The Global Edge AI Processor Market size is expected to reach $5.5 billion by 2028, rising at a market growth of 15.3% CAGR during the forecast period.
Edge artificial intelligence (edge AI) is a paradigm for creating AI workflows that range from centralized data centers (the cloud) and devices closer to humans and physical objects outside the cloud (the edge). This is in contrast to the increasingly usual approach of developing and running AI applications exclusively in the cloud, which has been dubbed cloud AI.
It also varies from previous AI development methods, in which AI algorithms were created on desktops and then deployed on desktops or specific hardware for tasks like reading check numbers. The edge is frequently defined as a physical object, like a network gateway, smart router, or intelligent 5G cell tower. A better way to grasp the significance of edge is to understand it as a mechanism to extend cloud-based digital transformation practices to the rest of the world.
Analysis occurs in a fraction of a second, which is vital in time-sensitive scenarios. Considering the machines that make up an industrial assembly line. If a robot on the production line is activated at the incorrect moment or too late, the product may be damaged or travel further down the line unprocessed and undisturbed. If the error goes undetected, the incorrect product could end up on the market or cause damage later in the manufacturing process. When the majority of data processing occurs locally, on the edge, a centralized service or data transport will not constitute a barrier.
Large volumes of data are frequently involved in edge AI use cases. Transferring video image data to a cloud service is not a realistic solution if the user needs to process data from a variety of distinct sources at the same time. In a self-driving automobile, there are hundreds of sensors that constantly monitor elements like the vehicle's position and tire rotation speed. Based on the data collected from the sensors, the driving computer can make the appropriate decisions regarding steering, braking, and throttle use automatically.
The influence of COVID-19 on businesses is altering business paradigms. Every organization is affected by the COVID-19 pandemic. In order to provide a safe working environment, businesses are striving to reconfigure their supply networks. Remote working functionality, remote asset maintenance, and monitoring, plant automation, as well as telehealth are all being implemented by organizations all over the world to reduce pandemic risks. The healthcare business has benefitted immensely from the transition from computers to the cloud to the edge.
Because there is less data on the cloud, there are fewer tendencies for cyber-attacks. Edge frequently operates in a closed network, making information theft more difficult. A network with several devices is also more difficult to pull down. In general, anything that has a security component should be done on the edge. Considering the intelligent safety monitoring systems in a factory, for example. When devices fail to function properly or people move in an area where they are not authorized to, an alarm should sound before an accident occurs.
One of the major features, as well as a driving factor, of edge AI processors, is that it saves a significant amount of money for the company. Edge AI processors are very cost-efficient due to lesser requirements. Because of the scalability of analytics in making key decisions, the edge can save a significant cost for a company. In addition to saving time, the edge can conserve bandwidth by reducing the amount of data that needs to be transferred. This also improves the energy efficiency of the equipment.
Latency issues, privacy concerns, and bandwidth constraints are just a few of the concerns that cloud computing encounters. Chips are now so compact that they can conduct advanced computing functions on Edge-enabled devices natively, making Edge computing a must-have in situations where latency and privacy are critical. When a centralized system, such as the cloud, gets overwhelmed with massive amounts of data, latency issues arise. As a result, real-time business requirements may be challenging to meet with cloud computing.
Based on the Device Type, the Edge AI Processor Market is bifurcated into Consumer Devices and Enterprise Devices. This is due to its advantages, which include energy efficiency. Less data is transmitted to and from the cloud as more data is processed at the edge, resulting in lower data latency and energy consumption. A vast number of companies aim to employ Edge computing solutions for energy efficiency monitoring in the next years.
By the Type, the Edge AI Processor Market segregated into Central Processing Unit (CPU), Graphics Processing Unit (GPU), and Application Specific Integrated Circuit (ASIC). Application-specific integrated circuits allow for the creation of whole mechanisms on a single chip, which is expected to drive application-specific integrated circuits' growth. An application-specific integrated circuits are chips that are modified for a particular use rather than being developed for general usage.
On the basis of End-Use, the Edge AI Processor Market is segmented into Automotive and Transportation, Healthcare, Consumer Electronics, Retail and Ecommerce, Manufacturing, and Others. In terms of volume, consumer electronics dominate the edge AI processor market due to rising technological advancements all over the world. This is due to rising consumer expenditure along with increasing demand for consumer gadgets. Smart wearables, smartphones, and other electronic devices are gaining in popularity.
| Report Attribute | Details |
|---|---|
| Market size value in 2021 | USD 2.1 Billion |
| Market size forecast in 2028 | USD 5.6 Billion |
| Base Year | 2021 |
| Historical Period | 2018 to 2020 |
| Forecast Period | 2022 to 2028 |
| Revenue Growth Rate | CAGR of 15.3% from 2022 to 2028 |
| Number of Pages | 239 |
| Number of Tables | 372 |
| Report coverage | Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Competitive Landscape, Companies Strategic Developments, Company Profiling |
| Segments covered | Device Type, Type, End Use, Region |
| Country scope | US, Canada, Mexico, Germany, UK, France, Russia, Spain, Italy, China, Japan, India, South Korea, Singapore, Malaysia, Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria |
| Growth Drivers |
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| Restraints |
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Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. This is due to a variety of variables, including the greatest production of Edge AI processors in the United States and Canada, as well as a significant consumer base. These reasons are expected to drive significant growth in the regional edge AI processor market in the coming years.
Free Valuable Insights: Global Edge AI Processor Market size to reach USD 5.6 Billion by 2028
The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; Apple, Inc. and Google LLC. are the forerunners in the Edge AI Processor Market. Companies such as Qualcomm, Inc., Intel Corporation and NVIDIA Corporation are some of the key innovators in Edge AI Processor Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Apple, Inc., Samsung Electronics Co., Ltd. (Samsung Group), Mythic, Qualcomm, Inc., Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.), Intel Corporation, Google LLC, NVIDIA Corporation, Arm Limited (Softbank Group Corp.) and Advanced Micro Devices, Inc.
By Device Type
By Type
By End Use
By Geography
The global edge AI processor market size is expected to reach $5.5 billion by 2028.
Enhanced privacy and security are driving the market in coming years, however, Increased latency and high bandwidth usage limited the growth of the market.
Apple, Inc., Samsung Electronics Co., Ltd. (Samsung Group), Mythic, Qualcomm, Inc., Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.), Intel Corporation, Google LLC, NVIDIA Corporation, Arm Limited (Softbank Group Corp.) and Advanced Micro Devices, Inc.
Due to COVID-19 the healthcare business has benefitted immensely from the transition from computers to the cloud to the edge.
The Central Processing Unit (CPU) market is generating high revenue in the Global Edge AI Processor Market by Type in 2021, thereby, achieving a market value of $2.8 billion by 2028.
The North America is the fastest growing region in the Global Edge AI Processor Market by Region in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $2.1 billion by 2028.
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