Edge AI Hardware Market with COVID-19 Impact Analysis device, Processor (CPU, GPU, and ASICs), End User, Function (Training and Inference), Power (Less Than 1W, 1-3 W, 3-5 W, 5-10W and more than 10W) and Region - Global Forecast to 2026
[236 Pages Report] The edge AI hardware market is projected to grow from 920 million units in 2021 to 2,080 million units by 2026; it is expected to grow at a CAGR of 17.7% from 2021 to 2026. The key factors contributing to the growth of the market include growth in demand for low latency and real-time processing on edge devices, emergence of AI coprocessors for edge computing, reduction in data storage and operations cost, Increase in enterprise workloads on the cloud and rapid growth in the number of intelligent applications.
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COVID-19 Impact on the Global Edge AI Hardware Market
As the world braces for the continued impact of the COVID-19 pandemic, every industry has been affected. To mitigate pandemic risks, organizations around the world are taking adequate measures such as remote working capabilities, remote asset maintenance and monitoring, plant automation, and telehealth. A high positive impact has been witnessed in the healthcare vertical, as firms have started realizing the potential of Edge AI Hardware in combating the impact of COVID-19. This has led to increased funding and research to keep businesses safe and secure across the value chain. It is expected that the market will witness slow growth during the pandemic and bounce back with a higher adoption rate across verticals post-pandemic. Organizations worldwide have been using digital infrastructure to continue their usual business activities as it serves as essential infrastructure. Healthcare, the public sector, and education verticals are adopting digitalization at an unprecedented rate. Several clouds and edge companies are offering their computational services for free to the frontline workers to reduce the impact of COVID-19.
Edge AI Hardware Market Dynamics
Driver: Growth in demand for low latency and real-time processing on edge devices
In edge AI, machine learning algorithms use device-generated data and process the data in the device. This reduces latency and leads to real-time, automated decision-making. Applications that require real-time data processing will benefit from the fact that edge AI allows real-time operations such as data generation, learning, and inference. Autonomous vehicles (AVs) have very little time between sensing a possible collision and making an adjustment regarding steering and braking. A large amount of data gathered from an IoT device is transmitted to the cloud, where machine learning (ML) models run and transmit the processed data back to the device, which can lead to a delay in response. On-device AI reduces sharing of data resulting in a faster response. In addition, it may not be feasible to store a large amount of data in the cloud.
Restraint: Limited on-device training
Currently, machine learning models available for edge AI are pre-trained and used for inference. Pre-trained models are offered to users, and the model fine-tunes itself based on the users data. Training a model consumes a lot of computational power, and edge AI is more likely to suffer from uncertainty and randomness as it has limited access to training data.
On-device learning has its own advantages:
- No need to send data to servers, which may lead to data privacy and security risks.
- The model will always be updated related to learning
Opportunity:Dedicated AI processors for on-device image analytics
AI mobile processors support computational imaging applications in drones, wearable electronics, robots, surveillance cameras, and autonomous vehicles. The application of AI-based vision processing units (VPU) can help drones make better decisions and reduce the risk of accidents, which will add to the rising demand for drones for industrial and personal use. Computational imaging and visual awareness applications are enhancing mobile devices by replacing complex optics with simplified lens assemblies and multiple apertures; combining images captured by heterogeneous sensors; including RGB (red, green, blue), infrared (IR), and depth sensors; and extracting contextual metadata from still images and video streams. These factors enable the use of VPUs for a broad range of new application areas and use cases (previously limited to desktops and workstations) in mobile handsets, tablets, wearable devices, and personal robots. VPU-enabled surveillance cameras help real-time data processing in cameras only, rather than in the cloud, which reduces the chances of data hacking and enables faster processing.
Challenge: Power consumption and size constraint
Edge AI devices such as smartphones, cameras, drones, and robots are being introduced in the market with on-device intelligence. However, in the long run, edge AI has to overcome challenges such as power consumption and device size. Cloud-based AI offers advantages such as easier implementation, integration, and scaling and shifts the cost burden from capital to operational expenditure. Cloud-based AI also has the advantage of storing data centrally and off-premise. The size of a neural network is directly proportional to the demand for power, and an increase in size will lead to higher power consumption. The optimization of power consumption with the help of software for deep neural network models is a challenge. There is a need to focus on the joint design of algorithms and hardware to achieve high-performance and power-efficient on-device AI.
The market for wearables in edge AI hardware market could grow at the highest CAGR during the forecast period
The wearables segment could witness fast growth during the forecast period. This high growth rate could be attributed to the augmentation of features among wearables. Wearables are becoming smarter, and the inclusion of AI and edge computing could further enhance their capabilities.
The market for consumer electronics is estimated to account for the largest share during the forecast period in market
The consumer electronics segment holds a major share in terms of volume. This is due to the rising consumer spending and demand for consumer electronics. The demand for smartphones, smart wearables, and other devices is witnessing strong growth. Moreover, the innovation and development of new use cases for edge AI could lead to the high growth of consumer electronics in the edge AI hardware market.
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Key Market Players
The major players in the edge AI hardware market are Intel (US), Apple (US), Huawei (China), MediaTek (Taiwan), Samsung Electronics (South Korea), and Qualcomm Technologies (US)
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|
Report Metric |
Scope |
|
Market size available for years |
20172026 |
|
Base year considered |
2020 |
|
Forecast period |
20212026 |
|
Forecast units |
Value (USD Billion), and Volume (Units) |
|
Segments covered |
By Device, End User, Function, Processor, Power Consumption, and Region |
|
Geographies covered |
North America, Europe, Asia Pacific, and Rest of World |
|
Companies covered |
The major players in the edge AI hardware market are Apple (US), Intel (US), NVIDIA (US), Qualcomm Technologies (US), Huawei Technologies (China), Samsung Electronics (South Korea), IBM (US), Micron Technology (US), Xilinx (US), Google (US), Microsoft (US) and AMD (US). |
The study categorizes the edge AI hardware market based on by device, end user, function, processor, power consumption, regional and global level.
