Global AI Server Market Size, Share & Industry Analysis Report By Processor Type (GPU-based Servers, FPGA-based Servers, and ASIC-based Servers), By Cooling Technology (Air Cooling, Liquid Cooling, and Hybrid Cooling), By Form Factor (Rack-mounted Servers

The Global AI Server Market size is expected to reach $1.6 trillion by 2032, rising at a market growth of 37.5% CAGR during the forecast period. Growth is driven by widespread AI adoption across sectors and government investments like the U.S. Department of Energy’s AI infrastructure funding. Leading firms such as Dell, HPE, and Lenovo are launching AI-optimized servers with advanced cooling and scalable designs.

Key Highlights:

 The North America market dominated the Global Market in 2024, accounting for a 37.2% revenue share in 2024.

 The US AI server market is expected to continue its dominance in North America region thereby reaching a market size of 467.1 billion by 2032.

 Among the various Processor type segments, the GPU-based Servers dominated the global market contributing a revenue share of 53.4% in 2024.

 In terms of the cooling type segmentation, the Air cooling segment is projected to dominate the global market with the projected revenue share of 61.48%m in 2032.

 Rack-mounted servers led the form factor segments in 2024, capturing a 39.6% revenue share and is projected to continue its dominance during projected period.

 Among different end user verticals, IT & Telecommunication sector with a revenue contribution of 33.1 billion in 2024 is projected to continue its dominance.

The introduction of AI servers marked a pivotal shift in the industry. Companies like NVIDIA played a crucial role by providing GPUs that significantly enhanced the processing capabilities required for AI tasks. Simultaneously, cloud service providers (CSPs) such as Amazon Web Services, Microsoft Azure, and Google Cloud began offering AI-specific infrastructure, making AI more accessible to businesses of all sizes.

The proliferation of AI applications across various sectors—including healthcare, finance, automotive, and manufacturing—further fueled the demand for AI servers. These servers became essential for tasks ranging from natural language processing and image recognition to predictive analytics and autonomous driving.

Government initiatives also contributed to the market's growth. For instance, the U.S. Department of Energy invested in AI research and infrastructure, recognizing the strategic importance of AI in national security and economic competitiveness. Similarly, countries like China and the United Kingdom launched national AI strategies, emphasizing the development of AI infrastructure, including servers.

Original Equipment Manufacturers (OEMs) responded to this growing demand by developing AI-specific server solutions. Companies like Dell Technologies, Hewlett Packard Enterprise (HPE), and Lenovo introduced servers optimized for AI workloads, featuring advanced cooling systems, high-speed interconnects, and scalable architectures.

There is a significant shift towards the development and adoption of custom AI chips. Major cloud service providers like Microsoft, Google, and Amazon are investing in designing their own application-specific integrated circuits (ASICs) to optimize AI workloads. Secondly, the integration of AI servers into edge computing environments is gaining momentum. Edge AI servers enable real-time data processing closer to the data source, reducing latency and bandwidth usage.

The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In May, 2025, Cisco joined the AI Infrastructure Partnership with BlackRock, Microsoft, NVIDIA, and others to accelerate innovation and scale secure, efficient AI data center infrastructure, enhancing AI servers and supporting technologies to meet the growing demands of AI workloads. Moreover, In May, 2025, Cisco partnered with Saudi Arabia’s HUMAIN AI enterprise to build scalable, secure AI infrastructure, supporting the Kingdom’s Vision 2030 goals. This collaboration aims to advance digital innovation by deploying cloud-based AI servers and technologies for large-scale AI development.

KBV Cardinal Matrix - AI Server Market Competition Analysis

Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and NVIDIA Corporation are the forerunners in the AI Server Market. In May, 2025, NVIDIA and HUMAIN partnered to build AI factories in Saudi Arabia powered by NVIDIA GPUs and supercomputers, aiming to train sovereign AI models and deploy digital twins using Omniverse, positioning the Kingdom as a global leader in AI and data infrastructure. Companies such as Cisco Systems, Inc. and Salesforce, Inc. are the key innovators in AI Server Market.

Market Consolidation Analysis:

The unprecedented rise of artificial intelligence has fundamentally redefined the global computing landscape, placing AI servers at the heart of modern digital infrastructure. As enterprises and governments increasingly deploy AI-driven applications—from large language models to autonomous systems—the demand for high-performance, scalable server architectures has surged.

This chapter presents a detailed analysis of market consolidation dynamics within the global AI server sector. It evaluates the structural and strategic parameters shaping competitive intensity, innovation barriers, and vendor dominance. Drawing from publicly accessible sources such as government publications, OEM disclosures, and business technology insights, the analysis quantifies consolidation levels across key indicators—ranging from technological innovation, regulatory environments, and geopolitical influence, to supply chain dependencies and entry barriers.

