Data Center Accelerator Market Size and Share Analysis
Data Center Accelerator Market by Processor (GPU, CPU, ASIC, FPGA), Type (Cloud Data Center, HPC Data Center), Application (Deep Learning Training, Enterprise Inference), End-user (IT & Telecom, Healthcare, Energy) and Region - Global Forecast to 2030
OVERVIEW
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
The global data center accelerator market is expected to grow from USD 170.81 billion in 2025 to USD 372.68 billion by 2030 at a CAGR of 16.9% during the forecast period. The rapid adoption of artificial intelligence, machine learning, and high-performance computing is a key factor driving the data center accelerator industry. Technological advancements, such as the development of next-generation GPUs, FPGAs, and ASICs, along with optimized hardware-software integration, further enhance processing efficiency, scalability, and performance across cloud, enterprise, and edge data centers.
KEY TAKEAWAYS
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BY FUNCTIONKey functions of data center accelerators span training and inference. Inference workloads dominate as accelerators enable real-time AI model deployment, offering speed, scalability, and efficiency for diverse cloud and enterprise applications.
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BY PROCESSOR TYPEThe processor types comprises CPU, GPU, ASIC, and FPGA. ASICs are expected to register the highest growth, driven by their optimized performance and energy efficiency for AI and HPC workloads.
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BY TYPEKey data center types include cloud data centers and enterprise data centers. Cloud data centers remain the largest segment, driven by hyperscalers’ need for scalable, high-performance infrastructure to support generative AI and large-scale data analytics.
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BY VERTICALThe verticals for the data center accelerator market include IT & telecom, healthcare, BFSI, government, energy, automotive, retail & e-commerce, and other verticals. IT & telecom leads adoption as rising data traffic, 5G rollouts, and AI-driven services demand accelerators to ensure low latency, efficiency, and enhanced computational power.
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BY REGIONThe data center accelerator market covers Europe, North America, Asia Pacific, and the Rest of the World (RoW). North America leads the market regionally due to early AI adoption, substantial hyperscaler investments, advanced digital infrastructure, and strong enterprise deployment of high-performance data center accelerators.
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COMPETITIVE LANDSCAPEMajor players in the data center accelerator market are pursuing organic and inorganic strategies, including partnerships, acquisitions, and product innovations. NVIDIA Corporation, Intel Corporation, Advanced Micro Devices, Inc., Amazon Web Services, Inc., and Alphabet, Inc. are expanding their AI-focused data center offerings, launching specialized GPUs, ASICs, and cloud-based accelerators to strengthen market presence and support large-scale AI workloads.
Data center accelerators are essential components that enhance computing performance by offloading intensive workloads, such as AI, machine learning, and data analytics. Their adoption is expanding across cloud, enterprise, and hyperscale environments. With the rising demand for generative AI and high-performance computing, the data center accelerator market is poised for steady growth, driven by technological advancements, increasing workload complexity, and the need for energy-efficient, scalable infrastructure.
TRENDS & DISRUPTIONS IMPACTING CUSTOMERS' CUSTOMERS
The impact on consumers’ business emerges from customer trends or disruptions. It illustrates how companies’ revenue mix is expected to evolve over the next 4–5 years, moving from current offerings to new use cases, technologies, and markets. The future of the data center accelerator market is shaped by two major trends: the shift from general-purpose accelerators to AI-Specific Processors (NPU, TPU, DPU, IPU) to handle advanced AI/ML deployments, and the disruption of Edge Computing, which demands specialized accelerators for real-time analytics and IoT across all industry verticals.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
MARKET DYNAMICS
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Rise in generative AI workloads
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Scaling machine learning via cloud-based accelerators for enterprise data centers
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High total cost of ownership limiting
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Supply chain and packaging constraints
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Ability of FPGA and custom silicon accelerators to unlock high-performance, energy-efficient AI deployment
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Deployment of accelerator-as-a-service and subscription models to enable scalable AI deployment
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Power and cooling inefficiencies constraining scalable deployment of AI data center accelerators
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Addressing architectural fragmentation and integration challenges in AI accelerators
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
Driver: Rise in generative AI workloads
Generative AI workloads are a major driver for the data center accelerator market, pushing hyperscalers and enterprises to expand infrastructure. Accelerators such as GPUs, ASICs, and TPUs are critical in handling complex AI training and inference tasks, delivering the high-speed processing and scalability required for models such as large language models (LLMs). This trend is reshaping data center investments globally, with companies prioritizing accelerator-driven systems to maintain competitiveness in the AI economy.
Restraint: High total cost of ownership
One of the key restraints in the data center accelerator market is the high total cost of ownership. Deploying accelerators involves significant capital outlay not only for hardware but also for associated energy, cooling, and maintenance requirements. These costs make scalability difficult, particularly for smaller enterprises, as the operational expenses often outweigh the perceived benefits of adoption, slowing broader market penetration.