By Device
- Smartphones
- Robots
- Surveillance cameras
- Wearables
- Smart speakers
- Automotive
- Edge servers
- Smart mirrors
By End User
- Smart home
- Consumer electronics
- Automotive & transportation
- Aerospace & defense
- Industrial
- Government
- Healthcare
- Construction
By Function
- Training
- Inference
By Processor
- CPU
- GPU
- ASICs
By Power Consumption
- Less than 1W,
- 1-3 W,
- 3-5 W,
- 5-10W
- More than 10W
By Region
- North America
- Europe
- Asia Pacific
- Rest of World
Recent Developments
- In April 2021, Intel announced the launch of its 3rd Gen Intel Xeon Scalable processor that would deliver a balanced architecture with built-in artificial intelligence, crypto acceleration, and advanced security capabilities.
- In November 2020, Hyundai Motor (South Korea) partnered with NVIDIA to use NVIDIA DRIVE infotainment and AI platforms for its future Hyundai, Kia, and Genesis models.
- In April 2019, Qualcomm announced work with Vivo (China), Tencent (China) Honor of Kings, and Tencent AI Lab to drive and explore new gaming experiences of on-device AI applications utilizing the 4th Generation Qualcomm Artificial Intelligence (AI) Engine. Dubbed Project Imagination, this joint effort utilized the AI expertise of the four parties.
- In February arch 2020, Huawei announced the launch of 5G foldable tablets (HUAWEI MatePad Pro 5G, HUAWEI WiFi AX3 and HUAWEI 5G CPE Pro 2) and supporting software platform in the marketplace.
- In January 2021, Samsung Electronics announced a partnership with an eco-friendly shopping mall, Green Pea, in Italy. The company would promote its smart home appliances and consumer electronic products in the mall.
Frequently Asked Questions (FAQ):
What is the current size of the global edge AI hardware market?
The edge AI hardware market is projected to grow from 920 million units in 2021 to 2,080 million units by 2026; it is expected to grow at a CAGR of 17.7% from 2021 to 2026. The key factors contributing to the growth of the market include growth in demand for low latency and real-time processing on edge devices, emergence of AI coprocessors for edge computing, reduction in data storage and operations cost, Increase in enterprise workloads on the cloud and rapid growth in the number of intelligent applications.
Who are the winners in the global edge AI hardware market?
Intel (US), Apple (US), Huawei (China), MediaTek (Taiwan), Samsung Electronics (South Korea), and Qualcomm Technologies (US)
What is the COVID-19 impact on edge AI hardware providers?
The key manufacturers in edge AI hardware, including Intel (US), Apple (US), Huawei (China), MediaTek (Taiwan), Samsung Electronics (South Korea), and Qualcomm Technologies (US)have been impacted severely during the first and second quarters of 2020 owing to the outbreak and spread of COVID-19 .
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TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 25)
1.1 OBJECTIVES OF THE STUDY
1.2 DEFINITION
1.3 STUDY SCOPE
1.3.1 INCLUSIONS & EXCLUSIONS
1.4 MARKETS COVERED
FIGURE 1 EDGE AI HARDWARE MARKET SEGMENTATION
1.4.1 YEARS CONSIDERED FOR THE STUDY
1.5 CURRENCY
1.6 LIMITATIONS
1.7 STAKEHOLDERS
1.8 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY (Page No. - 29)
2.1 RESEARCH DATA
FIGURE 2 MARKET: RESEARCH DESIGN
2.1.1 SECONDARY & PRIMARY RESEARCH
2.1.2 SECONDARY DATA
2.1.2.1 Key data from secondary sources
2.1.2.2 Secondary sources
2.1.3 PRIMARY DATA
2.1.3.1 Key data from primary sources
2.1.3.2 Breakdown of primary interviews
2.1.3.3 Primary sources
2.2 MARKET SIZE ESTIMATION
2.2.1 BOTTOM-UP APPROACH
2.2.1.1 Demand-side analysis
FIGURE 3 MARKET SIZE ESTIMATION: BOTTOM-UP APPROACH