Market Consolidation:

1. Level of Innovation — ★★★★★ (5/5)

Innovation in the AI server market is accelerating rapidly—driven by breakthroughs in AI model training, high-performance computing (HPC), and custom chip development. However, this innovation is concentrated among a few dominant firms like NVIDIA, AMD, Intel, and Google (TPUs). These companies not only set the pace for innovation but also control much of the underlying infrastructure and intellectual property (IP), making it difficult for newcomers to compete meaningfully.

Justification:

Because the innovation is locked within vertically integrated ecosystems, smaller firms struggle to match the scale, R&D spend, and access to training data. This imbalance pushes the consolidation score to its maximum.

Product Life Cycle Analysis:

The AI Server Market is firmly in the growth stage, marked by rapid product innovation, widespread deployment, and major investment from both tech giants and governments. With key players such as NVIDIA, AMD, Intel, Google, AWS, and Microsoft leading the charge, the market is poised to enter maturity in the coming decade—but shows no signs of decline. Future competitiveness will rely on advancements in chip specialization, cooling efficiency, and AI stack integration.

The AI server market is currently in the growth phase, experiencing exponential demand due to the rise of generative AI, large language models (LLMs), and AI-as-a-Service offerings. Governments and corporations alike are building dedicated AI infrastructure, and innovation is shifting from feasibility to performance optimization.

• Microsoft Azure and OpenAI deployed tens of thousands of NVIDIA H100 GPUs in custom clusters to train.
• Amazon Web Services developed its own Trainium and Inferentia ASIC chips to reduce dependency on NVIDIA, powering internal and third-party workloads like Anthropic’s Claude.
• Google launched the Cloud TPU v5p, used in their Gemini models and made available through Google Cloud.

Market Growth Factors

The rapid integration of artificial intelligence (AI) across various sectors is a primary catalyst for the burgeoning demand for AI servers. Industries such as healthcare, finance, automotive, retail, and manufacturing are increasingly adopting AI to enhance operational efficiency, decision-making, and customer experiences. In healthcare, AI servers facilitate advanced diagnostics, predictive analytics, and personalized treatment plans by processing vast amounts of medical data. Financial institutions leverage AI for fraud detection, risk assessment, and algorithmic trading, necessitating robust server infrastructures to handle complex computations. Consequently, the rising reliance on AI across key industries is set to significantly propel the demand for high-performance AI servers.

Additionally, Technological innovations in AI-specific hardware components are significantly enhancing the performance and efficiency of AI servers. Developments in Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), Application-Specific Integrated Circuits (ASICs), and Field-Programmable Gate Arrays (FPGAs) have revolutionized the capabilities of AI servers. GPUs and TPUs are designed for parallel processing, making them ideal for training complex AI models and handling large datasets. In summary, advancements in AI-specific hardware are driving unprecedented performance, efficiency, and accessibility, fueling the rapid growth of the AI server market.

Market Restraining Factors

The rapid expansion of AI applications has led to a significant increase in energy consumption by data centers. AI servers, particularly those used for training large models, require substantial computational power, resulting in higher electricity usage. For instance, a single query consumes approximately 2.9 watt-hours of electricity, compared to 0.3 watt-hours for a standard Google search. This surge in energy demand not only raises operational costs but also contributes to increased carbon emissions. A United Nations report highlighted that indirect carbon emissions from major tech companies like Amazon, Microsoft, Alphabet, and Meta rose by an average of 150% between 2020 and 2023, largely due to energy-intensive AI data centers. In light of these challenges, prioritizing energy-efficient innovations and sustainable practices is essential to ensure the responsible growth of AI technologies.

Value Chain Analysis

The value chain of the AI Server Market begins with research and development (R&D) to drive innovation in hardware and software capabilities. This is followed by component sourcing and fabrication, where essential server parts such as processors, GPUs, and memory modules are procured and manufactured. System integration and assembly combines these components into fully functional AI servers. The software ecosystem and optimization layer enhances AI workloads through tailored software. Subsequent stages include testing and quality assurance to ensure performance standards, and marketing and distribution to reach end-users. Post-deployment involves integration in customer environments, aftermarket services and support, and continuous customer feedback, which feeds back into the R&D process, fostering product improvement and innovation.

Market Share Analysis

The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.

Processor Type Outlook

Based on the Processor Type, the AI server market is segmented into GPU-based, FPGA-based, and ASIC-based servers. The GPU-Based Servers held the largest market share among all the processor types in 2024 followed by FPGA-based Servers. The GPU-based servers continue to dominate AI training workloads, especially for large language models (LLMs) and generative AI applications.

