
- 기타 지역
제9장 기업 프로파일
- Alibaba Group
- Advanced Micro Devices, Inc.
- Amazon Web Services, Inc.
- Apple, Inc.
- Arm Ltd.
- Cerebras Systems, Inc.
- Fujitsu, Ltd.
- Google, LLC
- Graphcore(SoftBank)
- Groq, Inc.
- Huawei Technologies Co., Ltd.
- IBM Corp.
- Intel Corp.
- Lightmatter
- Marvell Technology, Inc.
- Micron Technology, Inc.
- NeuroBlade
- NVIDIA Corp.
- NXP Semiconductors NV
- Samsung Electronics Co., Ltd.
- Tenstorrent
AI Accelerator Market Size, Share & Trends Analysis Report by Type (Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), Application-Specific Integrated Circuits (ASICs), Central Processing Units (CPUs), Field-Programmable Gate Arrays (FPGAs)), and by Technology Integration (Cloud-Based AI Accelerators, and Edge AI Accelerators) and by End-User (IT & Telecom, Healthcare, Automotive, Finance, Retail, and Others) Forecast Period (2025-2035)
AI accelerator market is anticipated to reach $395.2 billion in 2035 from $23.6 billion in 2024, growing at a CAGR of 29.4% during the forecast period (2025-2035). The demand for AI and machine learning is growing in healthcare, finance, automotive, and retail industries. Large datasets necessitate AI accelerators since more sophisticated models demand AI evolution and specific hardware for quick executions. Major cloud service providers such as Amazon, Microsoft, and Google are integrating AI accelerators into cloud computing and edge computing to meet real-time processing demands. Government initiatives, in addition to direct investment, are accelerating AI development, driving the demand for AI accelerators. Several cloud service providers, including AWS, Microsoft Azure, Google Cloud, and more, are providing acceleration services for AI workloads that will help increase performance.
Market Dynamics
Integrations with AI Platforms & Cloud services
AI accelerators are used in cloud computing to expedite AI workloads, enabling faster training and inference of machine learning models. AI accelerators offer improved performance and efficiency when integrating AI into the cloud environment, for computationally intensive tasks such as deep learning. In November 2024, IBM and AMD collaborated to offer the AMD Instinct MI300X accelerators as a service on IBM Cloud, with performance and power efficiency as priorities for Gen AI models and high-performance computing applications. The collaboration supported AMD Instinct MI300X accelerators within IBM's Watson AI and data platform and Red Hat Enterprise Linux AI inferencing.
Expansion of Edge Computing
The global AI accelerator market is involved in advancing edge computing by supplying the hardware and processing power required for AI-based applications. Devices such as GPUs, TPUs, and FPGAs facilitate effective AI processing on-site, decreasing reliance on cloud resources and cutting down latency. The demand for AI accelerators is rising as a result of large expenditures in AI infrastructure in areas such as autonomous systems, IoT, and smart city initiatives. Edge computing, allows real-time data analysis in applications such as autonomous vehicles and smart cities, driving market growth owing to its closer processing of data. In May 2024, Couchbase released a survey of 500 senior IT decision makers estimating the investment in IT modernization to rise by 27% in 2024 as companies aim to leverage emerging technologies such as AI and edge computing to meet increasing productivity demands.
Market Segmentation
- Based on the type, the market is segmented into Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), Application-Specific Integrated Circuits (ASICs), Central Processing Units (CPUs), and Field-Programmable Gate Arrays (FPGAs).
- Based on technology integration, the market is segmented into cloud-based AI accelerators and edge AI accelerators.
- Based on the end user, the market is segmented into IT & telecom, healthcare, automotive, finance, retail, and others (government and defense).
IT & Telecom Segment to Hold a Considerable Market Share
AI is being utilized in the IT and telecom industries to enhance performance, efficiency, and customer service. In these sectors, AI is applied for network optimization, customer support, predictive maintenance, cybersecurity, and analytics. It aids in network management, boosts customer service, and streamline operations, while additionally offering real-time threat detection, data security, and personalized marketing strategies. The AI accelerator market, incorporating hardware and software solutions, enhances AI workload performance. Its key components include GPUs and TPUs that are vital for data processing and edge computing in telecom.
Regional Outlook
The global AI accelerator market is segmented based on geography including North America (the US, and Canada), Europe (the UK, Germany, France, Italy, Spain, Germany, France, Russia, and the Rest of Europe), Asia-Pacific (India, China, Japan, South Korea, Australia and New Zealand, ASEAN Countries, and the Rest of Asia-Pacific), and the Rest of the World (the Middle East & Africa, and Latin America).
Asia-Pacific Holds Major Market Share
Asia-Pacific holds a significant share owing to governments and organizations promoting AI adoption through funding for startups, public-private partnerships, and investment in AI education and workforce development. For instance, in September 2024, AWS selected seven Indian Gen AI startups for its Global Generative AI Accelerator program, which was the largest number from any single country in the Asia-Pacific region. The Indian companies are some of the 80 picked around the globe based on advanced AI usage and global growth intentions. AWS invested $230 million in startups to accelerate the generative AI applications. Indian AI and ML companies attracted $82 billion in 2024, while Asia-Pacific-based companies could raise $2.5 billion.
