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Edge AI hardware Market Size

ID: MRFR//6365-CR | 128 Pages | Author: Aarti Dhapte| March 2024

Many variables are involved influencing the development and direction of the Edge AI hardware market. The growing number of IoT devices is a major factor driving the expansion of this market. The growing number of connected devices, ranging from smart thermostats to industrial sensors, requires resource-efficient on-device AI processing. This is fueling demand for additional edge hardware capable of running sophisticated algorithms in a power-efficient manner. This burst in IoT adoption represents a key driver of the edge AI hardware market.
What's even more important are the rising needs for low- latency processing. Applications such as autonomous vehicles and augmented reality require hardware which can rapidly perform AI algorithms on the edge. As industries adopt these technologies, the market for Edge AI hardware reacts to this urgent need for computing near where data is generated.
Decentralized computing, another important factor for the Edge AI hardware market. There are also problems with latency and bandwidth constraints, as well as privacy concerns when it comes to cloud-based technology. Edge computing circumvents these problems by processing data locally, eliminating the reliance on distant data centers. The trend towards distributed computing is in harmony with the need for edge-AI hardware capable of delivering stable performance across a wide range of edge environments.
Additionally, the market is being changed by the rising proportion and variety of AI workloads. With the rapid advance of such applications, an increasing variety of workloads and a greater need for specialized hardware architectures are calling out. So hardware manufacturers must come up with new ideas and produce products catering to the needs of various kinds of artificial intelligence applications (like image recognition or natural language processing).

Covered Aspects:

Report Attribute/Metric Details
Market Size Value In 2023 USD  2,686.2 million
Growth Rate 18.20%

Global Edge AI Hardware Market Overview


Edge AI Hardware Market Size was valued at USD 2686.2 million in 2023. The Edge AI Hardware industry is projected to grow from USD 3275.01 million in 2024 to USD 15987.85 million by 2032, exhibiting a compound annual growth rate (CAGR) of 21.92% during the forecast period (2024 - 2032). Edge AI is an algorithm, which can process data locally on a hardware device. This ability makes a device capable of processing data and takes decisions independently without being connected. AI accelerators, which are specialized Edge AI hardware, enhance the capacity for data-intensive deep learning inference on Edge devices, rendering them a desirable option for several compute-intensive tasks. Specialized Edge AI hardware that permits quick deep learning on the device has grown more and more important as the demand for real-time deep learning workloads rises.


Global Edge AI Hardware Market Overview


Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review


Edge AI Hardware Market Trends




  • 5G AND 6G NETWORKS INTEGRATION




The integration of 5G and 6G networks presents significant opportunities for the growth of the Edge AI Hardware Market. With the advent of 5G networks, ultra-fast connectivity and high bandwidth enable the seamless deployment of real-time, low-latency Edge AI applications, expanding the capabilities of AI-enabled intelligent edge devices. As 5G networks continue to expand, the market can expect a proliferation of these devices capable of complex tasks and autonomous decision-making in crowded and device-saturated environments.


Furthermore, the future development of 6G networks, anticipated post-2030, with higher frequency bands promise even faster speeds, increased bandwidth availability, and enhanced network reliability, which are all vital for large-scale Edge AI applications. This creates fertile ground for the growth of the Edge AI hardware market, as demand for powerful and efficient hardware solutions to support these advanced networks and applications will only continue to increase.


Edge AI Hardware Market Segment Insights


Edge AI Hardware Component Insights


Based on Component, the Edge AI Hardware Market is segmented into CPU, GPU, ASIC, and FPGA. CPU would be the majority shareholder in 2022. The market for edge AI hardware is expanding due in large part to the Central Processing Unit (CPU). As edge computing becomes more popular, there is a growing need for strong and capable processors to manage sophisticated AI applications closer to the data generation edge of networks. With the incorporation of specific features and optimizations for AI workloads, modern CPUs are becoming more efficient at tasks like image recognition, natural language processing, and machine learning inference.


Edge AI Hardware Device Insights


Based on device, the Edge AI Hardware Market is segmented into Smartphone, Camera, Robot, Automobile, Smart Speaker, Wearables, Smart Mirror, and Others. The camera held the largest market share in 2022, as these are primary sources for gathering information in the OSINT domain. Cameras with integrated enhanced image processing capabilities are driving the edge AI hardware market. Cameras with embedded AI hardware can analyse photos and videos on-the-spot, enabling in-the-moment object identification, face recognition, and scene comprehension. By minimizing the need for data transmission to cloud servers, this on-device processing reduces latency and addresses privacy issues.


