The global AI server market was valued at USD 124.81 billion in 2024 and is projected to reach USD 854.16 billion by 2030, growing at a compound annual growth rate (CAGR) of 38.7% from 2025 to 2030. The primary drivers of this growth include the expansion of cloud computing and hyperscale data centers.

Major cloud service providers are significantly investing in AI-optimized server infrastructure to meet the increasing demand from enterprises seeking AI-as-a-service solutions. These deployments often feature custom server architectures that enhance energy efficiency and computational throughput. As organizations adopt hybrid and multi-cloud strategies, the need for scalable, AI-optimized server systems within data centers becomes critical, facilitating both centralized training and edge inferencing.

The rapid adoption of generative AI applications across various sectors is also propelling the growth of the AI server market. Applications ranging from content creation and customer service automation to personalized marketing and drug discovery require highly specialized server architectures capable of supporting massive parallelism and fast data throughput. The rising demand for generative models like GPT and DALL·E is driving enterprises and cloud providers to invest heavily in AI servers that can handle such computational intensity with speed and reliability.

Furthermore, the growing trend of hybrid and multi-cloud strategies is accelerating the deployment of AI servers. Enterprises are increasingly opting for flexible infrastructure models that enable seamless integration between on-premises systems and public cloud platforms. AI servers designed for hybrid deployments must be adaptable, scalable, and secure to ensure smooth data mobility and unified AI workloads across various environments. This flexibility is essential for organizations aiming to optimize cost efficiency, performance, and regulatory compliance when deploying AI solutions at scale.

Key Market Trends & Insights

• North America: This region dominated the global AI server market, accounting for over 37.0% of revenue in 2024. The surge in data generation from connected devices, enterprise applications, and digital services has created an unprecedented demand for powerful data processing capabilities.
  
  
• U.S. Growth: The U.S. AI server market is expected to grow significantly during the forecast period, benefiting from a strong ecosystem of semiconductor and server hardware providers. Companies such as NVIDIA, AMD, and Intel, along with emerging AI chip startups like Cerebras and Groq, are developing innovative processors optimized for AI workloads.
  
  
• GPU-Based Servers: This segment accounted for the largest share of over 52.0% of revenue in 2024, driven by the rise of large language models (LLMs) and generative AI systems that require high throughput and low latency. Advanced GPU architectures, such as NVIDIA’s A100 and H100, efficiently meet these demands.
  
  
• Air Cooling: Dominating the market with over 65.0% of revenue in 2024, the air cooling segment is boosted by the increasing number of edge AI applications, particularly in environments where liquid cooling is impractical.
  
  
• Rack-Mounted Servers: This segment also led the market with over 39.0% of revenue in 2024, fueled by the growing emphasis on modular and space-efficient data center architectures.

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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
• Asia Pacific: Fastest-growing market

Key Companies & Market Share Insights

Leading companies in the AI server market include Dell Inc. and IBM Corporation, among others, which utilize product launches and developments, expansions, and collaborations to enhance their market share.

• Dell Inc. is a major player in information technology solutions, offering a comprehensive portfolio that includes personal computers, servers, storage systems, networking equipment, software, and cloud services. The PowerEdge server lineup, particularly the XE series, is engineered for high-performance AI and deep learning tasks. For example, the PowerEdge XE9680 server, which is the first to ship with eight NVIDIA H100 GPUs, enables rapid development, training, and deployment of large machine learning models.
  
  
• IBM Corporation specializes in information technology services and has developed specialized hardware to meet the demanding requirements of AI workloads. The IBM Power Systems, particularly those based on POWER9 and POWER10 processors, are designed to accelerate deep learning and AI tasks. The POWER9-based AC922 servers, for instance, have demonstrated nearly four times the deep-learning framework performance compared to traditional x86 systems.

Emerging market participants include Super Micro Computer, Inc. and ADLINK Technology Inc.

• Super Micro Computer, Inc. focuses on high-performance server and storage solutions, offering GPU-accelerated systems such as the H12 and H14 series, which support the latest NVIDIA and AMD GPUs for deep learning and high-performance computing tasks.
  
  
• ADLINK Technology Inc. designs and manufactures embedded computing products, including the MEC-AI7400 series, an AI edge server tailored for smart manufacturing applications. This server integrates various acceleration cards within a compact chassis, ensuring durability and adaptability for real-time data analysis.

Key Players

• 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.

Conclusion

The AI server market is experiencing rapid growth, driven by the increasing demand for cloud computing, generative AI applications, and hybrid infrastructures. As enterprises seek to optimize their AI capabilities, the investment in specialized server architectures will continue to rise, paving the way for innovations that enhance performance, scalability, and efficiency across various industries.

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