2.2.2 EDGE AI HARDWARE MARKET SIZE ESTIMATION: DEMAND-SIDE ANALYSIS
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY: DEMAND-SIDE ANALYSIS
2.2.3 TOP-DOWN APPROACH
2.2.3.1 Supply-side analysis
FIGURE 5 MARKET SIZE ESTIMATION: TOP-DOWN APPROACH
2.3 DATA TRIANGULATION
FIGURE 6 DATA TRIANGULATION
2.4 RESEARCH ASSUMPTIONS
2.5 RISK ASSESSMENT
TABLE 1 ANALYSIS OF RISK FACTORS
3 EXECUTIVE SUMMARY (Page No. - 41)
3.1 POST-COVID-19: REALISTIC SCENARIO
3.2 POST-COVID-19: OPTIMISTIC SCENARIO
3.3 POST-COVID-19: PESSIMISTIC SCENARIO
FIGURE 7 PRE- AND POST-COVID-19 SCENARIO ANALYSIS FOR THE EDGE AI HARDWARE MARKET, 20172026
FIGURE 8 SMARTPHONES SEGMENT TO HOLD THE LARGEST MARKET SIZE IN 2026
FIGURE 9 HEALTHCARE SEGMENT TO GROW AT THE HIGHEST CAGR FROM 2021 TO 2026
FIGURE 10 TRAINING SEGMENT TO GROW AT A HIGHER CAGR FROM 2021 TO 2026
FIGURE 11 NORTH AMERICA HELD THE LARGEST SHARE OF MARKET IN 2020, IN TERMS OF VOLUME
4 PREMIUM INSIGHTS (Page No. - 46)
4.1 BRIEF OVERVIEW OF MARKET
FIGURE 12 MARKET TO WITNESS LUCRATIVE GROWTH OPPORTUNITIES FROM 2021 TO 2026
4.2 MARKET, BY DEVICE
FIGURE 13 SMARTPHONES TO HOLD THE LARGEST SHARE IN MARKET
4.3 MARKET, BY END USER
FIGURE 14 CONSUMER ELECTRONICS TO HAVE THE LARGEST SHARE BY END USER DURING 2021−2026
4.4 MARKET, BY FUNCTION
FIGURE 15 INFERENCE FUNCTION PROJECTED TO HOLD A LARGER SHARE OF THE MARKET IN 2026
4.5 GEOGRAPHICAL SNAPSHOT OF MARKET, 20212026
FIGURE 16 MEXICO TO GROW AT THE HIGHEST RATE FROM 2021 TO 2026 IN NORTH AMERICA
5 MARKET OVERVIEW (Page No. - 49)
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
FIGURE 17 GROWTH IN DEMAND FOR LOW LATENCY AND REAL-TIME PROCESSING DRIVES THE EDGE AI HARDWARE MARKET
5.2.1 DRIVERS
5.2.1.1 Growth in demand for low latency and real-time processing on edge devices
5.2.1.2 Emergence of AI coprocessors for edge computing
5.2.1.3 Reduction in data storage and operations cost
5.2.1.4 Increase in enterprise workloads on the cloud
5.2.1.5 Rapid growth in the number of intelligent applications
FIGURE 18 IMPACT ANALYSIS: DRIVERS
5.2.2 RESTRAINTS
5.2.2.1 Limited on-device training
5.2.2.2 Limited number of AI experts
FIGURE 19 IMPACT ANALYSIS: RESTRAINTS
5.2.3 OPPORTUNITIES
5.2.3.1 Dedicated AI processors for on-device image analytics
5.2.3.2 Growth in demand for edge computing in IoT
5.2.3.3 Emergence of the 5G network to bring IT and telecom together
FIGURE 20 IMPACT ANALYSIS: OPPORTUNITIES
5.2.4 CHALLENGES
5.2.4.1 Power consumption and size constraint
5.2.4.2 Optimization of edge AI standards
FIGURE 21 IMPACT ANALYSIS: CHALLENGES
5.3 EVOLUTION
FIGURE 22 EVOLUTION OF EDGE AI
5.4 EDGE AI MARKET ECOSYSTEM
FIGURE 23 ECOSYSTEM OF EDGE AI
TABLE 2 MARKET ECOSYSTEM, BY KEY PLAYER
5.5 EDGE AI HARDWARE MARKET: COVID-19 IMPACT
5.6 CASE STUDY ANALYSIS
5.6.1 USE CASE 1: CREATING MOTION INTELLIGENCE WITH IMAGIMOBS SENSORBEAT AI SOLUTION
5.6.2 USE CASE 2: USING IMAGIMOBS SENSORBEAT AI SOFTWARE FOR PREDICTIVE MAINTENANCE IN MANUFACTURING
5.6.3 USE CASE 3: USING ANAGOG JEDAI 4.0 TO PERSONALIZE BANKING EXPERIENCE
5.6.4 USE CASE 4: USING HIGH-PERFORMANCE EMBEDDED COMPUTING (HPEC) SYSTEMS OF EUROTECH FOR AUTONOMOUS DRIVING
5.6.5 USE CASE 5: USING EDGE AI STARTER KIT OF BYTELAKE FOR THE DETECTION OF GROCERIES IN RETAIL
5.6.6 USE CASE 6: USING EDGE AI STARTER KIT OF BYTELAKE FOR TRAFFIC ANALYTICS USING VIDEO SURVEILLANCE
5.7 VALUE CHAIN ANALYSIS
FIGURE 24 VALUE CHAIN ANALYSIS
5.8 PRICING ANALYSIS
FIGURE 25 PRICING ANALYSIS
5.9 TECHNOLOGY ANALYSIS
5.9.1 EDGE AI AND INTERNET OF THINGS (IOT)
5.9.2 EDGE AI AND 5G
5.9.3 EDGE AI AND BLOCKCHAIN
5.10 PORTERS FIVE FORCES ANALYSIS
FIGURE 26 PORTERS FIVE FORCES ANALYSIS