Opportunity: Ability of FPGA and custom silicon accelerators to unlock high-performance, energy-efficient AI deployment
The growing adoption of FPGAs and custom silicon solutions presents major opportunities in the data center accelerator market. Unlike general-purpose GPUs, these accelerators can be tailored for specific AI workloads, delivering superior performance and energy efficiency. Their flexibility allows enterprises to optimize deep learning, edge AI, and inference applications, making them attractive for hyperscalers and industries aiming to balance cost-effectiveness with high computational output.
Challenge: Power and cooling inefficiencies constraining scalable deployment of AI data center accelerators
A significant challenge for the market is managing power consumption and cooling requirements associated with accelerator-intensive workloads. As AI training models demand higher computational throughput, data centers face rising risks of overheating and inefficiencies in energy use. This constraint not only inflates operational costs but also limits the scalability of infrastructure, prompting the need for innovation in liquid cooling, thermal management, and energy-optimized designs.
Data Center Accelerator Market: COMMERCIAL USE CASES ACROSS INDUSTRIES
| COMPANY | USE CASE DESCRIPTION | BENEFITS |
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High-performance GPUs (H100, H200, Blackwell) for AI training and inference in cloud data centers, enterprise AI, and generative AI applications across healthcare, automotive, and financial services | Exceptional AI performance | CUDA ecosystem dominance | comprehensive software stack | industry-leading parallel processing capabilities |
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MI300 series accelerators for AI workloads, data analytics, and high-performance computing in cloud infrastructure, research institutions, and enterprise data centers | Competitive price-performance ratio | energy efficiency | open-source ROCm platform | integrated CPU-GPU chiplet designs for diverse workloads |
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Xeon CPUs with AI acceleration, Gaudi AI accelerators, and Data Center GPUs for AI inference, training, and general-purpose computing in hybrid cloud and edge deployments | Broad CPU ecosystem compatibility | integrated AI capabilities | cost-effective inference solutions | established enterprise relationships |
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Custom TPU (Tensor Processing Unit) v5/v6 for AI training and inference workloads in Google Cloud Platform, powering search, YouTube recommendations, and generative AI services | Purpose-built for TensorFlow/JAX frameworks | superior energy efficiency for AI workloads | seamless Google Cloud integration | optimized for large language models |
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Custom silicon including AWS Trainium (training) and AWS Inferentia (inference) chips for machine learning workloads, plus Graviton CPUs for general compute across AWS cloud services | Cost savings vs. GPU alternatives | tight integration with AWS services (SageMaker, EC2) | optimized power efficiency | reduced vendor dependency |
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MARKET ECOSYSTEM
The data center accelerator ecosystem involves identifying and analyzing interconnected relationships among various stakeholders, including chip designers/OEMs, raw material provides & foundries, component suppliers, accelerator manufacturers, system integrators, distributors, and end users.
Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.
MARKET SEGMENTS
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
Data Center Accelerator Market, By Function
The inference segment is expected to hold the largest share and grow the fastest during 2025-2030, driven by the rising deployment of AI-powered services. Inference workloads require rapid, low-latency data processing, making accelerators essential for real-time applications, such as recommendation engines, natural language processing, and autonomous systems. The surge in AI adoption across industries strengthens inference as both the dominant and most rapidly expanding function segment.
Data Center Accelerator Market, By Processor Type
GPUs are anticipated to account for the largest share of the market in 2030, owing to their widespread use in deep learning, high-performance computing, and AI training. Meanwhile, ASICs are expected to register the highest CAGR due to their application-specific design advantages, including energy efficiency, speed, and optimization for tasks such as AI inference and cryptocurrency mining. GPUs and ASICs drive the technological advancement of accelerator architectures.
Data Center Accelerator Market, By Type
Cloud data centers are expected to hold the largest share in 2030, supported by hyperscaler investments and the growing demand for AI-based workloads across global enterprises. Enterprise data centers, however, are projected to grow at the fastest rate as organizations increasingly adopt hybrid and edge computing strategies. The need for cost-effective, scalable, and efficient processing power is reinforcing the strong growth momentum in both segments.
Data Center Accelerator Market, By Vertical
The IT & telecom sector is projected to dominate the market in 2030, as global operators invest heavily in 5G, cloud, and AI infrastructure. Conversely, the automotive industry is expected to grow at the fastest pace, fueled by increasing reliance on AI for autonomous driving, vehicle connectivity, and smart mobility solutions. Both sectors underscore the critical role of accelerators in enabling next-generation technologies.
REGION
Asia Pacific is expected to be fastest-growing segment in the global data center accelerator market during the forecast period
Asia-Pacific is projected to be the fastest-growing segment in the data center accelerator market during 2025–2030, fueled by rapid cloud adoption, hyperscale data center expansion, and increasing AI-driven workloads. Strong government support, 5G rollouts, and rising digital transformation initiatives across China, India, and Japan further accelerate the demand for advanced high-performance computing infrastructure.
