What are the latest figures on the ai accelerator market’s size and projected CAGR?
The AI accelerator market size has grown exponentially in recent years. It will grow from $16.55 billion in 2024 to $20.95 billion in 2025 at a compound annual growth rate (CAGR) of 26.6%. The growth in the historic period can be attributed to increasing demand for deep learning models, rise in government investments, rise in adoption of AI in image and speech recognition technologies, rise in AI adoption for precision agriculture, and growth in consumer electronics.
The AI accelerator market size is expected to see exponential growth in the next few years. It will grow to $53.23 billion in 2029 at a compound annual growth rate (CAGR) of 26.2%. The growth in the forecast period can be attributed to rising deployment of AI servers, increasing need for real-time data processing, increasing deployment of IoT devices, increasing investments in AI research, and increasing consumer data generation. Major trends in the forecast period include technological advancements, machine learning, cloud-based AI solutions, AI chips, and cybersecurity.
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Which Market drivers have played a significant role in driving the ai accelerator market?
The increasing deployment of IoT devices is expected to propel the growth of the AI accelerator market going forward. IoT devices refer to physical objects embedded with sensors, software, and connectivity features that enable them to collect, exchange, and process data over the internet. The increasing deployment of IoT devices is driven by factors such as the growing demand for automation, improved connectivity, and the rising consumer adoption of smart devices. AI accelerators enable IoT devices to process data locally, reducing the need for cloud transmission, which results in faster decision-making, lower latency, and reduced bandwidth consumption, enhancing efficiency in real-time applications like smart homes, industrial automation, and healthcare. For instance, in April 2024, according to a report published by Ericsson, a Sweden-based telecommunications company, the global IoT connections reached 15.7 billion connections in 2023 and are expected to increase by 16% to 38.8 billion connections by 2029. Therefore, the increased deployment of IoT devices is driving the growth of the AI accelerator market.
What are the key segments within the ai accelerator market?
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
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Which key players are shaping the ai accelerator market?
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.
Which transformative trends will shape the ai accelerator market landscape?
Major companies operating in the AI accelerator market are focusing on developing advanced technologies such as 5 nm node process technology to enhance performance, improve energy efficiency, and support the increasing demands of AI workloads. 5 nm node process technology refers to a semiconductor manufacturing process where the transistors are only 5 nanometers in size, allowing for improved performance, reduced power consumption, and more compact chip designs. For instance, in August 2024, IBM, a US-based technology company, launched the Spyre accelerator chip, an advanced AI processing unit designed for IBM Z systems. It is equipped with 32 cores and 25.6 billion transistors, utilizing 5nm node process technology to deliver both high performance and energy efficiency. This is mounted on PCIe cards that can be clustered together to boost processing power and facilitates large-scale AI inferencing and supports complex applications, such as fraud detection and generative AI for automating business processes and modernizing code. Its architecture is optimized to handle AI workloads, allowing businesses to deploy AI models securely and efficiently on-premises.
How do regional factors impact the ai accelerator market, and which region is the largest contributor?
North America was the largest region in the AI accelerator market in 2024. The regions covered in the AI accelerator market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Does The AI Accelerator Market Report 2025 Offer?
The ai accelerator market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.
AI accelerators refer to specialized hardware or software designed to speed up and optimize artificial intelligence computations. It offers a wide range of uses and benefits for developers, businesses, cloud service providers, and other stakeholders in the AI technology ecosystem.
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