TABLE 3 IMPACT OF PORTERS FIVE FORCES ON THE MARKET, 2020
5.10.1 THREAT OF NEW ENTRANTS
5.10.2 THREAT OF SUBSTITUTES
5.10.3 BARGAINING POWER OF SUPPLIERS
5.10.4 BARGAINING POWER OF BUYERS
5.10.5 INTENSITY OF COMPETITIVE RIVALRY
5.11 PATENT ANALYSIS
FIGURE 27 PATENT ANALYSIS
TABLE 4 NOTICEABLE EDGE AI HARDWARE-RELATED PATENTS
5.11.1 INNOVATION AND PATENT REGISTRATIONS
TABLE 5 IMPORTANT INNOVATION AND PATENT REGISTRATIONS, 20192020
5.12 TARIFF AND REGULATORY LANDSCAPE
5.12.1 INTRODUCTION
5.12.2 GENERAL DATA PROTECTION REGULATION
5.12.3 HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT
5.12.4 FEDERAL TRADE COMMISSION
5.12.5 FEDERAL COMMUNICATIONS COMMISSION
5.12.6 ISO/IEC JTC 1/SC 42
5.13 REVENUE SHIFT AND NEW REVENUE POCKETS FOR THE EDGE AI HARDWARE MARKET
FIGURE 28 REVENUE SHIFT IN MARKET
5.14 TRADE ANALYSIS
TABLE 6 IMPORT DATA OF UNITS FOR ELECTRICAL APPARATUS FOR SWITCHING OR PROTECTING ELECTRICAL CIRCUITS, BY COUNTRY, 20172020 (USD MILLION)
TABLE 7 EXPORT DATA OF UNITS FOR ELECTRICAL APPARATUS FOR SWITCHING OR PROTECTING ELECTRICAL CIRCUITS, BY COUNTRY, 20172020 (USD MILLION)
6 EDGE AI HARDWARE MARKET, BY DEVICE (Page No. - 75)
6.1 INTRODUCTION
FIGURE 29 WEARABLES EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 8 MARKET, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 9 MARKET, BY DEVICE, 20212026 (THOUSAND UNITS)
TABLE 10 MARKET, BY DEVICE, 20172020 (USD MILLION)
TABLE 11 MARKET, BY DEVICE, 20212026 (USD MILLION)
6.2 SMARTPHONES
6.2.1 SMARTPHONES TO DOMINATE THE MARKET DURING THE FORECAST PERIOD
TABLE 12 MARKET FOR SMARTPHONES, BY REGION, 20172020 (MILLION UNITS)
TABLE 13 MARKET FOR SMARTPHONES, BY REGION, 20212026 (MILLION UNITS)
6.3 SURVEILLANCE CAMERAS
6.3.1 PUBLIC SAFETY TO BE A MAJOR APPLICATION OF AI-BASED CAMERAS
TABLE 14 MARKET FOR SURVEILLANCE CAMERAS, BY END USER, 20172026 (THOUSAND UNITS)
TABLE 15 MARKET FOR SURVEILLANCE CAMERAS, BY END USER, 20212026 (THOUSAND UNITS)
TABLE 16 MARKET FOR SURVEILLANCE CAMERAS, BY REGION, 20172020 (MILLION UNITS)
FIGURE 30 ASIA PACIFIC IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 17 MARKET FOR SURVEILLANCE CAMERAS, BY REGION, 20212026 (MILLION UNITS)
6.4 ROBOTS
6.4.1 ROBOTICS IS ONE OF THE FASTEST-GROWING MARKETS FOR EDGE AI HARDWARE
TABLE 18 MARKET FOR DRONES, BY END USER, 20172020 (THOUSAND UNITS)
TABLE 19 EDGE AI HARDWARE MARKET FOR DRONES, BY END USER, 20212026 (THOUSAND UNITS)
TABLE 20 MARKET FOR ROBOTS, BY REGION, 20172020 (THOUSAND UNITS)
TABLE 21 MARKET FOR ROBOTS, BY REGION, 20212026 (THOUSAND UNITS)
6.5 WEARABLES
6.5.1 EYEWEAR EXPECTED TO BE A MAJOR MARKET FOR EDGE AI HARDWARE IN WEARABLES
TABLE 22 MARKET FOR WEARABLES, BY END USER, 20172020 (THOUSAND UNITS)
TABLE 23 MARKET FOR WEARABLES, BY END USER, 20212026 (THOUSAND UNITS)
TABLE 24 MARKET FOR WEARABLES, BY REGION, 20172020 (THOUSAND UNITS)
FIGURE 31 NORTH AMERICA TO DOMINATE THE MARKET DURING THE FORECAST PERIOD
TABLE 25 MARKET FOR WEARABLES, BY REGION, 20212026 (THOUSAND UNITS)
6.6 EDGE SERVERS
6.6.1 EDGE AI SERVERS HAVE SIGNIFICANT GROWTH OPPORTUNITIES IN ENTERPRISE AND INDUSTRIAL SECTOR
TABLE 26 MARKET FOR EDGE SERVERS, BY REGION, 20172020 (THOUSAND UNITS)
TABLE 27 MARKET FOR EDGE SERVERS, BY REGION, 20212026 (THOUSAND UNITS)
6.7 SMART SPEAKERS
6.7.1 SMART SPEAKERS ARE NOW USED TO CONTROL SMART HOME PRODUCTS
TABLE 28 MARKET FOR SMART SPEAKERS, BY REGION, 20172020 (MILLION UNITS)
TABLE 29 MARKET FOR SMART SPEAKERS, BY REGION, 20212026 (MILLION UNITS)
6.8 AUTOMOTIVE
6.8.1 SEMI-AUTONOMOUS AND AUTONOMOUS VEHICLES TO DRIVE THE MARKET FOR AUTOMOTIVE
TABLE 30 MARKET FOR AUTOMOTIVE, BY REGION, 20172020 (THOUSAND UNITS)
TABLE 31 MARKET FOR AUTOMOTIVE, BY REGION, 20212026 (THOUSAND UNITS)
