세계의 AI 서버 시장 : 프로세서 유형별, 기능별, 냉각 기술별, 폼 팩터별, 전개별, 용도별, 최종 사용자별, 지역별 - 예측(-2030년)
AI Server Market by Processor Type (GPU, FPGA, ASIC), Function (Training, Inference), Form Factor (Rack-Mounted Server, Blade Server, Tower Server), Cooling Technology (Air Cooling, Liquid Cooling, Hybrid Cooling) - Global Forecast to 2030
상품코드:1618944
리서치사:MarketsandMarkets
발행일:2024년 12월
페이지 정보:영문 316 Pages
라이선스 & 가격 (부가세 별도)
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한글목차
AI 서버 시장 규모는 2024년 1,428억 8,000만 달러 규모에 이른 것으로 평가되었고, 2024년부터 2030년까지 34.3%의 연평균 복합 성장률(CAGR)로 확대될 전망이며, 2030년에는 8,378억 3,000만 달러에 달할 것으로 예상됩니다.
기업과 업계가 데이터 분석, 자동화, 의사결정을 위해 AI 기술에 대한 의존도를 높이고 있기 때문에 머신러닝(ML) 및 심층 학습 알고리즘의 채용이 증가하고 있는 것이 AI 서버 시장의 주요 추진 요인이 되고 있습니다. 클라우드 기반 AI 솔루션의 채용이 증가하고 있는 것도 AI 서버 시장의 또 다른 촉진요인이며, 보다 많은 업계가 클라우드 플랫폼의 확장성, 유연성, 비용 효율성을 활용하여 AI 기술을 도입하고 있습니다. 클라우드 기반 AI 서비스를 이용하면 기업은 고가의 온프레미스 인프라에 투자할 필요가 없어 모든 규모의 기업이 AI에 접근할 수 있게 됩니다. AWS, Microsoft Azure, Google Cloud 등의 클라우드 AI 플랫폼을 통해 기업은 사내에 전용 하드웨어를 마련하지 않고도 고급 AI 모델을 도입할 수 있기 때문에 대규모 AI 계산에 대응할 수 있는 클라우드 기반 AI 서버에 대한 수요가 높아지고 있습니다.
조사 범위
조사 대상년도
2020-2030년
기준년
2023년
예측 기간
2024-2030년
검토 단위
금액(10억 달러)
부문별
프로세서 유형별, 기능별, 냉각 기술별, 폼 팩터별, 전개별, 용도별, 최종 사용자별, 지역별
대상 지역
북미, 유럽, 아시아태평양 및 기타 지역
AI 서버 시장에서는 액체 냉각이 최대 점유율을 차지하고 있습니다. HPC나 AI 워크로드를 위한 냉각 수요가 급속히 높아지고 있어 액냉 기술을 채용함으로써 서버 냉각 상황을 재구축하고 있습니다. 공랭은 강력한 GPU나 CPU에서 발생하는 고열 부하에 대응할 수 없지만 액랭, 특히 칩 직하 액랭은 우수한 열 관리를 제공합니다. 액랭은 에너지 효율을 유지하면서 더 높은 계산 밀도를 관리하는 데 가장 중요한 솔루션입니다. AI의 채용이 계속 확대되는 가운데, 액랭은, 공급망 전체에 있어서의 새로운 전개 전략과 혁신에 의해, 데이터 센터에에서 표준이 될 것으로 기대되고 있습니다. 서버의 주문자상표제품제조업자(ODM)는 이 진화하는 에코시스템의 리더로서의 지위를 확립하기 위해 액랭에 대한 투자를 늘리고 있으며, 지금은 액랭의 리스크마저 받아들이고 있습니다. Chilldyne, Inc.(미국)는 2024년 7월에 액냉 스타터 키트를 발매해, 데이터 센터가 액냉으로 신속하게 이행할 수 있도록 했습니다. 이러한 냉각 기술은 최첨단 AI 시스템의 안정적이고 지속 가능한 냉각을 보장하며, 공랭에서 보다 효율적인 액랭 솔루션으로의 이행 동향을 지원합니다.
