The global computing power market is entering a transformative era, fueled by rapid advancements in artificial intelligence (AI), cloud computing, high-performance computing (HPC), and edge infrastructure. According to the latest industry analysis, the global computing power market size was valued at USD 238.9 billion in 2024 and is projected to grow from USD 254.7 billion in 2025 to USD 620.5 billion by 2033, registering a CAGR of 11.5% during the forecast period (2025–2033).
The accelerating deployment of large language models (LLMs), AI-driven analytics, scientific simulations, autonomous systems, and enterprise-scale cloud applications is significantly increasing demand for advanced computational capabilities worldwide. Organizations across industries are investing heavily in scalable GPU infrastructure, AI accelerators, liquid cooling technologies, and distributed cloud systems to support compute-intensive workloads.
The rapid expansion of AI model training and inference applications continues to reshape the computing power landscape. Enterprises, hyperscalers, and research institutions are deploying increasingly powerful GPU clusters and AI accelerators to handle complex workloads requiring massive parallel processing capabilities.
High-performance GPU servers dominated the market in 2024 due to their critical role in AI training, simulation modeling, and advanced scientific workloads. AI model training also emerged as the largest application segment as organizations increasingly adopt generative AI systems and foundation models with billions of parameters.
Cloud service providers (CSPs) remain the leading distribution channel, enabling organizations to access scalable computing resources through flexible pay-as-you-go models. Technology companies, including AI startups, SaaS providers, and hyperscale cloud firms, continue to represent the largest end-user segment due to their extensive reliance on advanced compute infrastructure.
The computing power market is witnessing a strong shift toward sustainability-focused infrastructure development. As AI workloads place unprecedented pressure on data centers, enterprises are prioritizing energy-efficient cooling systems, optimized chip architectures, and sustainable compute operations.
In December 2024, Schneider Electric and NVIDIA announced a global partnership to develop AI-optimized energy and cooling architectures capable of supporting up to 132 kW per rack using advanced liquid cooling technologies. These systems are designed to reduce cooling-related energy consumption while supporting increasingly dense AI environments.
The growing emphasis on ESG compliance and carbon reduction strategies is accelerating adoption of energy-efficient computing platforms globally.
The rise of dense AI workloads is also accelerating adoption of advanced liquid cooling solutions. Traditional air-cooling systems are increasingly unable to manage thermal loads generated by modern GPU clusters and AI accelerators.
In February 2025, Vertiv launched its Vertiv™ Liquid Cooling Services portfolio designed specifically for AI-ready and high-density computing environments. The solution includes lifecycle services ranging from deployment and fluid management to ongoing maintenance of liquid-cooled infrastructure.
This transition toward thermally optimized infrastructure is expected to become a defining feature of next-generation data centers over the coming decade.
Despite strong growth momentum, the market faces significant infrastructure challenges tied to escalating energy consumption and grid dependency. AI-ready data centers increasingly require power capacities exceeding 100 MW, creating bottlenecks related to grid expansion, energy provisioning, and permitting approvals.
Inconsistent global carbon reporting standards and varying sustainability incentives also create uncertainty for operators seeking to scale environmentally responsible compute infrastructure.
The increasing need for localized, low-latency AI processing is generating strong opportunities for edge computing and on-premise AI systems. Industries such as healthcare, manufacturing, smart cities, and financial services are investing in localized computing infrastructure to improve real-time analytics and data sovereignty.
In May 2025, Intel introduced its Gaudi 3 AI accelerators tailored for edge and private data center deployments. The new accelerators deliver improved performance-per-watt efficiency while supporting enterprise AI training and inference applications in compact environments.
This trend is expected to open new revenue opportunities for server manufacturers, semiconductor firms, and infrastructure providers focused on scalable edge AI solutions.
North America dominated the global computing power market in 2024, supported by its strong ecosystem of hyperscale cloud providers, semiconductor innovators, AI research institutions, and advanced digital infrastructure.