6.9 SMART MIRRORS
6.9.1 RETAIL TO BE A MAJOR INDUSTRY FOR SMART MIRRORS
TABLE 32 MARKET FOR SMART MIRRORS, BY REGION, 20172020 (THOUSAND UNITS)
TABLE 33 EDGE AI HARDWARE MARKET FOR SMART MIRRORS, BY REGION, 20212026 (THOUSAND UNITS)
7 EDGE AI HARDWARE MARKET, BY POWER CONSUMPTION (Page No. - 91)
7.1 INTRODUCTION
FIGURE 32 DEVICES WITH LESS THAN 1W EXPECTED TO ACCOUNT FOR THE FASTEST GROWTH DURING THE FORECAST PERIOD
TABLE 34 MARKET, BY POWER CONSUMPTION, 20172020 (MILLION UNITS)
TABLE 35 MARKET, BY POWER CONSUMPTION, 20212026 (MILLION UNITS)
7.2 LESS THAN 1W
7.2.1 WEARABLES EXPECTED TO BE THE MAJOR CONTRIBUTORS TO THE MARKET FOR LESS THAN 1W OF POWER CONSUMPTION
7.3 13W
7.3.1 SMARTPHONES TO DOMINATE THE EDGE AI HARDWARE MARKET FOR 13W
7.4 35W
7.4.1 SMART SPEAKERS EXPECTED TO LEAD THE MARKET FOR 35W
7.5 510W
7.5.1 SURVEILLANCE CAMERAS AND DRONES EXPECTED TO BE MAJOR CONTRIBUTORS TO MARKET FOR 510W
7.6 MORE THAN 10W
7.6.1 AUTOMOTIVE EXPECTED TO GROW AT THE HIGHEST RATE IN MARKET FOR 510W
8 EDGE AI HARDWARE MARKET, BY PROCESSOR (Page No. - 95)
8.1 INTRODUCTION
FIGURE 33 MARKET FOR GPU TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 36 MARKET, BY PROCESSOR, 20172020 (MILLION UNITS)
TABLE 37 MARKET, BY PROCESSOR, 20212026 (MILLION UNITS)
8.2 CPU
8.2.1 CPU TO HOLD THE LARGEST SHARE OF MARKET FOR PROCESSORS
8.3 GPU
8.3.1 AUTOMOTIVE AND ROBOTICS TO BE MAJOR MARKETS FOR GPU
8.4 ASIC
8.4.1 CPU TO BE REPLACED BY ASIC FOR AI-BASED APPLICATIONS
8.5 OTHERS
9 EDGE AI HARDWARE MARKET, BY FUNCTION (Page No. - 99)
9.1 INTRODUCTION
FIGURE 34 INFERENCE TO HOLD A LARGER SHARE IN THE MARKET DURING THE FORECAST PERIOD
TABLE 38 MARKET, BY FUNCTION, 20172020 (MILLION UNITS)
TABLE 39 MARKET, BY FUNCTION, 20212026 (MILLION UNITS)
9.2 TRAINING
9.2.1 TRAINING IS MOSTLY DONE ON THE CLOUD
9.3 INFERENCE
9.3.1 DEVELOPMENT OF EFFICIENT PROCESSORS TO DRIVE THE EDGE INFERENCE MARKET
10 EDGE AI HARDWARE MARKET, BY END USER (Page No. - 102)
10.1 INTRODUCTION
TABLE 40 MARKET, BY END USER, 20172020 (THOUSAND UNITS)
FIGURE 35 CONSUMER ELECTRONICS TO HOLD THE LARGEST SHARE OF THE MARKET DURING THE FORECAST PERIOD
TABLE 41 MARKET, BY END USER, 20212026 (THOUSAND UNITS)
10.2 CONSUMER ELECTRONICS
10.2.1 SMARTPHONES ARE MAJOR CONTRIBUTORS TO THE MARKET IN CONSUMER ELECTRONICS
TABLE 42 MARKET FOR CONSUMER ELECTRONICS, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 43 MARKET FOR CONSUMER ELECTRONICS, BY DEVICE, 20212026 (THOUSAND UNITS)
10.2.2 SMARTPHONES
10.2.3 WEARABLES
10.2.4 ENTERTAINMENT ROBOTS
10.3 SMART HOME
10.3.1 SMART SPEAKERS ARE MAJOR CONTRIBUTORS OF EDGE AI HARDWARE IN SMART HOMES
TABLE 44 EDGE AI HARDWARE MARKET FOR SMART HOME, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 45 MARKET FOR SMART HOME, BY DEVICE, 20212026 (THOUSAND UNITS)
10.3.2 SMART SPEAKERS
10.3.3 SMART CAMERAS
10.3.4 DOMESTIC ROBOTS
10.4 AUTOMOTIVE & TRANSPORTATION
10.4.1 VEHICLE NUMBER PLATE RECOGNITION, VEHICLE COUNT, AND VEHICLE RECOGNITION TO BE MAJOR APPLICATIONS OF CAMERAS IN AUTOMOTIVE
TABLE 46 MARKET FOR AUTOMOTIVE & TRANSPORTATION, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 47 MARKET FOR AUTOMOTIVE & TRANSPORTATION, BY DEVICE, 20212026 (THOUSAND UNITS)
10.4.2 AUTOMOTIVE
10.4.3 SURVEILLANCE CAMERAS
10.4.4 LOGISTICS ROBOTS
10.5 GOVERNMENT
10.5.1 SURVEILLANCE CAMERAS TO BE THE MAJOR CONTRIBUTORS OF EDGE AI HARDWARE IN GOVERNMENTS
TABLE 48 EDGE AI HARDWARE MARKET FOR GOVERNMENTS, BY DEVICE, 20172020 (THOUSAND UNITS)
FIGURE 36 SURVEILLANCE CAMERAS TO HOLD A LARGER SHARE IN THE MARKET DURING THE FORECAST PERIOD
TABLE 49 MARKET FOR GOVERNMENTS, BY DEVICE, 20212026 (THOUSAND UNITS)
10.5.2 SURVEILLANCE CAMERAS
10.5.3 DRONES