1. GPU-Based Servers: Dominance in AI Training Workloads

Trend: GPU-based servers continue to dominate AI training workloads, especially for large language models (LLMs) and generative AI applications.

To illustrate:

• NVIDIA's Blackwell B200 GPU Launch: In March 2024, NVIDIA unveiled its Blackwell B200 GPU, boasting up to 20 petaflops of AI performance, significantly surpassing its predecessor, the H100. The B200 is designed to handle trillion-parameter AI models, enhancing both training and inference capabilities.

“The GPU is a special-purpose supercomputer. Its parallel architecture is precisely what artificial intelligence needs.”

Jensen Huang, CEO of NVIDIA

2. FPGA-Based Servers: Flexibility for Real-Time Inference

Trend: FPGA-based servers offer customizable hardware acceleration, making them ideal for real-time AI inference tasks and adaptable to evolving workloads.

Supporting News:

• Microsoft's Project Catapult: Microsoft's Project Catapult integrates FPGAs into its data centers to accelerate AI workloads. This architecture allows for reconfigurable computing, enhancing performance for services like Bing and Azure.

“When we founded Positron, it was focused on the fact that only two things matter—having a completely seamless experience going from Nvidia-based systems… and the failure point we saw for so many AI chip startups is they just took way too long and way too much to get to market.”

Thomas Sohmers, Co-founder and CTO of Positron

Cooling Technology Outlook

Based on the Cooling Technology, the Global AI Server Market is segmented into Air Cooling, Liquid Cooling, and Hybrid Cooling segments. The Air Cooling segment registered the major share of 63.4% followed by Liquid Cooling segment in Global AI Server Market in 2024.

Air Cooling

Trend:

Air cooling remains a foundational method for thermal management in data centers, utilizing techniques like hot/cold aisle containment and computer room air conditioning (CRAC) units.

To illustrate:

• Samsung Electronics announced its acquisition of German air conditioning and heating systems manufacturer FlaktGroup for €1.5 billion ($1.68 billion), aiming to strengthen its capabilities in cooling solutions for high-demand data centers, especially those supporting artificial intelligence workloads.

“The need to support hyperscale data centers, pervasive cloud services, and AI workloads is changing the data center paradigm. Today’s data centers need to be scalable, energy efficient, and advance sustainability.”

Jeremy Foster, Senior Vice President, Cisco

Date: April 30, 2024

Liquid Cooling

Trend:

Liquid cooling, including direct-to-chip and immersion methods, is gaining traction for its efficiency in managing high-density computing environments.

To illustrate:

• Super Micro Computer announced plans to build a new campus in Silicon Valley to boost liquid-cooled data center production, anticipating that up to 30% of new data centers will adopt liquid cooling solutions.

“The infrastructure required for AI computer systems is a step up from what was required from standard internet cloud data centers. The latest AI graphics processing units from Nvidia, called Blackwell, generate a lot of heat and require liquid cooling systems to remove it. Traditional air cooling systems are insufficient.”

Giordano Albertazzi, CEO, Vertiv

Date: November 1, 2024

Form Factor Outlook

Based on Form Factor, the Global AI Server Market is segmented into Rack-mounted servers, Blade Servers, and Tower servers segment. The Rack mounted server segment registered the largest revenue share of 39.6% among others in 2024 in Global AI Server Market.

Rack-Mounted Servers

Trend:

Rack-mounted servers are widely adopted globally due to their scalability and efficient space utilization, making them ideal for data centers and enterprise environments.

To illustrate:

• Amazon's $20 Billion Investment in Pennsylvania: Amazon announced plans to invest at least $20 billion in Pennsylvania to expand its data center infrastructure, reflecting its continued commitment to artificial intelligence and cloud services. This initiative is part of Amazon's broader push to support the growth of generative AI technologies.

“The pace of innovation sparked by generative AI has been breakneck and it's only just beginning. This AI wave is a major technology disruption, and we've learned from past technology disruptions (cloud, mobility, the internet) that networks need fundamental transformation to support these changes.”

Chuck Robbins, CEO, Cisco

Date: June 11, 2025

Blade Servers

Trend:

Blade servers are gaining traction globally, particularly in environments requiring high-density computing and efficient resource utilization, such as virtualization and cloud computing.

To illustrate:

• Dell's Integrated Rack Solutions: Dell Technologies announced additional servers and integrated rack solutions that represent the latest additions to the Dell AI Factory infrastructure portfolio. This new infrastructure enables customers to accelerate the time to value of their AI efforts and improves energy efficiency in support of sustainability goals.

