Edge AI Hardware Market to Reach USD 6.90 Billion by 2032, Driven By Advancements in AI and Edge Computing
The Edge AI Hardware Market is expanding with demand for real-time processing in IoT, automation, and smart devices, driven by advancements in AI and edge computing.
Austin, Feb. 13, 2025 (GLOBE NEWSWIRE) -- Edge AI Hardware Market Size & Growth Insights:
According to the SNS Insider, 'The Edge AI Hardware Market is expected to rise from USD 1.27 billion in 2023 to USD 6.90 billion by 2032, growing at a CAGR of 20.7% from 2024 to 2032.'
The Edge AI hardware market has witnessed substantial growth in a constant escalation in artificial intelligence technology and the demand for real-time data processing continues to take place at the edge. For instance, due to the increasing demand for low-latency, high-performance computing solutions, companies are heavily investing in edge AI hardware to facilitate IoT applications, including autonomous vehicles, smart cities, and industrial automation. Moreover, the rollout of 5G is leading to more widespread adoption of edge AI hardware because faster data transmission speeds and lower latency are important for many edge AI applications. Consequently, the global edge AI hardware market is forecasted to increase significantly in the forthcoming years as companies strive to utilize artificial intelligence near the data source. The growing demands in this market are being supposed by the leading market players providing cutting-edge solutions which include NVIDIA, Intel, Qualcomm, Huawei, IBM.
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Leading Market Players with their Product Listed in this Report are:
NVIDIA Corporation (Graphics Processing Units, AI Accelerators)
Google (Alphabet Inc.) (Edge TPU, Google Cloud AI)
Intel Corporation (Xeon Processors, Movidius AI Chips)
Huawei Technologies Co., Ltd. (Ascend AI Processors, Kirin Chips)
Apple Inc. (A-Series Chips, Neural Engine)
Qualcomm Incorporated (Snapdragon Processors, AI Engine)
Samsung Electronics Co., Ltd. (Exynos Chips, AI Hardware)
IBM Corporation (Power AI, IBM Edge Computing Solutions)
Dell Technologies Inc. (Edge Computing Servers, VxRail Systems)
Microsoft Corporation (Azure AI, Azure Percept)
ARM (Cortex-A Processors, AI Edge Processors)
Hailo (Hailo-8 AI Processor)
MediaTek Inc. (Dimensity AI Chips)
Xilinx Inc. (Versal AI Acceleration, FPGAs)
Micron Technology (Memory and Storage Solutions for AI).
Edge AI Hardware Market Report Scope:
Report Attributes
Details
Market Size in 2023
USD 2.78 Billion
Market Size by 2032
USD 14.62 Billion
CAGR
CAGR of 20.25% From 2024 to 2032
Report Scope & Coverage
Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segmentation
• By Processor(CPU, GPU, FPGA ,ASICs)• By Devices(Smartphones, Cameras, Robots, Wearables, Smart Speaker, Other Devices)• By End Use Industry(Government, Real Estate, Consumer Electronics, Automotive, Transportation, Healthcare, Manufacturing, Others)
Key Drivers
• Incredible Growth of Edge AI Hardware Market Driven by Low-Latency Demand in Virtual Reality.
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By Processor, CPU Dominating and GPU Fastest Growing
In 2023, the CPU segment led the Edge AI Hardware market, accounting for 54% of the revenue, driven to the fact that CPUs offer a level of flexibility and generalization that is desirable for many different applications ranging from smartphones to industrial IoT devices. CPUs play a crucial role in data processing and algorithm execution, which allows edge AI systems to efficiently process complex workloads.
The GPU segment is the fastest growing over the forecast period over the forecast period 2024-2032 due to its capability for parallel processing, making it ideal for data-intensive tasks like deep learning and image processing. As AI, models grow in size and data demands, GPUs are becoming essential for training and inference, particularly for applications that require low latency and real-time decision-making, such as robots, autonomous vehicles, and cameras, thus driving their adoption in edge AI systems.
By Device, Camera Dominating and Smartphone Fastest Growing
In 2023, the camera segment holds the largest share of the Edge AI hardware market at 35%, driven by its critical role in applications like CCTV, ADAS, and robotics where visual data processing requires instant results. The advent of AI-enabled imaging at the edge through AI image recognition/object recognition has led to the rise of cameras on edge AI hardware for further smart decision-making and situational awareness.
The smartphone segment is the fastest growing, projected to expand significantly from 2024 to 2032. The expansion stems from the fact that smartphones are increasingly incorporating AI capabilities like Face ID, AR features, and voice assistants. The AI-enabled mobile chips and mobile processors enable smartphones to run AI tasks on the device itself and not rely on cloud computing.
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Market Dominance and Growth Projections in the Edge AI Hardware Market: Asia-Pacific and North America
The Asia-Pacific region is expected to dominate the Edge AI hardware market, accounting for 43% of the market share in 2023. The reason is the increasing pace of technological advancements in countries such as China, Japan, South Korea, and India, which has made heavy investments in AI, robots, and IoT. China's heavy investment in edge computing infrastructure and AI chip fabrication play a large role in the global AI ecosystem. Add this to the region's broad application of AI in the healthcare, automotive, and industrial sectors, and growth becomes on double speed.
North America is projected to see the fastest growth from 2024 to 2032, as innovations arise from the USA (the home of the best chip manufacturers, including NVIDIA, Intel, and Google) as well as the high deployment of AI in the automotive and enterprise solutions.
Table of Contents - Major Points
1. Introduction
2. Executive Summary
3. Research Methodology
4. Market Dynamics Impact Analysis
5. Statistical Insights and Trends Reporting
5.1 Customer Adoption and Use Cases
5.2 Supply Chain Data
5.3 Power Consumption and Efficiency Metrics
6. Competitive Landscape
7. Edge AI Hardware Market Segmentation, by Processor
8. Edge AI Hardware Market Segmentation, by Device
9. Edge AI Hardware Market Segmentation, by End Use Industry
10. Regional Analysis
11. Company Profiles
12. Use Cases and Best Practices
13. Conclusion
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