AI Server Market Size To Hit USD 854.16 Billion By 2030

 San Francisco, 15 December 2025: The Report AI Server Market (2025 - 2030) Size, Share, & Trends Analysis Report By Processor Type (GPU-based Servers, ASIC-based Servers), By Cooling Technology (Air Cooling, Hybrid Cooling), By Form Factor (Rack-Mounted Servers), By End Use, By Region, And Segment Forecasts

The global AI server market size was estimated at USD 124.81 billion in 2024 and is projected to reach USD 854.16 billion by 2030, growing at a CAGR of 38.7% from 2025 to 2030. Cloud computing and hyperscale data center expansion are driving the AI servers market growth.

Key Market Trends & Insights

• North America AI server market dominated the global market and held the major revenue share of over 37.0% in 2024.
• The U.S. AI server market is projected to grow during the forecast period.
• By processor type, the GPU-based servers segment accounted for the largest revenue share of over 52.0% in 2024.
• By cooling technology, the air cooling segment dominated the market and accounted for a revenue share of over 65.0% in 2024.
• By form factor, the rack-mounted servers segment dominated the market and accounted for a revenue share of over 39.0% in 2024.

Market Size & Forecast

• 2024 Market Size: USD 124.81 Billion
• 2030 Projected Market Size: USD 854.16 Billion
• CAGR (2025-2030): 38.7%
• North America: Largest market in 2024
• Europe: Fastest growing market

Major cloud service providers are investing heavily in AI-optimized server infrastructure to cater to the growing number of enterprises seeking AI-as-a-service solutions. These deployments often involve custom server architectures, which allow for better energy efficiency and computational throughput. Moreover, as organizations shift toward hybrid and multi-cloud strategies, the need for scalable, AI-optimized server systems within data centers becomes even more critical, supporting both centralized training and edge inferencing scenarios.

The rapid adoption of generative AI applications across various industries is driving AI server market growth. From content creation and customer service automation to personalized marketing and drug discovery, generative AI is pushing the boundaries of compute-intensive operations. These applications require highly specialized server architectures capable of supporting massive parallelism and fast data throughput. The surge in demand for generative models like GPT and DALL·E is compelling enterprises and cloud providers to invest heavily in AI servers that can manage such computational intensity with speed and reliability.

 

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The rise of hybrid and multi-cloud strategies is also accelerating the deployment of AI servers. Enterprises are opting for flexible infrastructure models that allow seamless integration between on-premises systems and public cloud platforms. Artificial intelligence (AI) servers designed for hybrid deployments must be highly adaptable, scalable, and secure to ensure smooth data mobility and unified AI workloads across diverse environments. This flexibility is crucial for organizations looking to optimize cost efficiency, performance, and regulatory compliance when deploying AI solutions at scale.

Cybersecurity and data privacy concerns are further fueling the need for on-premises AI servers. As organizations become increasingly reliant on AI for handling sensitive information such as biometric data, financial records, and proprietary business intelligence, there is growing reluctance to process such data in public cloud environments. On-prem AI servers offer the control and security needed to meet strict compliance standards like GDPR, HIPAA, and PCI-DSS, making them indispensable for industries such as healthcare, finance, and defense.

Moreover, the growth of AI chipsets and system-on-chip (SoC) technologies is transforming the design and capabilities of AI servers. Innovations in AI-specific hardware are leading to more compact, energy-efficient servers that can deliver unprecedented levels of performance. These new designs enable edge computing capabilities without compromising on processing power, and they open up possibilities for AI deployment in environments previously deemed impractical, like mobile units, remote locations, or disaster recovery sites. The continuous advancement of AI hardware is thus a foundational driver pushing the server market forward.

Key AI Server Company Insights

Some key companies operating in the market Dell Inc. and IBM Corporation, among others, are some leading participants in the AI server market.