Data Center Accelerator Market: COMPANY EVALUATION MATRIX
In the data center accelerator market matrix, NVIDIA Corporation (Star) leads with a dominant market presence and an extensive GPU portfolio, driving widespread adoption across cloud, AI, and HPC workloads. Qualcomm Technologies, Inc. (Emerging Leader) is gaining traction with custom AI and edge accelerator solutions, positioning itself as a growing contender in high-performance computing and enterprise AI applications.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
KEY MARKET PLAYERS - Data Center Accelerator Companies
MARKET SCOPE
| REPORT METRIC | DETAILS |
|---|---|
| Market Size in 2024 (Value) | USD 124.04 Billion |
| Market Forecast in 2030 (Value) | USD 372.68 Billion |
| Growth Rate | CAGR of 16.9% from 2025-2030 |
| Years Considered | 2021-2030 |
| Base Year | 2024 |
| Forecast Period | 2025-2030 |
| Units Considered | Value (USD Million/Billion) and Volume (Million Units) |
| Report Coverage | Revenue forecast, company ranking, competitive landscape, growth factors, and trends |
| Segments Covered |
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| Regional Scope | North America, Europe, Asia Pacific, and RoW |
WHAT IS IN IT FOR YOU: Data Center Accelerator Market REPORT CONTENT GUIDE
DELIVERED CUSTOMIZATIONS
We have successfully delivered the following deep-dive customizations:
| CLIENT REQUEST | CUSTOMIZATION DELIVERED | VALUE ADDS |
|---|---|---|
| Local Competitive Landscape | Profiles of key regional and global players, including market share, revenue, product portfolio, and strategic initiatives in GPUs, CPUs, FPGAs, and ASICs. | Facilitated competitive benchmarking and informed strategy development for technology adoption and investment planning. |
| Regional Market Entry Strategy | Country- or region-specific go-to-market strategy covering barriers, regulations, cloud adoption trends, and competitive landscape. | Minimized entry risk and accelerated deployment of accelerator solutions in target markets. |
| Local Risk & Opportunity Assessment | Identification of regional risks, infrastructure challenges, energy constraints, and untapped opportunities for data center accelerators by vertical. | Enabled proactive risk mitigation and informed strategic investments. |
| Technology Adoption by Region | Insights on local adoption of GPUs, FPGAs, CPUs, and ASIC-based accelerators, cloud versus edge deployment trends, and enterprise versus hyperscale uptake. | Guided R&D, product positioning, and investment decisions aligned with regional demand patterns. |
RECENT DEVELOPMENTS
- August 2025 : Intel Corporation entered a USD 2.00 billion investment agreement with SoftBank Group. This strategic partnership aims to bolster Intel's capabilities in semiconductor innovation and support the growing demand for AI accelerators in data center applications.
- August 2025 : Alphabet's Google Cloud secured a six-year, over USD 10.00 billion cloud computing agreement with Meta Platforms. This deal includes the provision of servers, storage, networking, and other cloud services, supporting Meta's extensive AI infrastructure expansion plans.
- January 2025 : Amazon Web Services (AWS) announced a significant expansion of its Generative AI Innovation Center with an additional USD 100.0 million investment. This initiative aims to accelerate the development and deployment of agentic AI systems, providing customers with enhanced tools and resources to integrate advanced AI capabilities into their operations.
- November 2024 : Alphabet's Google Cloud announced the launch of a new AI accelerator optimized for large language models (LLMs). The accelerator, built on custom tensor processing units (TPUs), is designed to enhance the performance and efficiency of LLMs in data center environments. This development aims to support the growing demand for AI-driven applications and services.
Table of Contents
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Methodology
The research study involved four major activities in estimating the size of the data center accelerator market. Exhaustive secondary research has been done to collect key information about the market and peer markets. The next step has been to validate these findings and assumptions and size them with the help of primary research with industry experts across the value chain. Both top-down and bottom-up approaches have been used to estimate the market size. After this, the market breakdown and data triangulation were adopted to estimate the market sizes of segments and sub-segments.
Secondary Research
In the secondary research process, various secondary sources were referred to identify and collect information required for this study. The secondary sources include annual reports, press releases, investor presentations of companies, white papers, and articles from recognized authors. Secondary research has been mainly done to obtain key information about the market’s value chain, the pool of key market players, market segmentation according to industry trends, regional outlook, and developments from market and technology perspectives.
The data center accelerator market report estimates the global market size using the top-down and bottom-up approaches and several other dependent submarkets. Major players in the market were identified using extensive secondary research, and their presence in the market was determined using secondary and primary research. All the percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.
