DELRAY BEACH, Fla., Dec. 12, 2024 /PRNewswire/ -- The AI server market is expected to grow from USD 142.88 billion in 2024 and is estimated to reach USD 837.83 billion by 2030; it is expected to grow at a Compound Annual Growth Rate (CAGR) of 34.3% from 2024 to 2030 according to a new report by MarketsandMarkets. Market growth in AI servers is primarily driven by NVIDIA's Blackwell GPU architecture offering unprecedented performance gains, which catalyzes enterprise AI adoption. This momentum is further amplified by the explosive demand for GenAI applications requiring robust infrastructure, coupled with the shift towards AI-optimized data centers and increased cloud service provider investments in AI-specific hardware to support large language models and inference workloads.
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Browse in-depth TOC on "AI Server Market"
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AI Server Market Report Scope:
Report Coverage | Details |
Market Revenue in 2024 | $ 142.88 billion |
Estimated Value by 2030 | $ 837.83 billion |
Growth Rate | Poised to grow at a CAGR of 34.3% |
Market Size Available for | 2020-2030 |
Forecast Period | 2024-2030 |
Forecast Units | Value (USD Million/Billion) |
Report Coverage | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends |
Segments Covered | By Processor Type; Function; Cooling Technology, Form Factor, Deployment, Application, End User, and Region |
Geographies Covered | North America, Europe, Asia Pacific, and Rest of World |
Key Market Challenge | Supply chain disruptions |
Key Market Opportunities | Increasing investments in data centers by cloud service providers |
Key Market Drivers | Increase in data traffic and need for high computing power |
By Processor Type, ASIC-based servers' segment is projected to grow at a high CAGR of AI server market during the forecast period
ASIC-based servers will grow at a high rate in the AI server market as companies are increasingly using ASIC technology to meet demands for high-performance computing (HPC) and machine learning (ML). For example, Google's 6th generation Trillium TPU delivers a 4.7x compute performance boost over its predecessor (TPU v5e) and doubles High Bandwidth Memory (HBM) capacity. Companies are also focusing on custom ASICs for optimization for energy efficiency and operation cost saving, particularly for data centers with heavy AI workloads. SambaNova Systems, Inc. offers the DataScale platform that combines a high-performance ASIC with an optimized software stack supporting efficient training and inference of enterprise and data-centric applications. However, the most advanced ASIC is Cerebras WSE-3, launched in March 2024, with the world's largest chip specifically designed for AI processing. With the processing power oriented toward speeding up AI training and inference, it sets a new benchmark for the AI server market. These achievements mark the rapid development of ASIC technology and its role in advancing the AI server market.
By deployment, On-premises segment will account for the highest CAGR during the forecast period.
On-premises segment will account for the high CAGR in the forecasted period. On-premises AI platform refers to an infrastructure that runs AI services and applications entirely within an organization's physical environment rather than depending on the cloud-based hosting. This deployment model ensures that all data processing, storage, and management occur on local servers and provide an organization with complete control over its AI operations. Proper maintenance and operation of the on-premises AI platforms is in the control of employees in the organization, which increases the security as all sensitive data is kept under control. Such a configuration is quite good for industries with stringent regulations like healthcare and finance where proper privacy to their data is required. These service providers can offer low latency that allows data and analytics to be processed in real time. Furthurmore, for applications in sectors like gaming, finance, or healthcare which require minimal delay as it might result in highly serious impacts, these platforms can deliver reduced latency, enabling real-time data processing and analytics. Therefore, the demand for On-premises segment in the AI server market is expected to increase.
By end user- enterprises segment in AI server market will account for the high CAGR by 2030.
Enterprises segment will account for the high CAGR in the forecasted period. The enterprises segment in the AI server market encompasses diverse industries, including healthcare, BFSI (banking, financial services, and insurance), automotive, retail and e-commerce, media and entertainment, as well as sectors like law firms, marketing agencies, research centers, educational institutions, and architectural, engineering, and design firms. Enterprises deploy AI servers in on-premises data centers or edge devices, and they necessitate a combination of high-performance and specialized computing resources that are tailored to the specific use. This makes AI server capability to increase complex computations and support many machine learning algorithms integral components of the IT architecture within enterprise. The increasing role of AI in automating routine tasks, enhancing cyber security practices, and delivering predictive maintenance gives more operational efficiency and cost savings. Enterprises rely more on AI-based business intelligence solutions for actionable insights from large datasets. High computing capacity of AI servers enables real-time analytics, allowing businesses to act with speed and efficiency based on data.
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Asia Pacific region in AI server market will account for the high CAGR during the forecasted timeline.
The Asia Pacific is expected to grow at a high rate in the AI server industry. The region has fastest-growing technology hubs in countries such as China, Japan, South Korea, and India, which are investing strongly in AI research and development. In July 2024, China Mobile Limited (China) has launched a data center in Beijing that incorporates 4,000 AI accelerator cards. It has more than 1000 petaflops of AI computing power and uses 8000 AI servers for its intelligent computing project. Japan also invests in data center infrastructures as cloud computing, big data analytics, and IoT technologies adoption is rising. In April 2024, Microsoft announced an investment of USD 2.9 billion in AI and cloud infrastructure in Japan, with the aim of enhancing their digital capabilities and providing more advanced computing resources needed to accelerate AI workloads. The investment will also be directed toward research, skills, and cybersecurity in the country. Similarly, Oracle announced USD 8 billion for investments in Japan due to the growing need for cloud computing and AI infrastructure in the country. Such investments by tech companies will see the increase of both demand and production of AI servers in the region.
Key Players
Key companies operating in the AI server companies 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.
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