Edge AI Hardware Power Consumption Insights


Based on power consumption, the Edge AI Hardware Market is segmented into 0-5 W, 6-10 W, and More Than 10 W. 0-5 W held the majority share in 2022. The market for edge AI hardware is expanding due in part to the drive toward ultra-low power consumption, particularly in the 0–5W range. Energy efficiency is critical for applications like wearables, portable devices, and Internet of Things sensors, where edge devices functioning in this power envelope are essential. These low-power edge AI solutions are perfect for distant and resource-constrained locations since they allow for continuous operation without the need for periodic battery replacement or recharge.


FIGURE 2: EDGE AI HARDWARE MARKET, BY POWER CONSUMPTION, 2022 VS 2032 (USD MILLION)


EDGE AI HARDWARE MARKET, BY POWER CONSUMPTION, 2022 VS 2032


Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review


Edge AI Hardware Vertical Insights


Based on Vertical, the Edge AI Hardware Market is segmented into consumer electronics, smart home, automotive & transportation, healthcare, aerospace & defense, government, construction, and others. The consumer electronics held the majority share in 2022. The market for edge AI hardware is expanding due to consumer electronics' direct integration of advanced AI capabilities into commonplace products. To improve user experiences, on-device processing using specialized AI technology is used by smartphones, smart TVs, and smart speakers. Edge AI is used for real-time responsiveness in features like speech recognition, picture processing, and personalized suggestions. Manufacturers are actively working to create small, energy-efficient CPUs that are tailored for edge AI applications in response to the growing customer demand for connected and intelligent devices.


Edge AI Hardware Regional Insights


By Region, the study provides market insights into North America, Europe, Asia-Pacific, Middle East and Africa and South America. North America is likely to be the largest contributor to the Edge AI Hardware market. This includes the US, Canada, and Mexico. The regional market share is influenced by the existence of major companies who are always focusing on strategic development, such as mergers, acquisitions, product launches, and partnerships, in order to remain competitive in the market. For example, Synaptics Inc. established a relationship with Edge Impulse in September 2021. Through this agreement, thousands of embedded developers will be able to construct, train, and deploy bespoke models for a wide range of AI applications using Synaptics’ KatanaUltra Low-Power Edge AI Platform in conjunction with the Edge Impulse software development platform.With the Edge Impulse Embedded ML Platform, developers can work more quickly and effectively to produce models that are ready for production. It also makes model optimization, training, and testing in a full MLOps context simple.


Asia Pacific is one of the fastest growing markets for Edge AI Hardware in the world. The introduction of 5G in the area and the rise in IoT-integrated devices are projected to propel the Asia Pacific region to the top of the Edge AI Hardware Market growth chart. It is anticipated that the expanding smartphone penetration in China, Japan, India, and Suth Korea will boost the market adoption of AI hardware. China and Japan are the two biggest markets in the region. The expansion of the edge AI hardware market in the region is being driven by the presence of numerous major suppliers in the automotive, electronics, and semiconductor industries that are making considerable investments in AI technology. According to the number of patents filed, China's edge AI business has experienced explosive growth in invention over the past year for edge computing and hardware solutions, demonstrating the country's fast-paced industrial innovation.


FIGURE 3: EDGE AI HARDWARE MARKET SIZE BY REGION 2022 VS 2032


EDGE AI HARDWARE MARKET SIZE BY REGION 2022 VS 2032


Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review


Further, the major countries studied in the market report are the U.S., Canada, Mexico, Germany, UK, France, Italy, Spain, China, Japan, and India.


Edge AI Hardware Key Market Players & Competitive Insights


The Edge AI Hardware Market is characterized by the presence of many global, regional, and local vendors. The regional market is highly competitive, with all the players continually competing to gain a larger market share. The vendors compete based on reliability, cost, product quality, and aftermarket services. Therefore, vendors must provide cost-effective and efficient products to survive and succeed in a competitive market environment.


The growth of the vendors is dependent on market conditions, government support, and industrial development. Thus, the vendors should focus on expanding their presence and improving their services. According to MRFR analysis, the growth of the Edge AI Hardware Market is dependent on market conditions.