AI 서버 시장에서는 랙 마운트형 AI 서버가 급성장하는 자세입니다. 인공지능 용도는 대량의 데이터 처리와 실시간 의사결정 등 복잡성과 데이터 강도가 점점 높아지고 있습니다. 그래서 바로 대량의 데이터를 효율적인 프로세스로 처리하기 위해 필요한 성능을 제공하는 랙 마운트 서버가 사용됩니다. 게다가 냉각 기술과 에너지 효율의 급속한 향상으로, 고성능의 AI 워크로드에도 랙 마운트형 서버를 용이하게 도입할 수 있게 되어 있습니다. 또한 랙 마운트형 서버는 합리화된 케이블 배선과 관리 툴을 통해 유지보수 및 업그레이드 절차를 간소화하고 운영 오버헤드를 줄입니다. AI 주도의 솔루션에 대한 요구가 헬스케어와 금융에서 제조업과 소매업에 이르기까지 폭넓은 업계를 석권하는 가운데 랙마운트형 AI 서버는 특히 데이터센터의 적응성, 성능, 공간 효율적인 이용으로 상승세를 타고 있는 것 같습니다.
이 보고서는 세계의 AI 서버 시장을 조사했으며, 프로세서 유형별, 기능별, 냉각 기술별, 폼 팩터별, 배포별, 용도별, 최종 사용자별, 지역별 동향 및 시장 진출기업 프로파일 등을 정리했습니다.
목차
제1장 서론
제2장 조사 방법
제3장 주요 요약
제4장 중요 인사이트
제5장 시장 개요
서문
시장 역학
고객사업에 영향을 주는 동향 및 혼란
가격 분석
밸류체인 분석
생태계 분석
투자 및 자금조달 시나리오
기술 분석
서버 비용 구조 및 부품표(BOM)
AI 서버의 현재 보급률과 성장 예측
클라우드 서비스 제공업체별 데이터센터의 향후 전개
클라우드 서비스 제공업체의 설비 투자
프로세서 벤치마크
특허 분석
무역 분석
주된 회의 및 이벤트(2024-2025년)
사례 연구 분석
규제 상황
Porter's Five Forces 분석
주요 이해관계자 및 구매 기준
제6장 AI 서버 시장 : 프로세서 유형별
서문
GPU 기반 서버
FPGA 기반 서버
ASIC 기반 서버
제7장 AI 서버 시장 : 기능별
서문
트레이닝
추론
제8장 AI 서버 시장 : 냉각 기술별
서문
공냉
액체 냉각
하이브리드 냉각
제9장 AI 서버 시장 : 폼 팩터별
서문
랙마운트형 서버
블레이드 서버
타워 서버
제10장 AI 서버 시장 : 전개별
서문
온프레미스
클라우드
제11장 AI 서버 시장 : 용도별
서문
생성형 AI
머신러닝
자연언어처리
컴퓨터 비전
제12장 AI 서버 시장 : 최종 사용자별
서문
클라우드 서비스 제공업체
기업
정부기관
제13장 AI 서버 시장 : 지역별
서문
북미
북미의 거시경제 전망
미국
캐나다
멕시코
유럽
유럽의 거시 경제 전망
영국
독일
프랑스
이탈리아
스페인
기타
아시아태평양
아시아태평양의 거시 경제 전망
중국
일본
한국
인도
기타
기타 지역
기타 지역의 거시 경제 전망
중동
아프리카
남미
제14장 경쟁 구도
개요
주요 참가 기업의 전략 및 강점(2020-2024년)
수익 분석
시장 점유율 분석(2023년)
기업가치평가 및 재무지표
브랜드 및 제품 비교
기업평가 매트릭스 : 주요 진입기업(2023년)
기업평가 매트릭스 : 스타트업 및 중소기업(2023년)
경쟁 시나리오 및 동향
제15장 기업 프로파일
주요 진출기업
DELL INC.
HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
LENOVO
HUAWEI TECHNOLOGIES CO., LTD.
IBM
H3C TECHNOLOGIES CO., LTD.
CISCO SYSTEMS, INC.
SUPER MICRO COMPUTER, INC.
FUJITSU
INSPUR CO., LTD.
기타 기업
NVIDIA CORPORATION
ADLINK TECHNOLOGY INC.
ADVANCED MICRO DEVICES, INC.
QUANTA COMPUTERS
WISTRON CORPORATION
GIGABIT TECHNOLOGIES PVT LTD.
ASUSTEK COMPUTER INC.
AIVRES
AIME
WIWYNN CORPORATION
MITAC COMPUTING TECHNOLOGY CORPORATION
NEC CORPORATION INDIA PRIVATE LIMITED
XENON SYSTEMS PTY LTD.
GRAPHCORE
2CRSI GROUP
제16장 부록
AJY
영문 목차
영문목차
The AI server market is expected to be worth USD 142.88 billion in 2024 and is estimated to reach USD 837.83 billion by 2030, growing at a CAGR of 34.3% between 2024 and 2030. The increasing adoption of machine learning (ML) and deep learning algorithms is a key driver for the AI server market, as businesses and industries rely more heavily on AI technologies for data analysis, automation, and decision-making. The rising adoption of cloud-based AI solutions is a another driver for the AI server market, as more industries leverage the scalability, flexibility, and cost-efficiency of cloud platforms to implement AI technologies. With cloud-based AI services, organizations no longer need to invest in expensive on-premise infrastructure, making AI accessible to businesses of all sizes. Cloud AI platforms like AWS, Microsoft Azure, and Google Cloud, enable businesses to deploy sophisticated AI models without the need for specialized in-house hardware, driving demand for cloud-based AI servers that can handle large-scale AI computations.
Scope of the Report
Years Considered for the Study
2020-2030
Base Year
2023
Forecast Period
2024-2030
Units Considered
Value (USD Billion)
Segments
By Processor Type; Function; Cooling Technology, Form Factor, Deployment, Application, End User, and Region
Regions covered
North America, Europe, APAC, RoW
"Liquid cooling segment to hold the largest share in 2030."
Liquid cooling holds largest market share in the AI server market. The rapidly increasing demand of cooling for HPC and AI workloads are reshaping the server cooling landscape by adopting liquid cooling technology. Air cooling can't cope up with high heat loads generated by powerful GPUs and CPUs, while liquid cooling, especially direct-to-chip liquid cooling, provides superior thermal management. Liquid cooling is the most important solution in managing higher compute densities while maintaining energy efficiency. As AI adoption continues to grow, liquid cooling is expected to become standard in data centers with new deployment strategies and innovations in the whole supply chain. Servers Original Design Manufacturers (ODMs) are increasingly investing in liquid cooling where they now even accept the leakage risk, as they position themselves as leaders in this evolving ecosystem. Chilldyne, Inc. (US) launched their Liquid Cooling Starter Kit in July 2024 to enable data centers to transition rapidly to liquid cooling-supporting the shift toward next-generation AI and HPC workloads. These cooling technologies ensured stable and sustainable cooling for the cutting-edge AI systems, therefore supporting the trend to shift from air-cooling towards much more efficient liquid cooling solutions.
"Rack mounted servers by form factor is projected to grow at a high CAGR of AI server market during the forecasted timeline"
Rack-mounted AI servers are poised to grow rapidly in the AI server market. Applications for artificial intelligence have increasingly high complexity and data intensity, including handling large quantities of data and real-time decision-making. That is precisely where rackmounted servers are used to provide the required performance to handle the massive volumes of data in an efficient process. In addition, rapid advancements in cooling technologies and energy efficiency enable easy deployment of rack-mounted servers for even high-performance AI workloads. Rack mounted servers also simplify maintenance/upgrades procedure with stream-lined cabling and management tools, which reduce operation overheads. As the rising need for AI-driven solutions sweeps through industries in such a broad scale, from healthcare and finance to manufacturing and retail, rack mounted AI servers seem to be on an upward growth trend that is especially fueled by the adaptability, performance, and space-efficient utilization of data centers.