Primary Research
Extensive primary research has been conducted after understanding the data center accelerator market scenario through secondary research. Several primary interviews have been conducted with key opinion leaders from demand- and supply-side vendors across four major regions—North America, Europe, Asia Pacific, and RoW. Approximately 25% of the primary interviews have been conducted with the demand-side vendors and 75% with the supply-side vendors. Primary data was collected mainly through telephonic interviews, which comprised 80% of the total primary interviews; questionnaires and emails were also used to collect the data.
After successful interaction with industry experts, brief sessions were conducted with highly experienced independent consultants to reinforce the findings of our primary research. This, along with the in-house subject matter experts’ opinions, has led us to the findings as described in the report.
Note: “Others” includes sales, marketing, and product managers
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Market Size Estimation
In the market engineering process, the top-down and bottom-up approaches and data triangulation methods have been used to estimate and validate the size of the data center accelerator market and other dependent submarkets. The research methodology used to estimate the market sizes includes the following:
- Over 35 companies offering data center accelerators were initially identified, and their offerings were mapped by type, processor type, vertical, and function.
- The market was segmented based on the collected primary and secondary data to reflect the distribution of different accelerator types across industries and functions.
- Global server shipments for top players in each processor category were tracked, and a suitable penetration rate was applied to estimate the number of deployed data center accelerators.
- The market value for each processor type was calculated using the average selling price (ASP), obtained from secondary sources and validated through primary interviews.
- CAGR estimation was performed by analyzing industry penetration rates and demand-supply dynamics across verticals and deployment functions.
- Data sanity checks were conducted by reviewing the revenues of over 35 key providers via annual reports, press releases, and public filings, with each company’s revenue weighted according to its data center accelerator portfolio.
- All estimates were cross-verified with key industry stakeholders, including CXOs, directors, and operations managers, and further validated by MarketsandMarkets domain experts.
Data Center Accelerator Market: Top-Down and Bottom-Up Approach
Data Triangulation
After arriving at the overall market size by the market size estimation process explained in the earlier section, the overall data center accelerator market has been divided into several segments and subsegments. The data triangulation and market breakdown procedures have been used to complete the overall market engineering process and arrive at the exact statistics for all segments, wherever applicable. The data was triangulated by studying various factors and trends from the perspectives of demand and supply. Along with data triangulation and market breakdown, the market has been validated by top-down and bottom-up approaches.
Market Definition
Data center accelerators are specialized hardware modules that enhance CPUs, offering higher throughput, lower latency, and improved energy efficiency for AI training and inference, HPC, analytics, and infrastructure offload. Key types include GPUs, CPUs, FPGAs, and ASICs. The market is evaluated across data center types, functions, processor types, verticals, and regions. The forecasts are supported by vendor strategies, hardware-software integration, performance-per-watt improvements, and supply chain factors. Growth is due to the AI adoption, rising data volumes, and demand for scalable, low-latency computing, with opportunities in hybrid deployments and energy-efficient designs. Leading players include NVIDIA Corporation (US), Advanced Micro Devices, Inc. (US), Intel Corporation (US), Alphabet, Inc. (US), and Amazon Web Services, Inc. (US).
Key Stakeholders
- NGOs, Government Agencies, and Regulatory Bodies
- Investment Banks, Venture Capitalists, and Private Equity Firms
- Data Center Accelerator Manufacturers / Hardware Providers
- Original Equipment Manufacturers (OEMs)
- System Integrators
- Software Developers and AI/ML Platform Providers
- Data Center Operators and Colocation Service Providers
- Cloud Service Providers
- Value-Added Service Providers (VASPs)
- End Users (Enterprises & Organizations)
Report Objectives
- To define, describe, segment, and forecast the data center accelerator market, by processor type, function, type, and vertical, in terms of value
- To forecast the market, by processor type, in terms of volume
- To describe and forecast the market for various segments, with respect to four main regions: North America, Europe, Asia Pacific, and the Rest of the World (RoW), along with their respective countries, in terms of value
- To provide detailed information regarding drivers, restraints, opportunities, and challenges influencing the growth of the data center accelerator market
- To provide a detailed overview of the data center accelerator market’s supply chain, along with the ecosystem, technology trends, use cases, regulatory environment, Porter’s five forces analysis, the impact of Gen AI/AI, and the impact of the 2025 US tariff
- To analyze industry trends, pricing data, patents, and trade data (export and import data) related to the data center accelerators
- To strategically analyze the micromarkets1 with respect to individual growth trends, prospects, and contributions to the total market
- To strategically profile the key players and comprehensively analyze their market share and core competencies
- To analyze opportunities for stakeholders and provide a detailed competitive landscape of the market
- To analyze competitive developments, such as product launches/developments, collaborations, partnerships, acquisitions, and research & development (R&D) activities, in the data center accelerator market
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