Market Players Outlook
The major companies serving the AI accelerator market include Advanced Micro Devices, Inc., IBM Corp., Intel Corp., NVIDIA Corp., Samsung Electronics Co., Ltd., and others. The market players are increasingly focusing on business expansion and product development by applying strategies such as collaborations, mergers and acquisitions to stay competitive in the market.
Recent Developments
- In December 2024, MemryX showcased its MX3 AI Accelerator at CES 2025, showcasing its industry-leading performance, efficiency, and versatility in real-world Edge AI applications. Demos include 100 Simultaneous Video Streams, Industry 4.0, Yolo-World, and GPU comparison, showcasing the MX3 Edge AI performance advantage while using less power than mainstream NVIDIA GPU.
The Report Covers:
- Market value data analysis of 2024 and forecast to 2035.
- Annualized market revenues ($ million) for each market segment.
- Country-wise analysis of major geographical regions.
- Key companies operating in the global AI accelerator market. Based on the availability of data, information related to new products, and relevant news is also available in the report.
- Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
- Analysis of market-entry and market expansion strategies.
- Competitive strategies by identifying 'who-stands-where' in the market.
Table of Contents
1. Report Summary
- Current Industry Analysis and Growth Potential Outlook
- Global AI Accelerator Market Sales Analysis - Type| Technology Integration | Application| End-User ($ Million)
- AI Accelerator Market Sales Performance of Top Countries
- 1.1. Research Methodology
- Primary Research Approach
- Secondary Research Approach
- 1.2. Market Snapshot
2. Market Overview and Insights
- 2.1. Scope of the Study
- 2.2. Analyst Insight & Current Market Trends
- 2.2.1. Key AI Accelerator Industry Trends
- 2.2.2. Market Recommendations
- 2.3. Porter's Five Forces Analysis for the AI Accelerator Market
- 2.3.1. Competitive Rivalry
- 2.3.2. Threat of New Entrants
- 2.3.3. Bargaining Power of Suppliers
- 2.3.4. Bargaining Power of Buyers
- 2.3.5. Threat of Substitutes
3. Market Determinants
- 3.1. Market Drivers
- 3.1.1. Drivers For Global AI Accelerator Market: Impact Analysis
- 3.2. Market Pain Points and Challenges
- 3.2.1. Restraints For Global AI Accelerator Market: Impact Analysis
- 3.3. Market Opportunities
4. Competitive Landscape
- 4.1. Competitive Dashboard - AI Accelerator Market Revenue and Share by Manufacturers
- AI Accelerator Product Comparison Analysis
- Top Market Player Ranking Matrix
- 4.2. Key Company Analysis
- 4.3. Advanced Micro Devices, Inc.
- 4.3.1. Overview
- 4.3.2. Product Portfolio
- 4.3.3. Financial Analysis (Subject to Data Availability)
- 4.3.4. SWOT Analysis
- 4.3.5. Business Strategy
- 4.4. IBM Corp.
- 4.4.1. Overview
- 4.4.2. Product Portfolio
- 4.4.3. Financial Analysis (Subject to Data Availability)
- 4.4.4. SWOT Analysis
- 4.4.5. Business Strategy
- 4.5. Intel Corp.
- 4.5.1. Overview
- 4.5.2. Product Portfolio
- 4.5.3. Financial Analysis (Subject to Data Availability)
- 4.5.4. SWOT Analysis
- 4.5.5. Business Strategy
- 4.6. NVIDIA Corp.
- 4.6.1. Overview
- 4.6.2. Product Portfolio
- 4.6.3. Financial Analysis (Subject to Data Availability)
- 4.6.4. SWOT Analysis
- 4.6.5. Business Strategy
- 4.7. Top Winning Strategies by Market Players
- 4.7.1. Merger and Acquisition
- 4.7.2. Product Launch
- 4.7.3. Partnership And Collaboration
- 5. Global AI Accelerator Market by Type ($ Million)
- 5.1. Graphics Processing Units (GPUs)
- 5.2. Tensor Processing Units (TPUs)
- 5.3. Application-Specific Integrated Circuits (ASICs)
- 5.4. Central Processing Units (CPUs)
- 5.5. Field-Programmable Gate Arrays (FPGAs)
- 6. Global AI Accelerator Market by Technology Integration ($ Million)
- 6.1. Cloud-Based AI Accelerators
- 6.2. Edge AI Accelerators
- 7. Global AI Accelerator Market by End-User ($ Million)
- 7.1. IT & Telecom
- 7.2. Healthcare
- 7.3. Automotive
- 7.4. Finance
- 7.5. Retail
- 7.6. Others (Government and Defense)
8. Regional Analysis
- 8.1. North American AI Accelerator Market Sales Analysis - Type| Technology Integration | End-User | Country ($ Million)
- Macroeconomic Factors for North America
- 8.1.1. United States
- 8.1.2. Canada
- 8.2. European AI Accelerator Market Sales Analysis Type| Technology Integration | End-User | Country ($ Million)
- Macroeconomic Factors for European
- 8.2.1. UK
- 8.2.2. Germany
- 8.2.3. Italy
- 8.2.4. Spain
- 8.2.5. France
- 8.2.6. Russia
- 8.2.7. Rest of Europe
- 8.3. Asia-Pacific AI Accelerator Market Sales Analysis - Type| Technology Integration | End-User | Country ($ Million)
- Macroeconomic Factors for Asia-Pacific
- 8.3.1. China
- 8.3.2. Japan
- 8.3.3. South Korea
- 8.3.4. India
- 8.3.5. Australia & New Zealand
- 8.3.6. ASEAN Countries (Thailand, Indonesia, Vietnam, Singapore, And Other)
- 8.3.7. Rest of Asia-Pacific
- 8.4. Rest of the World AI Accelerator Market Sales Analysis - Type| Technology Integration | End-User | Country ($ Million)
- Macroeconomic Factors for the Rest of the World
- 8.4.1. Latin America
- 8.4.2. Middle East and Africa
9. Company Profiles
- 9.1. Alibaba Group
- 9.1.1. Quick Facts
- 9.1.2. Company Overview
- 9.1.3. Product Portfolio
- 9.1.4. Business Strategies
- 9.2. Advanced Micro Devices, Inc.