"Cloud segment is expected to have the highest share during the forecast period."
Cloud-based deployment dominates the AI server market through flexibility, cost efficiency, access to advanced capabilities of AI, and is critical for businesses adopting AI at scale. Companies can scale their AI operations very quickly without highly investing in physical servers via a cloud infrastructure. For example, AWS provides Elastic Compute Cloud (EC2) instances that are specifically optimized for machine learning that allow businesses to ramp up and down based on the demand. Microsoft Azure contains AI tools such as Azure Machine Learning and Cognitive Services that have been widely designed to support complex model training and deployment with minimum time. CSPs also provide pre-built models and tools that reduce the development time for businesses and reduce technical barriers in various enterprises. In retail, for example, there is demand forecasting and personalized marketing. Healthcare organizations use cloud AI services for predictive analytics and diagnostics. These advantages make cloud-based AI deployments highly attractive and enable companies from all industries to utilize powerful, scalable, and flexible AI resources, making it the largest market share in the AI server market.
"North America is expected to hold high CAGR in during the forecast period."
North America will occupy high CAGR during the forecast period due to the presence of various AI server manufacturers, such NVIDIA Corporation (US), Dell Inc. (US), Hewlett Packard Enterprise Development LP (US), IBM (US), and Cisco Systems, Inc. (US), which contributes to the market's growth in this region. These firms are researching and developing AI servers and solutions, leading the region into the innovation front in technology. The growing trend of cloud computing has radically increased the economic impact of data center investments made by leading service providers such as Amazon Web Services, Inc. (AWS) (US), Meta (US), Google (US), and Microsoft (US). The competition for data center projects has increased in North America. The growth of emerging startups in the region further contribute to the developments in AI servers in the region. With a focus on harnessing the potential of artificial intelligence to drive economic growth, improve customer experiences, and address complex challenges, North America continues to be a hub for artificial intelligence innovation and entrepreneurship.
Extensive primary interviews were conducted with key industry experts in the AI server market space to determine and verify the market size for various segments and subsegments gathered through secondary research. The break-up of primary participants for the report has been shown below: The study contains insights from various industry experts, from component suppliers to Tier 1 companies and OEMs. The break-up of the primaries is as follows:
By Company Type: Tier 1 - 50%, Tier 2 - 20%, and Tier 3 - 30%
By Designation: C-level Executives - 20%, Directors - 30%, and Others - 50%
By Region: North America - 40%, Europe - 20%, Asia Pacific - 30%, and RoW - 10%
The report profiles key players in the AI server market with their respective market ranking analysis. Prominent players profiled in this report are Dell Inc. (US), Hewlett Packard Enterprise Development LP (US), Lenovo (Hong Kong), Huawei Technologies Co., Ltd. (China), IBM (US), H3C Technologies Co., Ltd. (China), Cisco Systems, Inc. (US), Super Micro Computer, Inc. (US), Fujitsu (Japan), INSPUR Co., Ltd. (China) among others.
Apart from this, ADLINK Technology Inc. (Taiwan), Advanced Micro Devices, Inc. (US), Quanta Computer lnc. (Taiwan), WISTRON CORPORATION (Taiwan), GIGABIT Technologies Pvt. Ltd. (Taiwan), ASUSTeK Computer Inc. (Taiwan), Aivres (US), AIME (Germany), Wiwynn Corporation (Taiwan), MiTAC Computing Technology Corporation (Taiwan), NEC Corporation India Private Limited (India), XENON Systems Pty Ltd (Australia), Graphcore (UK), and 2CRSi Group (France) are among a few emerging companies in the AI server market.
Research Coverage: This research report categorizes the AI server market based on processor type, function, cooling technology, form factor, deployment, application, end user, and region. The report describes the major drivers, restraints, challenges, and opportunities pertaining to the AI server market and forecasts the same till 2030. Apart from these, the report also consists of leadership mapping and analysis of all the companies included in the AI server ecosystem.
