U.S. AI Server Market (2025 - 2030)

U.S. AI Server Market Size & Trends

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.

Processor Type Insights

The GPU-based servers segment led the market with the largest revenue share of 52.19%in 2024, due to their supreme performance in handling the complex workloads characteristic of artificial intelligence (AI) and machine learning (ML) applications. In addition, the architecture of GPUs is suited for the massive parallel processing required in AI tasks, and GPUs can execute thousands of threads simultaneously, ideal for the matrix and tensor computations central to deep learning models. For instance,NVIDIAdeveloped a comprehensive platform that includes hardware like the A100 and H100 GPUs, along with software libraries such as CUDA and cuDNN. In 2023, NVIDIA shipped approximately 3.76 million data center GPUs, capturing a dominant share of the data center GPU market. In conclusion, the combination of GPUs' architectural suitability for AI workloads and NVIDIA's market leadership has propelled GPU-based servers to dominate the U.S. AI server industry.

The ASIC-based servers segment is anticipated to grow at the fastest CAGR during the forecast period. ASICs are custom-built for models or algorithms, enabling significantly higher performance-per-watt and cost-efficiency. The targeted performance is attractive to hyperscalers and enterprises deploying large-scale AI inference tasks, such as search ranking, recommendation engines, and real-time translation, where latency and power consumption are critical factors. Moreover, U.S.-based startups such as Cerebras, Groq, and Tenstorrent are introducing innovative ASIC-based architectures tailored for both training and inference. Therefore, these factors are contributing notably to spurring the market growth during the forecast period.

Cooling Technology Insights

The air cooling segment led the market with the largest revenue share of 65.41% in 2024. Air cooling systems have been the industry standard for decades and are well-established in most U.S. data centers. Organizations have already invested heavily in air-cooled HVAC systems, raised floor layouts, and hot/cold aisle containment. In addition, server manufacturers and data center providers across the U.S. continue to prioritize air-cooled system designs, making them readily available and easier to source, deploy, and maintain. From Dell and HPE to Supermicro and Lenovo, most mainstream server vendors offer optimized air-cooled AI server solutions compatible with existing data center standards. Subsequently, the factors mentioned earlier are contributing substantially to driving the market growth in the United States.

The hybrid cooling segment is expected to register at the fastest CAGR from 2025 to 2030. The increasing adoption of AI and machine learning applications has led to higher power densities in data centers, necessitating advanced cooling solutions. Hybrid cooling systems combine the benefits of air and liquid cooling, optimizing energy consumption and reducing operational costs. In addition, major industry players are investing in hybrid cooling technologies to enhance their product offerings. For example, in May 2025, Dell Technologies introduced the PowerCool Enclosed Rear Door Heat Exchanger (eRDHx), which captures 100% of the heat generated by IT equipment through a self-contained airflow design. Therefore, these factors are expected to drive the market growth during the forecast period.

Form Factor Insights

The rack-mounted servers segment led the market with the largest revenue share of 39.61% in 2024. Rack-mounted servers offer modular scalability, allowing organizations to easily add or swap out computed units as AI workload demands evolve. In addition, rack-mounted servers provide superior airflow and cooling management, which is critical when running heat-intensive AI hardware like GPUs, TPUs, or AI-optimized ASICs.

Moreover, many AI servers are equipped with multi-GPU configurations that generate significant heat. Rack-mounted enclosures can efficiently handle these thermal loads with integrated or external cooling solutions. Subsequently, the factors mentioned above are contributing remarkably to driving the market growth.

The blade servers segment is expected to register at the fastest CAGR during the forecast period, due to their space efficiency, modular design, and growing demand in edge AI, high-performance enterprise environments, and energy-constrained data centers.Blade servers are designed to maximize compute density in limited rack space, which is increasingly valuable in modern data centers facing real estate and power constraints. Each blade shares a common chassis that provides power, cooling, and connectivity, allowing organizations to deploy multiple high-performance nodes in less space than traditional rack-mounted servers.

In addition, major OEMs such as HPE (Synergy), Dell Technologies (PowerEdge MX7000), and Lenovo are designing AI-optimized blade systems that support high-bandwidth interconnects, multiple GPUs per blade, and high-speed memory modules.For instance, in 2024, Dell Technologies announced an upgrade to its PowerEdge blade systems to support NVIDIA H100 GPUs and Intel’s Sapphire Rapids processors, targeting enterprise AI workloads with high density and modularity.

End-use Insights

The IT & telecommunication segment led the market with the largest revenue share of 26.60% in 2024, due to enabling intelligent automation, enhancing network performance, and powering next-generation digital services. In 5G and edge computing, AI servers are vital to managing the ultra-low latency and high-bandwidth requirements of modern applications. Deployed at the network edge in Multi-access Edge Computing setups, AI servers support real-time data processing close to the end user. AI servers also enable network slicing in 5G, allowing operators to create multiple virtual networks tailored to different types of users or services on a shared physical infrastructure. For instance, in September 2023, the U.S. National Science Foundation's Directorate for Technology, Innovation and Partnerships (TIP) is investing USD 25 million to address challenges in 5G communication infrastructure and security.

The retail & e-commerce segment is expected to register at the fastest CAGR during the forecast period. AI servers are revolutionizing the retail and e-commerce industry by enabling intelligent automation, hyper-personalization, inventory optimization, and real-time customer engagement. As retailers and online platforms increasingly rely on data-driven insights to enhance customer experience and streamline operations, AI servers provide the high-performance infrastructure necessary to process vast volumes of data and run complex machine learning models.

In addition, inventory management and demand forecasting are other critical area where AI servers add value. Retailers leverage AI models to predict product demand across different locations and time periods by analyzing historical sales data, seasonality trends, and external factors such as weather or local events. AI servers facilitate the fast processing and continuous learning required to update these forecasts in real time.

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.

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.

U.S. AI Server Market