10.6 HEALTHCARE
10.6.1 WEARABLES TO DOMINATE THE MARKET IN HEALTHCARE
TABLE 50 MARKET FOR HEALTHCARE, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 51 MARKET FOR HEALTHCARE, BY DEVICE, 20212026 (THOUSAND UNITS)
10.6.2 MEDICAL ROBOTS
10.6.3 WEARABLES
10.7 INDUSTRIAL
10.7.1 MACHINE VISION EXPECTED TO DRIVE THE EDGE AI HARDWARE MARKET IN THE INDUSTRIAL SECTOR
TABLE 52 MARKET FOR INDUSTRIAL, BY DEVICE, 20172020 (THOUSAND UNITS)
FIGURE 37 INDUSTRIAL ROBOTS TO GROW AT THE HIGHEST RATE IN MARKET DURING THE FORECAST PERIOD
TABLE 53 MARKET FOR INDUSTRIAL, BY DEVICE, 20212026 (THOUSAND UNITS)
10.7.2 INDUSTRIAL ROBOTS
10.7.3 DRONES
10.7.4 CAMERAS
10.8 AEROSPACE & DEFENSE
10.8.1 SERVICE ROBOTS TO DRIVE THE MARKET IN THE AEROSPACE INDUSTRY
TABLE 54 MARKET FOR AEROSPACE & DEFENSE, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 55 MARKET FOR AEROSPACE & DEFENSE, BY DEVICE, 20212026 (THOUSAND UNITS)
10.9 CONSTRUCTION
10.9.1 DRONES TO DRIVE THE MARKET IN THE CONSTRUCTION INDUSTRY
TABLE 56 MARKET FOR CONSTRUCTION, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 57 MARKET FOR CONSTRUCTION, BY DEVICE, 20212026 (THOUSAND UNITS)
10.9.2 SERVICE ROBOTS
10.9.3 DRONES
10.10 OTHERS
TABLE 58 EDGE AI HARDWARE MARKET FOR OTHER END USERS, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 59 MARKET FOR OTHER END USERS, BY DEVICE, 20212026 (THOUSAND UNITS)
10.10.1 SURVEILLANCE CAMERAS
10.10.2 ROBOTS
10.10.3 WEARABLES
10.10.4 SMART MIRRORS
11 GEOGRAPHIC ANALYSIS (Page No. - 118)
11.1 INTRODUCTION
FIGURE 38 MARKET, BY GEOGRAPHY
TABLE 60 MARKET, BY REGION, 20172020 (MILLION UNITS)
TABLE 61 MARKET, BY REGION, 20212026 (MILLION UNITS)
11.2 NORTH AMERICA
FIGURE 39 SNAPSHOT OF THE MARKET IN NORTH AMERICA
TABLE 62 NORTH AMERICA: MARKET, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 63 NORTH AMERICA: MARKET, BY DEVICE, 20212026 (THOUSAND UNITS)
TABLE 64 NORTH AMERICA: MARKET, BY COUNTRY, 20172020 (MILLION UNITS)
TABLE 65 NORTH AMERICA: MARKET, BY COUNTRY, 20212026 (MILLION UNITS)
11.2.1 US
11.2.1.1 US to drive the edge AI hardware market in North America
11.2.2 CANADA
11.2.2.1 Canada holds significant opportunities for edge AI hardware in North America
11.2.3 MEXICO
11.2.3.1 Mexico to Exhibit the Fastest Growth in Edge AI hardware in North America
11.3 EUROPE
FIGURE 40 SNAPSHOT OF THE MARKET IN EUROPE
TABLE 66 EUROPE: MARKET, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 67 EUROPE: MARKET, BY DEVICE, 20212026 (THOUSAND UNITS)
TABLE 68 EUROPE: MARKET, BY COUNTRY, 20172020 (MILLION UNITS)
TABLE 69 EUROPE: MARKET, BY COUNTRY, 20212026 (MILLION UNITS)
11.3.1 GERMANY
11.3.1.1 Germany is one of the fastest-growing markets for edge AI hardware in Europe
11.3.2 UK
11.3.2.1 The UK to dominate the edge AI hardware market in Europe
11.3.3 FRANCE
11.3.3.1 Growing demand for surveillance to drive market in France
11.3.4 REST OF EUROPE (ROE)
11.4 ASIA PACIFIC (APAC)
FIGURE 41 SNAPSHOT OF THE MARKET IN APAC
TABLE 70 APAC: MARKET, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 71 APAC: MARKET, BY DEVICE, 20212026 (THOUSAND UNITS)
TABLE 72 APAC: MARKET, BY COUNTRY, 20172020 (MILLION UNITS)
TABLE 73 APAC: MARKET, BY COUNTRY, 20212026 (MILLION UNITS)
11.4.1 CHINA
11.4.1.1 AI-based surveillance to drive the market in China
11.4.2 JAPAN
11.4.2.1 Robotics to drive the edge AI hardware market in Japan
11.4.3 SOUTH KOREA
11.4.3.1 Government initiatives to drive the market in Japan
11.4.4 REST OF APAC
11.5 REST OF THE WORLD (ROW)
TABLE 74 ROW: MARKET, BY DEVICE, 20172020 (THOUSAND UNITS)
TABLE 75 ROW: MARKET, BY DEVICE, 20212026 (THOUSAND UNITS)
TABLE 76 ROW: MARKET, BY REGION, 20172020 (MILLION UNITS)