Key Benefits of Buying the Report The report will help the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall AI server market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
Analysis of key drivers (Increase in data traffic and need for high computing power; Increasing adoption of machine learning and deep learning algorithms, and Rising adoption of cloud-based AI solutions across industries) influencing the growth of the AI server market.
Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI server market.
Market Development: Comprehensive information about lucrative markets - the report analysis the AI server market across varied regions
Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI server market
Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players like Dell Inc. (US), Hewlett Packard Enterprise Development LP (US), Lenovo (Hong Kong), Huawei Technologies Co., Ltd. (China), IBM (US) among others in the AI server market.
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKETS COVERED AND REGIONAL SCOPE
1.3.2 INCLUSIONS AND EXCLUSIONS
1.3.3 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
1.5 UNITS CONSIDERED
1.6 LIMITATIONS
1.7 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.1.1 List of major secondary sources
2.1.1.2 Key data from secondary sources
2.1.2 PRIMARY DATA
2.1.2.1 List of primary interview participants
2.1.2.2 Breakdown of primaries
2.1.2.3 Key data from primary sources
2.1.2.4 Key industry insights
2.1.3 SECONDARY AND PRIMARY RESEARCH
2.2 MARKET SIZE ESTIMATION
2.2.1 BOTTOM-UP APPROACH
2.2.1.1 Approach to estimate market size using bottom-up analysis (demand side)
2.2.2 TOP-DOWN APPROACH
2.2.2.1 Approach to estimate market size using top-down analysis (supply side)
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
2.4 RESEARCH ASSUMPTIONS
2.5 RISK ASSESSMENT
2.6 RESEARCH LIMITATIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI SERVER MARKET
4.2 AI SERVER MARKET, BY PROCESSOR TYPE
4.3 AI SERVER MARKET, BY FUNCTION
4.4 AI SERVER MARKET, BY COOLING TECHNOLOGY
4.5 AI SERVER MARKET, BY FORM FACTOR
4.6 AI SERVER MARKET, BY DEPLOYMENT
4.7 AI SERVER MARKET, BY APPLICATION
4.8 AI SERVER MARKET, BY END USER
4.9 AI SERVER MARKET, BY COUNTRY
4.10 AI SERVER MARKET, BY REGION
5 MARKET OVERVIEW
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Increase in data traffic and need for high computing power
5.2.1.2 Increasing adoption of machine learning and deep learning algorithms
5.2.1.3 Rising adoption of cloud-based AI solutions across industries
5.2.1.4 Advancements in GPU and ASIC technologies for AI acceleration
5.2.2 RESTRAINTS
5.2.2.1 High initial costs of AI server hardware and infrastructure
5.2.2.2 Shortage of AI hardware experts and skilled workforce
5.2.2.3 Power consumption and cooling challenges for high-density AI servers
5.2.3 OPPORTUNITIES
5.2.3.1 Growing potential of AI in healthcare sector
5.2.3.2 Increasing investments in data centers by cloud service providers
5.2.3.3 Growing demand for AI-as-a-Service (AIaaS) platforms