• Dell Inc. is an information technology solutions company providing a comprehensive portfolio that spans personal computers, servers, storage systems, networking equipment, software, and cloud services. The company's PowerEdge server lineup, particularly the XE series, is engineered to accelerate deep learning and AI tasks. For instance, the PowerEdge XE9680 server is designed for high-performance AI, machine learning, and deep learning workloads, enabling rapid development, training, and deployment of large machine learning models. It is the industry's first server to ship with eight NVIDIA H100 GPUs and NVIDIA AI software. It provides enterprises with a highly refined, systemized, and scalable platform to achieve breakthroughs in natural language processing, recommender systems, data analytics, and more.
• IBM Corporation is an information technology services company. IBM has developed specialized hardware to meet the demanding requirements of AI workloads. The IBM Power Systems, particularly those based on the POWER9 and POWER10 processors, are engineered to accelerate deep learning and AI tasks. These systems incorporate advanced technologies such as PCIe 4.0, NVIDIA NVLink, and OpenCAPI, facilitating faster data movement and improved performance over traditional x86 architectures. The POWER9-based AC922 servers, for instance, have demonstrated nearly four times the deep-learning framework performance compared to x86 systems, making them suitable for applications ranging from scientific research to real-time fraud detection.

Super Micro Computer, Inc., and ADLINK Technology Inc. are some emerging market participants in the AI server market.

• Super Micro Computer, Inc. specializes in high-performance server and storage solutions. The company offers a comprehensive portfolio of GPU-accelerated systems, including its H12 and H14 series servers, which support the latest NVIDIA and AMD GPUs. These servers are engineered to deliver high-density computing power, essential for tasks such as deep learning, machine learning, and high-performance computing (HPC). Supermicro's AI platforms are designed with flexibility in mind, offering various form factors and cooling options, including air and liquid cooling, to accommodate different deployment scenarios.
• ADLINK Technology Inc. specializes in designing and manufacturing embedded computing products, including computer-on-modules, industrial motherboards, data acquisition modules, and complete systems. The MEC-AI7400 series is an AI edge server designed specifically for smart manufacturing applications. This server integrates various acceleration cards, including GPU, motion control, I/O, and image capture cards, within a compact and dustproof chassis. Such a design ensures durability and adaptability in industrial settings, facilitating real-time data analysis and intelligent decision-making on the factory floor.

Key AI Server Companies:

The following are the leading companies in the AI server market. These companies collectively hold the largest market share and dictate industry trends.

• Dell Inc.
• Cisco Systems, Inc.
• IBM Corporation
• HP Development Company, L.P.
• Huawei Technologies Co., Ltd.
• Nvidia Corporation
• Fujitsu Limited
• ADLINK Technology Inc.
• Lenovo Group Limited
• Super Micro Computer, Inc.

Recent Developments

• In May 2025, Dell Inc. launched new servers powered by Nvidia's Blackwell Ultra chips to meet growing AI demand. The servers are offered in air- and liquid-cooled versions. They support up to 192 chips by default, with customization up to 256, enabling AI model training up to four times faster than before.
• In May 2025, NVIDIA Corporation launched the DGX Spark and DGX Station systems. These systems feature ConnectX-8 SuperNIC, which delivers networking speeds of up to 800 Gb/s, enabling high-speed connectivity and scalable performance. The DGX Station can function either as a powerful desktop workstation for a single user running complex AI models with local data or as a centralized compute resource accessible on-demand by multiple users. It also supports NVIDIA Multi-Instance GPU (MIG) technology, allowing the GPU to be partitioned into up to seven instances, each equipped with dedicated high-bandwidth memory, cache, and compute cores, creating a personal cloud environment ideal for AI development and data science teams.
• In April 2025, Fujitsu Limited partnered with Supermicro Inc. and Nidec Corporation to enhance data center energy efficiency. They are integrating Fujitsu’s liquid-cooling software, Supermicro’s high-performance GPU servers, and Nidec’s efficient liquid-cooling system to create AI server systems optimized for liquid cooling. This approach eliminates air cooling fans, cuts server power consumption, lowers noise, and reduces operating temperatures, boosting overall data center power usage effectiveness (PUE).

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