TABLE 77 ROW: MARKET, BY REGION, 20212026 (MILLION UNITS)
11.5.1 MIDDLE EAST & AFRICA (MEA)
11.5.1.1 Saudi Arabia, Israel, and South Africa are expected to be the major contributors to the edge AI hardware market in MEA
11.5.2 SOUTH AMERICA
11.5.2.1 South America to account for a larger share of the market in RoW
12 COMPETITIVE LANDSCAPE (Page No. - 135)
12.1 INTRODUCTION
TABLE 78 COMPANIES ADOPTED PRODUCT LAUNCHES AND DEVELOPMENTS AS KEY GROWTH STRATEGIES FROM 2019 TO 2021
12.2 MARKET SHARE ANALYSIS, 2020
nbsp; TABLE 79 EDGE AI HARDWARE MARKET: DEGREE OF COMPETITION
FIGURE 42 MARKET SHARE OF KEY COMPANIES IN THE MARKET, 2020
12.2.1 MARKET SHARE BY DEVICE TYPE
TABLE 80 MARKET SHARE FOR SMARTPHONES
TABLE 81 MARKET SHARE FOR CAMERAS
TABLE 82 MARKET SHARE FOR ROBOTS
TABLE 83 MARKET SHARE FOR WEARABLES
TABLE 84 MARKET SHARE FOR SMART SPEAKERS
TABLE 85 MARKET SHARE FOR SMART MIRRORS
TABLE 86 MARKET SHARE FOR PROCESSOR VENDORS FOR PASSENGER VEHICLES
TABLE 87 EDGE AI HARDWARE MARKET: MARKET SHARE FOR PROCESSOR VENDORS FOR CAMERA
12.3 REVENUE ANALYSIS
FIGURE 43 5-YEAR REVENUE ANALYSIS FOR KEY COMPANIES, 20162020 (USD BILLION)
12.4 COMPETITIVE LEADERSHIP MAPPING
12.4.1 STARS
12.4.2 PERVASIVE PLAYERS
12.4.3 EMERGING LEADERS
12.4.4 PARTICIPANTS
FIGURE 44 MARKET (KEY PLAYERS): COMPETITIVE LEADERSHIP MAPPING, 2020
12.5 SME EVALUATION QUADRANT
12.5.1 PROGRESSIVE COMPANIES
12.5.2 RESPONSIVE COMPANIES
12.5.3 DYNAMIC COMPANIES
12.5.4 STARTING BLOCKS
FIGURE 45 EDGE AI HARDWARE MARKET (SME) EVALUATION QUADRANT, 2020
TABLE 88 COMPANY FOOTPRINT
TABLE 89 PRODUCT FOOTPRINT OF COMPANIES
TABLE 90 END-USER FOOTPRINT OF COMPANIES
TABLE 91 REGIONAL FOOTPRINT OF COMPANIES
12.6 COMPETITIVE SITUATIONS AND TRENDS
12.6.1 PRODUCT LAUNCHES
TABLE 92 MARKET: PRODUCT LAUNCHES, JANUARY 2019MARCH 2021
12.6.2 DEALS
13 COMPANY PROFILES (Page No. - 166)
(Business Overview, Products/Solutions/Services offered, Recent Developments, and MnM View (Key strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats))*
13.1 INTRODUCTION
13.2 KEY PLAYERS
13.2.1 INTEL
TABLE 93 INTEL: BUSINESS OVERVIEW
FIGURE 46 INTEL: COMPANY SNAPSHOT
13.2.2 NVIDIA
TABLE 94 NVIDIA: BUSINESS OVERVIEW
FIGURE 47 NVIDIA: COMPANY SNAPSHOT
13.2.3 QUALCOMM TECHNOLOGIES
TABLE 95 QUALCOMM: BUSINESS OVERVIEW
FIGURE 48 QUALCOMM TECHNOLOGIES: COMPANY SNAPSHOT
13.2.4 HUAWEI TECHNOLOGIES CO., LTD.
TABLE 96 HUAWEI TECHNOLOGIES CO., LTD.: BUSINESS OVERVIEW
FIGURE 49 HUAWEI TECHNOLOGIES CO., LTD.: COMPANY SNAPSHOT
13.2.5 SAMSUNG ELECTRONICS
TABLE 97 SAMSUNG ELECTRONICS: BUSINESS OVERVIEW
FIGURE 50 SAMSUNG ELECTRONICS: COMPANY SNAPSHOT
13.2.6 IBM
TABLE 98 IBM: BUSINESS OVERVIEW
FIGURE 51 IBM: COMPANY SNAPSHOT
13.2.7 MICRON TECHNOLOGY
TABLE 99 MICRON TECHNOLOGY: BUSINESS OVERVIEW
FIGURE 52 MICRON TECHNOLOGY: COMPANY SNAPSHOT
13.2.8 XILINX
TABLE 100 XILINX: BUSINESS OVERVIEW
FIGURE 53 XILINX: COMPANY SNAPSHOT
13.2.9 AMD
TABLE 101 AMD: BUSINESS OVERVIEW
FIGURE 54 AMD: COMPANY SNAPSHOT
13.2.10 GOOGLE
TABLE 102 GOOGLE: BUSINESS OVERVIEW
FIGURE 55 GOOGLE: COMPANY SNAPSHOT
13.2.11 MICROSOFT
TABLE 103 MICROSOFT: BUSINESS OVERVIEW
FIGURE 56 MICROSOFT: COMPANY SNAPSHOT
13.3 OTHER PLAYERS
13.3.1 IMAGINATION TECHNOLOGIES
13.3.2 CAMBRICON TECHNOLOGIES
13.3.3 TENSTORRENT
13.3.4 BLAIZE
13.3.5 GENERAL VISION
13.3.6 MYTHIC
13.3.7 ADAPTEVA INC.
13.3.8 MEDIATEK
13.3.9 APPLIED BRAIN RESEARCH
13.3.10 HORIZON ROBOTICS
13.3.11 CEVA
13.3.12 GRAPHCORE
13.3.13 SAMBANOVA
13.3.14 HALIO
13.3.15 VERIDIFY SECURITY INC.
*Details on Business Overview, Products/Solutions/Services offered, Recent Developments, and MnM View (Key strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats) might not be captured in case of unlisted companies.