5.2.3.4 Increasing adoption of AI in small and medium-sized enterprises (SMEs)
5.2.4 CHALLENGES
5.2.4.1 Data security and privacy concerns
5.2.4.2 Supply chain disruptions
5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
5.4 PRICING ANALYSIS
5.4.1 AVERAGE SELLING PRICE OF KEY PLAYERS, BY PROCESSOR TYPE
5.4.2 AVERAGE SELLING PRICE TREND, BY REGION
5.5 VALUE CHAIN ANALYSIS
5.6 ECOSYSTEM ANALYSIS
5.7 INVESTMENT AND FUNDING SCENARIO
5.8 TECHNOLOGY ANALYSIS
5.8.1 KEY TECHNOLOGIES
5.8.1.1 High-performance computing (HPC)
5.8.1.2 High bandwidth memory (HBM)
5.8.1.3 GenAI workload
5.8.2 COMPLEMENTARY TECHNOLOGIES
5.8.2.1 Data center power management and cooling system
5.8.2.2 High-speed interconnects
5.8.3 ADJACENT TECHNOLOGIES
5.8.3.1 AI development frameworks
5.8.3.2 Quantum AI
5.9 SERVER COST STRUCTURE/BILL OF MATERIAL (BOM)
5.9.1 GPU SERVER
5.10 AI SERVER'S CURRENT PENETRATION AND GROWTH FORECAST
5.11 UPCOMING DEPLOYMENTS OF DATA CENTER BY CLOUD SERVICE PROVIDERS
5.12 CLOUD SERVICE PROVIDERS' CAPEX
5.13 PROCESSOR BENCHMARKING
5.13.1 GPU BENCHMARKING
5.13.2 CPU BENCHMARKING
5.14 PATENT ANALYSIS
5.15 TRADE ANALYSIS
5.15.1 IMPORT SCENARIO (HS CODE 847150)
5.15.2 EXPORT SCENARIO (HS CODE 847150)
5.16 KEY CONFERENCES AND EVENTS, 2024-2025
5.17 CASE STUDY ANALYSIS
5.17.1 AIVRES' HIGH-PERFORMANCE COMPUTING SERVER ACCELERATES AI SOLUTION DEVELOPMENT
5.17.2 SEEWEB COLLABORATED WITH LENOVO AND NVIDIA TO LAUNCH GPU-COMPUTING-AS-A-SERVICE MODEL FOR EXPANDING AI ACCESSIBILITY
5.17.3 SHARONAI EXPANDS AI INFRASTRUCTURE WITH LENOVO TRUSCALE, DEPLOYING HUNDREDS OF GPU-DENSE SERVERS
5.17.4 SERVING INFERENCE FOR LLMS: A CASE STUDY WITH NVIDIA TRITON INFERENCE SERVER AND ELEUTHER AI
5.17.5 APPLIED DIGITAL CORPORATION EXPANDED AI CAPABILITIES WITH SUPERMICRO SERVERS
5.18 REGULATORY LANDSCAPE
5.18.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.18.2 STANDARDS
5.19 PORTER'S FIVE FORCES ANALYSIS
5.19.1 THREAT OF NEW ENTRANTS
5.19.2 THREAT OF SUBSTITUTES
5.19.3 BARGAINING POWER OF SUPPLIERS
5.19.4 BARGAINING POWER OF BUYERS
5.19.5 INTENSITY OF COMPETITIVE RIVALRY
5.20 KEY STAKEHOLDERS AND BUYING CRITERIA
5.20.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.20.2 BUYING CRITERIA
6 AI SERVER MARKET, BY PROCESSOR TYPE
6.1 INTRODUCTION
6.2 GPU-BASED SERVERS
6.2.1 INCREASING INTEGRATION OF GPU-BASED AI SERVER BY CLOUD PROVIDERS TO BOOST MARKET
6.3 FPGA-BASED SERVERS
6.3.1 GROWING NEED FOR FLEXIBILITY AND CUSTOMIZATION FOR AI WORKLOADS TO DRIVE DEMAND FOR FPGA-BASED SERVERS
6.4 ASIC-BASED SERVERS
6.4.1 RISING DEMAND FOR CUSTOMIZED, HIGH-PERFORMANCE AI PROCESSING TO FUEL ADOPTION OF ASIC-BASED SERVERS
7 AI SERVER MARKET, BY FUNCTION
7.1 INTRODUCTION
7.2 TRAINING
7.2.1 SURGE IN DEEP LEARNING TECHNOLOGIES TO DRIVE AI SERVER MARKET GROWTH
7.3 INFERENCE
7.3.1 SHIFT TOWARDS EDGE COMPUTING TO BOOST DEMAND FOR AI INFERENCE SERVERS
8 AI SERVER MARKET, BY COOLING TECHNOLOGY
8.1 INTRODUCTION
8.2 AIR COOLING
8.2.1 COST-EFFECTIVE AND SIMPLE INSTALLATION OF AIR COOLING TECHNOLOGY TO DRIVE DEMAND