The key vendors in the market are NVIDIA Corporation, Google (Alphabet Inc.), Intel Corporation, Huawei Technologies Co., Ltd., Apple Inc., Qualcomm Incorporated, Samsung Electronics Co., Ltd., IBM Corporation, Dell Technologies Inc., Microsoft Corporation, ARM, Hailo, MediaTek Inc., Xilinx Inc.  and Micron Technology. These players focus on expanding and enhancing their product portfolio and services to remain competitive and increase their customer base. Additionally, these players are focusing on partnerships & collaborations to expand their business and customer base to enhance their market position.


Key Companies in the Edge AI Hardware Market include.



  • NVIDIA Corporation

  • Google (Alphabet Inc.)

  • Intel Corporation

  • Huawei Technologies Co., Ltd.

  • Apple Inc.

  • Qualcomm Incorporated

  • Samsung Electronics Co., Ltd.

  • IBM Corporation

  • Dell Technologies Inc.

  • Microsoft Corporation

  • ARM

  • Hailo

  • MediaTek Inc.

  • Xilinx Inc.

  • Micron Technology

  • Others


Edge AI Hardware Industry Developments




  • October 2024, A new AI hardware platform has now been introduced by NVIDIA, including GPUs and other resources directed to edge computing applications and real-time processing. This development is expected to enhance the capabilities of driverless automobiles, intelligent cities, and industrial automation systems. 



  • July 2024, Intel has launched a new range of AI processors for edge devices; these devices were tailored explicitly for low latency and high throughput scenarios. Edge-based AI applications like autonomous surveillance and robotic systems will likely benefit from these processors. 



  • April 2024, Qualcomm has introduced an Edge AI chipset that works with 5G networks. This chipset works specifically with mobile edge computing and allows Internet of Things devices, automobiles, and applications for real-time data analytics to be much more efficient. 

  • January 2024, Google Cloud launched its aggressively aimed AI accelerator, which is directed towards edge devices and applications. This accelerator aims to allow machine learning applications to function without much reliance on cloud servers, critical in industrial applications and healthcare. 



  • October 2023, As part of its aspirations to further diversify its business, Arm Holdings announced plans to enter the AI chip market. Such a move would allow them to use their strengths in the architectural design of chips to make processors intended for AI workloads. Broadly, the goal is to provide solutions for the shortage of efficient AI hardware.



  • July 2023, Regarding edge applications, Broadcom today showcased a new AI accelerator that provides low energy requirements and high performance. Further boosters for broader segments such as automotive, healthcare, and many other industries would come by bringing AI computation to the edge.



  • In May 2023, Arm introduced a new Cortex-X4 high-performance core, and a GPU called G720. the Cortex-A720 performance cores and Cortex-A520 power-efficiency CPUs, can be paired with GPUs in smartphones, tablets, and PCs. The chipset package, called TCS23, has a mix of hardware and software technologies operating on the sidelines that improve AI performance.



  • April 2023, Qualcomm partnered with a large automotive group to incorporate its Edge AI hardware in future vehicles. This collaboration is expected to improve the capabilities of self-driving cars and the user experience inside the vehicle with advanced AI processing.




  • In March 2023, Intel's Habana Labs has launched second-generation Al processors for training and inferencing. In March 2022, Amphenol Corporation expanded its SURLOK Plus Series to include 8 mm and 10.3 mm right-angle connectors, with a voltage range of 1500 VDC to meet energy storage and high-power connection and transfer requirements.


Edge AI Hardware Market Segmentation:


Edge AI Hardware Component Outlook



  • CPU

  • GPU

  • ASIC

  • FPGA


Edge AI Hardware Device Outlook



  • Smartphone

  • Camera

  • Robot

  • Automobile

  • Smart Speaker

  • Wearables

  • Smart Mirror

  • Others


Edge AI Hardware Power Consumption Outlook



  • 0-5 W

  • 6-10 W

  • More Than 10 W


Edge AI Hardware Process Outlook



  • Training

  • Inference


Edge AI Hardware Vertical Outlook



  • Consumer Electronics

  • Smart Home

  • Automotive & Transportation

  • Healthcare

  • Aerospace & Defense

  • Government

  • Construction

  • Others


Edge AI Hardware Regional Outlook



  • North America

    • US

    • Canada

    • Mexico



  • Europe

    • UK

    • Germany

    • France

    • Italy

    • Spain

    • Rest of Europe



  • Asia-Pacific

    • China

    • Japan

    • India

    • South Korea

    • Rest of Asia-Pacific



  • Middle East & Africa

    • South America



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