In recent years, Edge AI hardware market dynamics have been drastically revamped by the surging requirements for energy-efficient and distributed artificial intelligence (AI) computing. Edge AI is the implementation of AI algorithms on devices located near data sources, lowering latency and increasing real-time decision capacities. This paradigm shift has boosted the drive to develop hardware designed especially for edge computing's unique needs.
The edge AI hardware market is being driven by the huge growth in the number of Internet of Things (IoT) devices. With the number of connected devices skyrocketing, a growing amount of is needed to process this large volume of data at the edge. These devices need edge AI hardware to make on-device artificial inference possible, and this can provide faster response times and less reliance on cloud-based processing.
The need for privacy and security in AI applications is also another factor influencing market dynamics. With edge AI hardware, data can be processed directly on the device. This decreases the risk of exposing sensitive data by transferring it to the cloud for processing. It is especially important in applications like healthcare, finance and smart homes, where data privacy is paramount. For this reason, more and more people want the AI hardware to provide strong performance at the edge but still guarantee data integrity and security.
The competitive landscape of the Edge AI hardware market is marked by a wave of innovation and a variety of solutions, all striving to win customers. Traditional semiconductor manufacturers and newcomers alike are trying to design processors and accelerators suited for each type of edge computing workload. These hardware solutions, designed to cope with the edge environments' unique power and space constraints, are equipped to meet these challenges.
Furthermore, the market dynamics are also driven by the increasing adoption of Edge AI in various industry verticals. From manufacturing and retail to healthcare and transportation, organizations are adopting edge computing abilities to drive operational efficiency and improve decision-making procedures. This widespread adoption across industries is driving the demand for hardware solutions that can deliver high performance, energy efficiency, and scalability in diverse edge environments.
Report Attribute/Metric | Details |
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Segment Outlook | Component, Device, Vertical |
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.
Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review
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.
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.
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.
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.
Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review
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.
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.
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.
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.
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