“We achieved first-quarter record servers and networking revenue of $6.3 billion, and we’re experiencing unprecedented demand for our AI-optimized servers.”

Jeff Clarke, Vice Chairman and COO, Dell Technologies

Date: May 21, 2025

End Use Outlook

Based on the End Use, the Global AI Server Market is segmented into IT & Telecommunication, BFSI, Retail & E-commerce, Healthcare & Pharmaceutical, Automotive and Other End Use. The IT & Telecommunication segment garnered the highest revenue share of 25.7% in global market followed by BFSI and Retail & E-commerce among all other end use verticals.

IT & Telecommunications:

Trend: Telecom operators are investing in AI-ready data centers to enhance network performance and service delivery.

To illustrate:

• Cisco announced its strategic focus on developing AI-centric data centers to support businesses in adapting to emerging technologies by integrating artificial intelligence into their infrastructure.

Banking, Financial Services & Insurance (BFSI)

Trend: Financial institutions are adopting AI servers to enhance operational efficiency and customer service.

To illustrate:

• Hewlett Packard Enterprise (HPE) reported that one-third of its AI orders were driven by enterprise-based GPU server purchases, reflecting BFSI sector investments in AI infrastructure.

Regional Outlook

Based on the Region, the market is segmented into North America, Europe, Asia Pacific, and LAMEA. North America leads with a 37.20% share in 2024, propelled by early AI adoption, robust cloud infrastructure, and heavy investment in AI-specific server farms. The U.S. remains the largest contributor due to the presence of major technology firms, hyperscalers, and AI chip manufacturers.

Market Competition and Attributes

The AI Server Market remains Highly competitive, driven by regional manufacturers, startups, and niche technology providers. These companies focus on specialized AI workloads, energy-efficient designs, and affordable solutions. The absence of dominant brands creates opportunities for innovation and market entry, though limited resources and scalability challenges constrain the ability of smaller firms to capture significant market share.

Recent Strategies Deployed in the Market

• May-2025: Salesforce acquired UK-based AI firm Convergence to boost the development of next-gen AI agents and expand its AI research presence in London. The acquisition supports autonomous workflows and strengthens Salesforce’s commitment to advancing innovation in enterprise AI solutions.
• May-2025: Huawei introduced its RASTM framework to develop next-generation AI data centers in Uzbekistan, emphasizing reliability, modular construction for quicker deployment, and energy efficiency through AI-driven optimization, supporting the nation’s AI development strategy and sustainable digital transformation.
• May-2025: NVIDIA launched DGX Spark and DGX Station with partners like Dell, HP, and Acer, offering desktop AI systems delivering server-grade performance. Powered by Grace Blackwell chips, they support advanced AI workloads, bridging local development with cloud and data center scalability.
• May-2025: IBM launched LinuxONE 5, a secure, high-performance AI server platform processing 450 billion AI inferences daily. Combined with advanced AI accelerators and hybrid cloud tools, it supports scalable, cost-efficient enterprise AI workloads, driving growth in the AI server market.Apr-2025: HP and Reincubate formed a multi-year partnership to enhance on-device AI video conferencing using neural processing units (NPUs). This collaboration delivers secure, low-latency, and efficient video experiences on next-gen AI PCs, boosting digital collaboration, creativity, and performance for hybrid work.
• Apr-2025: Fujitsu and Supermicro expanded their collaboration to launch PRIMERGY GX2570 M8s GPU servers with advanced cooling options, integrated management tools, and maintenance services, enabling enterprises to deploy generative AI infrastructure securely and efficiently without owning physical server assets.

List of Key Companies Profiled

• Dell Technologies, Inc.
• Cisco Systems, Inc.
• IBM Corporation
• HP Inc.
• Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• NVIDIA Corporation
• Fujitsu Limited
• Intel Corporation
• Microsoft Corporation
• Salesforce, Inc.

Global AI Server Market Report Segmentation

By Processor Type

• GPU-based Servers
• FPGA-based Servers
• ASIC-based Servers

By Cooling Technology

• Air Cooling
• Liquid Cooling
• Hybrid Cooling

By Form Factor

• Rack-mounted Servers
• Blade Servers
• Tower Servers

By End Use

• IT & Telecommunication
• BFSI
• Retail & E-commerce
• Healthcare & Pharmaceutical
• Automotive
• Other End Use

By Geography

• North America

US

Canada

Mexico

Rest of North America

• Europe

Germany

UK

France

Russia

Spain

Italy

Rest of Europe

• Asia Pacific

China

Japan

India

South Korea

Singapore

Malaysia

Rest of Asia Pacific

• LAMEA

Brazil

Argentina

UAE

Saudi Arabia

South Africa

Nigeria

• Rest of LAMEA