14 APPENDIX (Page No. - 229)
14.1 INSIGHTS OF INDUSTRY EXPERTS
14.2 DISCUSSION GUIDE
14.3 KNOWLEDGE STORE: MARKETSANDMARKETS SUBSCRIPTION PORTAL
14.4 AVAILABLE CUSTOMIZATIONS
14.5 RELATED REPORTS
14.6 AUTHOR DETAILS
The research study involved 4 major activities in estimating the size of the edge AI hardware market. Exhaustive secondary research has been done to collect significant information on the edge AI hardware, peer market, and parent market. The validation of these findings, assumptions, and sizing with industry experts across the value chain through primary research has been the next step. Both top-down and bottom-up approaches have been employed to estimate the global market size. Post which the market breakdown and data triangulation have been used to estimate the market sizes of segments and sub-segments.
Secondary Research
The secondary sources referred for this research study includes International Federation for Robotics (IFR), LF Edge, Project Linux Foundation, Institute of Electrical and Electronics Engineers, European Telecommunications Standards Institute (ETSI), European Association for Artificial Intelligence, Internet of Things Association, and Edge AI hardware Standards Association.
In the edge AI hardware market report, the top-down, as well as the bottom-up approaches, have been used for the estimation and validation of the size of the edge AI hardware market, along with several other dependent submarkets. The major players in the edge AI hardware market were identified using extensive secondary research and their presence using primary and secondary research. All the percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.
Primary Research
Extensive primary research has been conducted after understanding and analyzing the edge AI hardware market scenario through secondary research. Several primary interviews have been conducted with key opinion leaders from both demand- and supply-side vendors across 4 major regions North America, Europe, Asia Pacific (APAC), and the Rest of the World (South America, Middle East, and Africa). Approximately 25% of the primary interviews have been conducted with the demand side and 75% with the supply side. These primary data have been collected mainly through telephonic interviews, which consist of 80% of the total primary interviews; questionnaires and emails have also been used to collect the data.
After successful interaction with industry experts, brief sessions were conducted with highly experienced independent consultants to reinforce the findings from our primaries. This, along with the in-house subject matter experts opinions, has led us to the findings as described in the remainder of this report.
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
In the complete market engineering process, both top-down and bottom-up approaches have been implemented, along with several data triangulation methods, to estimate and validate the size of the edge AI hardware market, as well as that of various other dependent submarkets. The research methodology used to estimate the market sizes includes the following:
The bottom-up approach has been employed to arrive at the overall size of the edge AI hardware market, in terms of value and volume, by identifying edge AI hardware available in the market and their average selling price. Multiplication of the number of units of edge AI hardware shipped and the average selling price of each edge AI hardware led to the estimation of the overall size of the market.
Market Size Estimation Methodology-Bottom-up approach
To know about the assumptions considered for the study, Request for Free Sample Report
Data Triangulation
After arriving at the overall market size from the estimation process explained above, the overall edge AI hardware market has been split into several segments and sub-segments. To complete the overall market engineering process and arrive at the exact statistics for all segments and sub-segments, the data triangulation and market breakdown procedures have been employed, wherever applicable. The data has been triangulated by studying various factors and trends from both the demand and supply sides. Along with this, the edge AI hardware market has been validated using both top-down and bottom-up approaches.
The main objectives of this study are as follows:
- To describe and forecast the edge artificial intelligence (AI) hardware market, in terms of value, by processor, power consumption, device, and end user
- To describe and forecast the edge artificial Intelligence (AI) market, in terms of volume,
by device, power consumption, processor, and end user - To describe and forecast the edge AI hardware market, in terms of value, by region
North America, Europe, Asia Pacific (APAC), and the Rest of the World (RoW) - To describe and forecast the edge AI hardware market, in terms of volume, by region
North America, Europe, Asia Pacific (APAC), and the Rest of the World (RoW) - To provide detailed information regarding the major factors influencing the market growth (drivers, restraints, opportunities, and challenges)
- To strategically analyze the micromarkets1 with respect to individual growth trends, prospects, and contribution to the overall edge AI hardware market
- To profile key players and comprehensively analyze their market positions in terms of ranking and core competencies2 along with detailing the competitive landscape for the market leaders
- To analyze the competitive developments such as joint ventures, mergers and acquisitions, product developments, and ongoing research and development (R&D) in the edge AI hardware market
- To provide an illustrative segmentation, analysis, and projection of the main regional markets
Available Customizations:
With the given market data, MarketsandMarkets offers customizations according to the specific requirements of companies. The following customization options are available for the report:
Company Information
- Detailed analysis and profiling of additional market players (up to 5)
- Country-level market analysis for the Middle East, Africa, and South America
Get in-depth analysis of the COVID-19 impact on the Edge AI Hardware Market
Benchmarking the rapid strategy shifts of the Top 100 companies in the Edge AI Hardware Market
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- Triangulate with your Own Data
- Get Data as per your Format and Definition
- Gain a Deeper Dive on a Specific Application, Geography, Customer or Competitor
- Any level of Personalization
- What are the Known and Unknown Adjacencies Impacting the Edge AI Hardware Market
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- Who will be your Top Customer; what will make them switch?
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Growth opportunities and latent adjacency in Edge AI Hardware Market