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AI Accelerator Market Size Outlook: How Quickly Will Revenue Expand Through 2030?
The AI accelerator market has experienced remarkable expansion in recent years. This market is expected to increase from $20.91 billion in 2025 to $26.41 billion in 2026, exhibiting a compound annual growth rate (CAGR) of 26.3%. The historical growth of the market was driven by factors such as the rise in AI workloads, the constraints of general-purpose processors, the growth of cloud computing, the development of deep learning models, and the need for quicker inference.
The AI accelerator market is anticipated to see substantial expansion in the upcoming years. It is projected to increase to $68.38 billion in 2030, exhibiting a compound annual growth rate (CAGR) of 26.9%. This growth throughout the forecast period can be attributed to heightened AI adoption across various industries, the development of edge computing, the demand for low power AI hardware, the expansion of hyperscale data centers, and advancements in semiconductor design. Significant trends expected during the forecast period include the rise of edge AI accelerators, the innovation of custom AI chips, energy-efficient AI processing, cloud-based AI acceleration, and the integration of AI accelerators into data centers.
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AI Accelerator Market Growth Backed By Core Demand Fundamentals
The future expansion of the AI accelerator market is anticipated to be significantly driven by the increasing deployment of IoT devices. These IoT devices are defined as physical items equipped with sensors, software, and connectivity capabilities, allowing them to gather, share, and process data via the internet. This growing deployment of IoT devices stems from factors like the rising demand for automation, enhanced connectivity, and increased consumer adoption of smart devices. AI accelerators empower IoT devices to handle data processing on-site, thereby minimizing reliance on cloud transmission. This leads to quicker decision-making, reduced latency, and lower bandwidth usage, boosting efficiency in real-time applications across sectors such as smart homes, industrial automation, and healthcare. For example, a report released by Ericsson, a Sweden-based telecommunications firm, in April 2024, stated that global IoT connections totaled 15.7 billion connections in 2023 and are projected to grow by 16% to 38.8 billion connections by 2029. Consequently, the expanding deployment of IoT devices is fueling the growth of the AI accelerator market.
AI Accelerator Market Segments: Where Is Growth Concentrated?
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 Growth Trends Reshaping The Competitive Landscape
Leading firms in the AI accelerator market are prioritizing the development of cutting-edge technologies, such as the 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 manufacturing method where transistors measure only 5 nanometers, leading to better performance, lower power usage, and more compact chip designs. For example, in August 2024, IBM, a US-based technology company, introduced the Spyre accelerator chip, an advanced AI processing unit specifically designed for IBM Z systems. This chip features 32 cores and 25.6 billion transistors, leveraging 5nm node process technology to deliver both superior performance and energy efficiency. It is incorporated into PCIe cards that can be grouped together to amplify processing power, facilitating extensive AI inferencing and supporting intricate applications like fraud detection and generative AI for business process automation and code modernization. Its design is tailored to handle AI workloads, enabling enterprises to implement AI models securely and effectively within their own premises.
AI Accelerator Market Key Participants And Competitive Landscape
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 Geographic Analysis: Where Is Demand Rising Fastest?
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.
