U.S. AI Server Market Segment Analysis On The Basis Of Processor Type, Cooling Technology, Form Factor, End-Use And Forecast

 San Francisco, 22 December 2025: The Report U.S. AI Server Market (2025 - 2030) Size, Share & Trends Analysis Report By Processor Type (GPU-based Servers, FPGA-based Servers), By Cooling Technology (Air Cooling, Liquid Cooling), By Form Factor, By End-use, And Segment Forecasts

The U.S. AI server market size was estimated at USD 34.42 billion in 2024 and is projected to grow at a CAGR of 37.1% from 2025 to 2030. The U.S. AI server industry is experiencing rapid expansion, driven by growing demand for artificial intelligence across sectors such as healthcare, finance, and automotive. Companies are investing heavily in advanced server infrastructure to support increasingly complex AI workloads, particularly those involving machine learning and deep learning. The market is characterized by the strong presence of leading technology firms that offer a broad range of AI-optimized servers, including GPU-powered and high-performance computing systems.

 

Cloud service providers and data center operators are playing a critical role in scaling AI capabilities, while innovation in cooling technologies and energy-efficient designs continues to enhance server performance. The rise of edge computing and AI inference applications is also influencing server design and deployment strategies, positioning the U.S. as a global leader in AI server technology.

U.S. federal initiatives, such as the CHIPS and Science Act and National AI Research Resource (NAIRR), are investing billions into domestic AI infrastructure. These policies aim to strengthen national competitiveness, bolster AI R&D, and reduce dependency on foreign hardware. As a result, public-private partnerships are accelerating the deployment of AI servers in academic, defense, and national lab environments, expanding demand across various sectors.

In additionally, AI adoption in the U.S. is increasingly verticalized, with industries like agriculture, legal tech, logistics, and energy developing tailored AI models. These domain-specific applications require customized server configurations including optimized memory bandwidth, storage solutions, and thermal management to meet niche performance requirements. U.S.-based OEMs and integrators are responding by offering modular AI server architectures purpose-built for these specialized workloads.

Moreover, sustainability has become a critical factor in U.S. server procurement decisions. Enterprises and cloud providers are investing in energy-efficient AI servers to align with ESG goals and rising regulatory scrutiny around carbon emissions. U.S. data centers are increasingly adopting liquid cooling, AI-powered workload optimization, and renewable energy integration, creating demand for AI servers that support green computing practices.

Sectors such as healthcare, finance, telecommunications, and retail are increasingly integrating AI technologies to enhance operations and customer experiences. The need for high-performance computing to support these applications is driving the demand for AI servers. In addition, U.S. government policies and funding aimed at promoting AI research and development are fostering innovation and accelerating the adoption of AI technologies, thereby boosting the demand for AI server infrastructure.

 

Access Research Report of U.S. AI Server Market @ https://www.grandviewresearch.com/industry-analysis/us-ai-server-market-report

Key U.S. AI Server Company Insights

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

• Dell Inc. offers a broad range of IT solutions, including its PowerEdge XE series servers, which are optimized for AI and deep learning workloads. The PowerEdge XE9680, featuring eight NVIDIA H100 GPUs and NVIDIA AI software, is built for high-performance AI model training and deployment. It provides enterprises with a scalable and efficient platform for applications such as NLP, recommender systems, and data analytics.
• IBM Corporation offers specialized AI hardware through its Power Systems, built on POWER9 and POWER10 processors, designed to accelerate deep learning workloads. Featuring technologies like PCIe 4.0, NVIDIA NVLink, and OpenCAPI, these systems enable faster data processing and outperform traditional x86 servers. The POWER9-based AC922, for example, delivers up to 4x better deep learning performance, making it ideal for applications such as scientific research and real-time fraud detection.

Super Micro Computer, Inc., and ADLINK Technology Inc. are some of the emerging market participants in the U.S. market.

• Super Micro Computer, Inc. provides high-performance servers and storage solutions, including its H12 and H14 GPU-accelerated server series, which support the latest NVIDIA and AMD GPUs. These systems deliver dense computing power for AI, deep learning, and HPC workloads. Designed for flexibility, Supermicro's AI platforms offer multiple form factors and cooling options including both air and liquid cooling—to suit a wide range of deployment needs.
• ADLINK Technology Inc. focuses on embedded computing solutions, offering products like computer-on-modules, industrial motherboards, and complete systems. Its MEC-AI7400 series is an AI edge server tailored for smart manufacturing, featuring a compact, dustproof chassis and integration of GPU, motion control, I/O, and image capture cards. This robust design enables real-time data processing and intelligent decision-making in demanding industrial environments.

Key U.S. AI Server Companies:

• Dell Technologies
• Hewlett Packard Enterprise (HPE)
• IBM Corporation
• NVIDIA Corporation
• Super Micro Computer, Inc.
• Intel Corporation
• Lenovo Group Limited
• Cisco Systems, Inc.
• ADLINK Technology Inc.
• Advanced Micro Devices, Inc. (AMD)

Recent Developments

• In May 2025, Dell Inc. introduced new servers featuring NVIDIA’s Blackwell Ultra chips to address rising AI workload demands. Available in both air- and liquid-cooled configurations, these servers support up to 192 chips by default, with options to scale up to 256 chips. This setup enables AI model training speeds up to four times faster than previous generations.
• In May 2025, NVIDIA Corporation launched the DGX Spark and DGX Station systems, featuring ConnectX-8 SuperNIC for up to 800 Gb/s networking. The DGX Station serves as a high-performance desktop for single-user AI workloads or as a shared, on-demand compute resource for multiple users.
• In October 2024, Supermicro introduced new servers and GPU-accelerated systems featuring AMD EPYC 9005 Series CPUs and AMD Instinct MI325X GPUs. These systems are optimized for AI-ready data centers, offering improved performance and efficiency.
• In October 2024, Cisco introduced plug-and-play AI solutions, including an AI server family powered by NVIDIA accelerated computing and AI PODs, to simplify AI infrastructure deployment for enterprises.

About Grand View Research

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