8.3 LIQUID COOLING
8.3.1 INCREASING COOLING DEMANDS OF HPC AND AI WORKLOADS TO FUEL MARKET
8.4 HYBRID COOLING
8.4.1 RISE OF AI-DRIVEN MACHINE LEARNING, NATURAL LANGUAGE PROCESSING, AND COMPUTER VISION TO BOOST DEMAND
9 AI SERVER MARKET, BY FORM FACTOR
9.1 INTRODUCTION
9.2 RACK-MOUNTED SERVERS
9.2.1 ADVANCEMENTS IN COOLING TECHNOLOGIES AND ENERGY EFFICIENCY TO DRIVE DEMAND FOR RACK-MOUNTED AI SERVERS
9.3 BLADE SERVERS
9.3.1 INCREASING DEMAND FOR HANDLING AI WORKLOADS IN HEALTHCARE, FINANCE, AND AUTOMOTIVE INDUSTRIES TO DRIVE MARKET
9.4 TOWER SERVERS
9.4.1 INCREASED USE IN MACHINE LEARNING, DATA ANALYTICS, AND SMALLER-SCALE AI INFERENCING TASKS TO BOOST DEMAND
10 AI SERVER MARKET, BY DEPLOYMENT
10.1 INTRODUCTION
10.2 ON-PREMISES
10.2.1 INCREASING IMPLEMENTATION IN HEALTHCARE AND FINANCE SECTORS TO DRIVE MARKET
10.3 CLOUD
10.3.1 ABILITY TO RAPIDLY ADAPT TO FLUCTUATING WORKLOADS WITHOUT HEAVY UPFRONT INVESTMENTS TO DRIVE GROWTH
11 AI SERVER MARKET, BY APPLICATION
11.1 INTRODUCTION
11.2 GENERATIVE AI
11.2.1 RULE-BASED MODELS
11.2.1.1 Growing use in finance, healthcare, or legal systems to drive market
11.2.2 STATISTICAL MODELS
11.2.2.1 Increasing availability of vast datasets from IoT devices, social media, and public health data to drive demand
11.2.3 DEEP LEARNING
11.2.3.1 Proliferation of AI in healthcare, automotive, and consumer electronics to boost demand
11.2.4 GENERATIVE ADVERSARIAL NETWORKS (GANS)
11.2.4.1 Increasing need for high-quality, scalable data generation to support market growth
11.2.5 AUTOENCODERS
11.2.5.1 Increasing use in cloud and edge computing to enhance server performance to drive demand
11.2.6 CONVOLUTIONAL NEURAL NETWORKS (CNNS)
11.2.6.1 Proliferation of visual data through smart devices, security cameras, and self-driving cars to drive market
11.2.7 TRANSFORMER MODELS
11.2.7.1 Availability of large-scale datasets and advancements in data storage technologies to fuel market
11.3 MACHINE LEARNING
11.3.1 RAPID ADVANCEMENT AND DEPLOYMENT OF ML MODELS TO BOOST DEMAND
11.4 NATURAL LANGUAGE PROCESSING
11.4.1 INCREASING NEED FOR REAL-TIME REQUIREMENTS OF NLP APPLICATIONS TO SUPPORT MARKET GROWTH
11.5 COMPUTER VISION
11.5.1 SURGE IN COMPUTER VISION APPLICATIONS IN SECURITY, HEALTHCARE, AUTOMOTIVE, AND RETAIL FUELING DEMAND FOR AI SERVERS
12 AI SERVER MARKET, BY END USER
12.1 INTRODUCTION
12.2 CLOUD SERVICE PROVIDERS
12.2.1 SURGING AI WORKLOADS AND CLOUD ADOPTION TO STIMULATE MARKET GROWTH
12.3 ENTERPRISES
12.3.1 HEALTHCARE
12.3.1.1 Integration of AI for computer-aided drug discovery to foster market growth
12.3.2 BFSI
12.3.2.1 Growing need for fraud detection in financial institutions to boost demand
12.3.3 AUTOMOTIVE
12.3.3.1 Growing focus on safety, efficiency, and enhanced driving experiences to drive growth
12.3.4 RETAIL & E-COMMERCE
12.3.4.1 Personalized shopping experiences and improved customer service to offer lucrative growth opportunities
12.3.5 MEDIA & ENTERTAINMENT
12.3.5.1 Real-time analysis of viewer preferences, engagement patterns, and demographic information to augment market growth