The United States continues to lead global investments in AI data centers, GPU clusters, and cloud-native compute platforms. Major companies such as Microsoft, Amazon, Google, and NVIDIA are significantly expanding AI infrastructure to support rapidly growing enterprise AI demand.
Canada is also emerging as a key computing power hub, benefiting from strong academic AI research, renewable energy resources, and environmentally sustainable data center development.
Asia-Pacific is projected to witness the fastest market growth during the forecast period, driven by aggressive government-backed AI strategies, semiconductor investments, and large-scale digital transformation initiatives.
China continues to expand its supercomputing and AI infrastructure capabilities through extensive investments in domestic chip production, AI cloud platforms, and smart city deployments. Meanwhile, India is rapidly scaling AI compute clusters across Bengaluru, Hyderabad, and Pune to support language AI, industrial automation, and digital governance initiatives.
The region’s expanding cloud ecosystems and growing startup activity are expected to accelerate long-term demand for scalable computing power solutions.
Europe is strengthening its position in the computing power market through initiatives focused on digital sovereignty, secure infrastructure, and sustainable HPC development.
Programs such as EuroHPC and the European Green Deal are encouraging investments in low-carbon data centers, sovereign AI clusters, and energy-efficient supercomputing systems. Germany and France remain key regional contributors, leveraging advanced manufacturing, enterprise AI adoption, and strong public-private partnerships to expand compute infrastructure capabilities.
NVIDIA Corporation NVIDIA continues to dominate the AI computing ecosystem through its advanced GPU architectures, DGX supercomputing systems, and AI software stack. In 2025, the company expanded its DGX lineup with desktop-scale AI systems designed for enterprise researchers and developers.
Amazon Web Services (AWS) AWS remains the global leader in cloud infrastructure services, offering scalable AI compute resources and proprietary AI chips that support enterprise-grade machine learning and generative AI workloads.
Microsoft Corporation (Azure) Microsoft Azure continues to strengthen its position through deep OpenAI integration, AI-optimized cloud services, and aggressive investments in liquid-cooled AI data centers and GPU-rich infrastructure.
Google LLC (Google Cloud Platform) Google Cloud is expanding its AI infrastructure through Tensor Processing Units (TPUs), advanced AI research initiatives, and energy-efficient hyperscale data centers tailored for large-scale machine learning applications.
Alibaba Cloud (Alibaba Group) Alibaba Cloud is accelerating AI and cloud infrastructure expansion across Asia-Pacific while investing heavily in domestic AI chips and distributed computing platforms.
IBM Corporation IBM continues to focus on hybrid cloud computing, enterprise AI deployment, and quantum computing research aimed at next-generation computational workloads.
Oracle Corporation Oracle Cloud Infrastructure is strengthening its AI and HPC offerings through scalable cloud architectures optimized for enterprise databases, analytics, and AI applications.
Intel Corporation Intel is advancing edge AI and private data center solutions through innovations such as its Gaudi AI accelerators and high-performance server processors.
Advanced Micro Devices, Inc. (AMD) AMD continues expanding its AI and HPC portfolio through advanced GPUs, CPUs, and strategic acquisitions, including its 2025 acquisition of photonics startup Enosemi.
Huawei Technologies Co., Ltd. Huawei is driving AI compute adoption across China through its Ascend AI processors, cloud platforms, and enterprise AI infrastructure solutions.
The computing power market is expected to become one of the foundational pillars of the global digital economy over the next decade. As enterprises, governments, and research institutions increasingly rely on AI, machine learning, and real-time analytics, demand for scalable and energy-efficient computing infrastructure will continue to rise dramatically.
The next phase of market evolution will likely be shaped by advancements in liquid cooling, photonic interconnects, edge AI systems, quantum computing, and sustainable data center technologies. Companies capable of delivering high-performance, low-latency, and environmentally optimized computing solutions will be well-positioned to lead the future of AI-driven digital transformation.
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