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AI Accelerator Market Value Analysis: What Growth Is Expected Over The Forecast Period?
The AI accelerator market has witnessed substantial growth in recent years. It is forecast to expand from $20.91 billion in 2025 to $26.41 billion in 2026, demonstrating a compound annual growth rate (CAGR) of 26.3%. This historical expansion can be attributed to the increasing volume of AI workloads, the inherent limitations of general purpose processors, the widespread adoption of cloud computing, the emergence of deep learning models, and the growing demand for faster inference.
The AI accelerator market size is projected to experience substantial expansion over the upcoming years. By 2030, this market is anticipated to reach a valuation of $68.38 billion, exhibiting a compound annual growth rate (CAGR) of 26.9%. This projected growth during the forecast timeframe is attributable to several factors, including the rising integration of AI across various sectors, the expansion of edge computing, the need for energy-efficient AI hardware, the proliferation of hyperscale data centers, and advancements in semiconductor design. Key trends anticipated during the same period encompass the development of edge AI accelerators, the creation of customized AI chips, processing of AI with greater energy efficiency, cloud-based AI acceleration solutions, and the incorporation of AI accelerators within data centers.
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AI Accelerator Market Expansion Supported By Key Demand Factors
The expanded use of IoT devices is projected to boost the AI accelerator market’s growth in the future. These IoT devices are physical items equipped with sensors, software, and internet connectivity, allowing them to gather, share, and process data online. The surge in IoT device deployment stems from factors like the rising need for automation, better connectivity, and increased consumer acceptance of smart technologies. AI accelerators allow IoT devices to process data on-site, minimizing reliance on cloud data transfer. This leads to quicker decisions, reduced latency, and less bandwidth usage, thereby improving efficiency in real-time applications such as smart homes, industrial automation, and healthcare. For example, a report released in April 2024 by Ericsson, a Sweden-based telecommunications company, stated that global IoT connections totaled 15.7 billion connections in 2023, with a projected increase of 16% to 38.8 billion connections by 2029. Consequently, the wider adoption of IoT devices is fueling the expansion of the AI accelerator market.
AI Accelerator Market Segment Landscape: Which Areas Lead Market Development?
The AI accelerator market covered in this report is segmented –
1) By Type: Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), Application-Specific Integrated Circuits (ASICs), Central Processing Units (CPUs), Field-Programmable Gate Arrays (FPGAs)
2) By Technology: Cloud-Based AI Accelerators, Edge AI Accelerators
3) By End User: Information Technology And Telecom, Healthcare, Automotive, Finance, Retails, Other End Users
Subsegments:
1) By Graphics Processing Units (GPUs): AI Training GPUs, AI Inference GPUs, Cloud-Based AI GPUs, Edge AI GPUs, High-Performance Computing (HPC) GPUs
2) By Tensor Processing Units (TPUs): Cloud TPUs, Edge TPUs, AI Model Training TPUs, AI Model Inference TPUs, Energy-Efficient TPUs
3) By Application-Specific Integrated Circuits (ASICs): Deep Learning ASICs, Speech And Language Processing ASICs, Computer Vision ASICs, Edge AI ASICs, Low-Power AI ASICs
4) By Central Processing Units (CPUs): AI-Optimized Multi-Core CPUs, Cloud AI CPUs, Edge AI CPUs, Real-Time AI Processing CPUs, High-Performance AI Workstation CPUs
5) By Field-Programmable Gate Arrays (FPGAs): AI Model Customization FPGAs, Low-Latency AI Processing FPGAs, Edge AI FPGAs, Reconfigurable AI Hardware FPGAs, High-Throughput AI Computing FPGAs
AI Accelerator Market Industry Trends: What Changes Are Reshaping Demand?
Companies actively involved in the AI accelerator market are concentrating on developing sophisticated technologies, including 5 nm node process technology, to boost performance, enhance energy efficiency, and cater to the growing requirements of AI workloads. This 5 nm node process technology describes a semiconductor fabrication method where transistors measure merely 5 nanometers, leading to superior performance, lower power consumption, and more compact chip designs. An illustrative example occurred in August 2024, when IBM, a technology company based in the US, introduced the Spyre accelerator chip. This advanced AI processing unit was specifically engineered for IBM Z systems. The chip features 32 cores and 25.6 billion transistors, and it leverages 5nm node process technology to achieve both high performance and impressive energy efficiency. It is designed to be mounted on PCIe cards, which can be clustered to significantly increase processing power. This setup enables large-scale AI inferencing and supports intricate applications like fraud detection and generative AI, used for automating business processes and updating code. The architecture of the Spyre accelerator is optimized for managing AI workloads, thereby allowing businesses to securely and efficiently deploy AI models within their own premises.
AI Accelerator Market Industry Leaders And Market Competition
Major companies operating in the AI accelerator market are Samsung Electronics Co. Ltd., Huawei Technologies Co. Ltd., Taiwan Semiconductor Manufacturing Company, Intel Corporation, Cisco Systems Inc., Qualcomm Technologies Inc., Broadcom Inc., NVIDIA Corporation, Advanced Micro Devices Inc. (AMD), Baidu Inc., NXP Semiconductors N.V., Microchip Technology Incorporated, Synopsys Inc., Marvell Technology Inc., Arista Networks Inc., Xilinx Inc., Hailo Ltd., Rebellions.ai, Furiosa AI Inc., Graphcore Limited, BrainChip Holdings Ltd., LeapMind Inc.
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AI Accelerator Market Regional Outlook: Where Are The Largest Opportunities Located?
North America was the largest region in the AI accelerator market in 2025. The regions covered in the AI accelerator market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.