12.3.6 OTHERS
12.3.6.1 Proliferation of visual data through smart devices, security cameras, and self-driving cars to drive demand
12.4 GOVERNMENT ORGANIZATIONS
12.4.1 INCREASING USE OF AI IN NATIONAL SECURITY AND DEFENSE TO DRIVE MARKET GROWTH
13 AI SERVER MARKET, BY REGION
13.1 INTRODUCTION
13.2 NORTH AMERICA
13.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA
13.2.2 US
13.2.2.1 Government-led initiatives to boost semiconductor manufacturing to drive market
13.2.3 CANADA
13.2.3.1 Growing emphasis on commercializing AI to fuel demand
13.2.4 MEXICO
13.2.4.1 Increasing shift toward digital platforms and cloud-based solutions to accelerate demand
13.3 EUROPE
13.3.1 MACROECONOMIC OUTLOOK FOR EUROPE
13.3.2 UK
13.3.2.1 Growing investments in data center infrastructure to boost demand
13.3.3 GERMANY
13.3.3.1 Presence of robust industrial base to offer lucrative growth opportunities
13.3.4 FRANCE
13.3.4.1 Increasing number of AI startups to accelerate demand for AI servers
13.3.5 ITALY
13.3.5.1 Growing adoption of digitalization in automotive and healthcare sectors to drive market
13.3.6 SPAIN
13.3.6.1 Growing collaborations and partnerships among AI manufacturers to support market growth
13.3.7 REST OF EUROPE
13.4 ASIA PACIFIC
13.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
13.4.2 CHINA
13.4.2.1 Surge in research funding and implementation of supportive regulatory policy to augment market growth
13.4.3 JAPAN
13.4.3.1 Rising adoption of AI servers to advance robotics systems to offer lucrative growth opportunities
13.4.4 SOUTH KOREA
13.4.4.1 Thriving semiconductor industry in South Korea to drive market for AI servers
13.4.5 INDIA
13.4.5.1 Government-led initiatives to boost AI infrastructure to foster market growth
13.4.6 REST OF ASIA PACIFIC
13.5 ROW
13.5.1 MACROECONOMIC OUTLOOK FOR ROW
13.5.2 MIDDLE EAST
13.5.2.1 Growing emphasis on digital transformation and technological innovation to drive market growth
13.5.2.2 GCC countries
13.5.2.3 Rest of Middle East
13.5.3 AFRICA
13.5.3.1 Rising internet penetration and mobile subscriptions to offer lucrative growth opportunities
13.5.4 SOUTH AMERICA
13.5.4.1 Growing need to store vast amounts of data to boost demand
14 COMPETITIVE LANDSCAPE
14.1 OVERVIEW
14.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2020-2024
14.3 REVENUE ANALYSIS
14.4 MARKET SHARE ANALYSIS, 2023
14.5 COMPANY VALUATION AND FINANCIAL METRICS
14.6 BRAND/PRODUCT COMPARISON
14.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
14.7.1 STARS
14.7.2 EMERGING LEADERS
14.7.3 PERVASIVE PLAYERS
14.7.4 PARTICIPANTS
14.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
14.7.5.1 Company footprint
14.7.5.2 Region footprint
14.7.5.3 Processor type footprint
14.7.5.4 Function footprint
14.7.5.5 Cooling technology footprint
14.7.5.6 Form factor footprint
14.7.5.7 Deployment footprint
14.7.5.8 Application footprint
14.7.5.9 End user footprint
14.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