- 9.2.1. Quick Facts
- 9.2.2. Company Overview
- 9.2.3. Product Portfolio
- 9.2.4. Business Strategies
- 9.3. Amazon Web Services, Inc.
- 9.3.1. Quick Facts
- 9.3.2. Company Overview
- 9.3.3. Product Portfolio
- 9.3.4. Business Strategies
- 9.4. Apple, Inc.
- 9.4.1. Quick Facts
- 9.4.2. Company Overview
- 9.4.3. Product Portfolio
- 9.4.4. Business Strategies
- 9.5. Arm Ltd.
- 9.5.1. Quick Facts
- 9.5.2. Company Overview
- 9.5.3. Product Portfolio
- 9.5.4. Business Strategies
- 9.6. Cerebras Systems, Inc.
- 9.6.1. Quick Facts
- 9.6.2. Company Overview
- 9.6.3. Product Portfolio
- 9.6.4. Business Strategies
- 9.7. Fujitsu, Ltd.
- 9.7.1. Quick Facts
- 9.7.2. Company Overview
- 9.7.3. Product Portfolio
- 9.7.4. Business Strategies
- 9.8. Google, LLC
- 9.8.1. Quick Facts
- 9.8.2. Company Overview
- 9.8.3. Product Portfolio
- 9.8.4. Business Strategies
- 9.9. Graphcore (SoftBank)
- 9.9.1. Quick Facts
- 9.9.2. Company Overview
- 9.9.3. Product Portfolio
- 9.9.4. Business Strategies
- 9.10. Groq, Inc.
- 9.10.1. Quick Facts
- 9.10.2. Company Overview
- 9.10.3. Product Portfolio
- 9.10.4. Business Strategies
- 9.11. Huawei Technologies Co., Ltd.
- 9.11.1. Quick Facts
- 9.11.2. Company Overview
- 9.11.3. Product Portfolio
- 9.11.4. Business Strategies
- 9.12. IBM Corp.
- 9.12.1. Quick Facts
- 9.12.2. Company Overview
- 9.12.3. Product Portfolio
- 9.12.4. Business Strategies
- 9.13. Intel Corp.
- 9.13.1. Quick Facts
- 9.13.2. Company Overview
- 9.13.3. Product Portfolio
- 9.13.4. Business Strategies
- 9.14. Lightmatter
- 9.14.1. Quick Facts
- 9.14.2. Company Overview
- 9.14.3. Product Portfolio
- 9.14.4. Business Strategies
- 9.15. Marvell Technology, Inc.
- 9.15.1. Quick Facts
- 9.15.2. Company Overview
- 9.15.3. Product Portfolio
- 9.15.4. Business Strategies
- 9.16. Micron Technology, Inc.
- 9.16.1. Quick Facts
- 9.16.2. Company Overview
- 9.16.3. Product Portfolio
- 9.16.4. Business Strategies
- 9.17. NeuroBlade
- 9.17.1. Quick Facts
- 9.17.2. Company Overview
- 9.17.3. Product Portfolio
- 9.17.4. Business Strategies
- 9.18. NVIDIA Corp.
- 9.18.1. Quick Facts
- 9.18.2. Company Overview
- 9.18.3. Product Portfolio
- 9.18.4. Business Strategies
- 9.19. NXP Semiconductors N.V.
- 9.19.1. Quick Facts
- 9.19.2. Company Overview
- 9.19.3. Product Portfolio
- 9.19.4. Business Strategies
- 9.20. Samsung Electronics Co., Ltd.
- 9.20.1. Quick Facts
- 9.20.2. Company Overview
- 9.20.3. Product Portfolio
- 9.20.4. Business Strategies
- 9.21. Tenstorrent
- 9.21.1. Quick Facts
- 9.21.2. Company Overview
- 9.21.3. Product Portfolio
- 9.21.4. Business Strategies
