Data Center Accelerator Market: Powering the Next Wave of AI and High-Performance Computing
The global Data Center Accelerator Market has emerged as one of the fastest-growing segments within the broader technology hardware landscape, driven largely by the explosive rise of generative AI, machine learning, and high-performance computing (HPC) workloads. Data center accelerators — specialized hardware components such as GPUs, ASICs, FPGAs, and DPUs/IPUs/SmartNICs — are purpose-built to handle the massive parallel processing and low-latency computation that traditional CPUs simply cannot deliver efficiently. As enterprises, hyperscalers, and cloud service providers race to build out AI-ready infrastructure, demand for these accelerators has surged to unprecedented levels, reshaping how modern data centers are designed and operated.
Market Size and Growth Trajectory
The global data center accelerator market size was valued at USD 29.38 billion in 2025, according to Fortune Business Insights. The market is projected to grow from USD 37.92 billion in 2026 to USD 249.10 billion by 2034, exhibiting a compound annual growth rate (CAGR) of 26.53% during the forecast period, according to Fortune Business Insights. This remarkable growth trajectory underscores just how central accelerated computing has become to the digital economy, as organizations across industries shift workloads toward AI training, inference, and complex data analytics.
Asia Pacific dominated the market with a share of 41.37% in 2025, according to Fortune Business Insights, cementing its position as the epicenter of global data center accelerator demand, largely fueled by aggressive investments in AI infrastructure and hyperscale facilities across the region.
What Is Driving the Market?
Rising Demand for Generative AI and HPC Applications
The single most influential driver of this market is the surging appetite for generative AI and HPC applications, according to Fortune Business Insights. Large language models, autonomous systems, and advanced image-generation tools require massive parallel processing and low-latency computation — capabilities that conventional CPUs struggle to provide at scale. Simultaneously, HPC workloads in scientific research, simulations, and advanced analytics increasingly depend on accelerators to manage complex calculations efficiently. As enterprises, research institutions, and cloud providers continue adopting these technologies, demand for AI accelerators, GPUs, and other specialized hardware is expected to keep climbing.
Shift Toward AI-Optimized Data Centers
A defining trend reshaping the industry is the pivot toward AI-optimized data center architectures, according to Fortune Business Insights. Traditional data center designs are increasingly inadequate for meeting the intensive memory and computational demands of modern AI models. This has pushed operators to adopt GPUs, custom AI accelerators, and TPUs at scale. These AI-centric designs improve throughput, enhance energy efficiency, and reduce latency, prompting cloud providers and enterprises alike to restructure their infrastructure — integrating specialized hardware, advanced networking, and optimized software stacks to support large-scale training and inference operations.
Restraints: Cost and Power Consumption
Despite the strong growth outlook, the market faces notable headwinds. The high cost and substantial power consumption associated with advanced FPGAs, GPUs, and AI chips represent a significant restraint, according to Fortune Business Insights. These components demand considerable capital investment, making adoption difficult for smaller, cost-sensitive data centers. Rising operational costs — particularly around cooling and electricity — further compound the challenge, especially in regions with strict sustainability regulations or higher energy prices.
Opportunities in Edge and Cloud AI Infrastructure
On the opportunity side, the growing adoption of cloud and edge AI infrastructure presents significant room for expansion, according to Fortune Business Insights. As organizations increasingly shift AI processing to cloud-based platforms while simultaneously deploying edge devices for real-time data handling, demand for both high-performance and low-latency accelerators is rising in tandem. Cloud providers require scalable FPGA, GPU, and ASIC solutions capable of managing complex AI workloads, while edge environments call for compact, energy-efficient hardware — creating diverse opportunities for vendors across both ecosystems.
Market Segmentation Insights
By accelerator type, the GPU segment held the largest market share in 2024, generating USD 6.52 billion in revenue, according to Fortune Business Insights, thanks to its versatility in parallel processing and strong software ecosystem. The GPU segment is projected to account for 69.22% of the market in 2026, according to Fortune Business Insights. Meanwhile, the ASIC segment recorded the highest CAGR of 33.45% in 2024, according to Fortune Business Insights, owing to its efficiency and optimization for specific tasks like AI inference and encryption.
By deployment, the cloud segment dominated with USD 6.92 billion in revenue in 2024 and is expected to contribute 75.12% of global revenue in 2026, according to Fortune Business Insights, driven by its flexibility and scalability for resource-intensive AI workloads. On-premise deployment retains a strong second position, favored by industries like healthcare, finance, and government that prioritize data security and compliance.
By end user, Hyperscalers and Cloud Service Providers (CSPs) led the market with USD 6.49 billion in revenue in 2024 and are projected to hold a 70.02% share in 2026, according to Fortune Business Insights, reflecting massive infrastructure investments by major cloud operators.
Regional Outlook
North America generated USD 8.77 billion in 2025, contributing 29.86% of global revenue, according to Fortune Business Insights, supported by strong AI adoption and hyperscale data center presence in the U.S. Europe accounted for USD 5.72 billion, or 19.48% of the global market, according to Fortune Business Insights, driven by digital transformation initiatives. Asia Pacific led all regions with USD 12.16 billion in 2025, according to Fortune Business Insights, propelled by strong AI infrastructure investment across China, Japan, and India.
Competitive Landscape
The market remains highly competitive, with key players including NVIDIA Corporation, Advanced Micro Devices (AMD), Intel Corporation, Google LLC, Amazon Web Services, and Microsoft Corporation, according to Fortune Business Insights. These companies are focused on developing advanced AI-optimized chips, forming strategic partnerships with cloud providers, and investing heavily in R&D to improve throughput while lowering power consumption.
Conclusion
The data center accelerator market stands at the heart of the AI revolution, transforming how computational infrastructure is built and scaled worldwide. With generative AI, HPC, and edge computing driving relentless demand, the market's trajectory toward USD 249.10 billion by 2034 reflects a fundamental and lasting shift in enterprise computing priorities. While cost and power challenges persist, continuous innovation in chip design and infrastructure efficiency is likely to keep this sector at the forefront of technological transformation for years to come.
What's Driving Japan's Market? Discover the Latest "Bitumen Market" Insights