Edge Ai Hardware Market

Edge Ai Hardware Market

Edge Artificial intelligence (AI) Hardware Market Forecasts to 2028 - Global Analysis By Device (Smartphones, Surveillance Cameras, Wearables and Other Devices), Power Consumption (Less than 1 W, 1-3 W, 3-5 W, 5-10 W and More Than 10 W), Processor (Central Processing Unit (CPU), Graphics Processing Unit (GPU), Application Specific Integrated Circuit (ASIC) and Other Processors), Function (Inference and Training), Component (Memory, Sensor and Other Components), End User (Consumer Electronics, Smart Home, Automotive & Transportation, Healthcare, Industrial, Aerospace & Defense and Construction) and Geography

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4.3 (61 reviews)
Published: 2023 ID: SMRC22543

This report covers the impact of COVID-19 on this global market

Years Covered


Estimated Year Value (2022)

US $1,056 MN

Projected Year Value (2028)

US $3,281 MN

CAGR (2022 - 2028)


Regions Covered

North America, Europe, Asia Pacific, South America, and Middle East & Africa

Countries Covered

US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa

Largest Market

North America

Highest Growing Market

Asia Pacific

According to Stratistics MRC, the Global Edge AI Hardware Market is accounted for $1,056 million in 2022 and is expected to reach $3,281 million by 2028 growing at a CAGR of 20.8% during the forecast period. Edge AI hardware is a collection of devices and equipment used to process and power AI-based robots and devices. These devices and equipment are used to integrate and improve artificial intelligence device processing by processing data in the device itself. In this process, no cloud computing or cloud systems are required. This ability allows the devices to make their own decisions.

According to Seagate, 44% of the data created in the core and edge will be driven by analytics, artificial intelligence, and deep learning, as well as by an increasing number of IoT devices feeding data to the enterprise edge, where it creates key players in the market with ample opportunities to expand.

Market Dynamics:


Increase in demand for smart homes and smart cities

Smart cities are complex structures that integrate various systems to support the life cycle of a human. These systems include smart healthcare, smart transportation, smart manufacturing, smart buildings, smart energy, and smart farming, to name a few. Smart cities are gradually adopting AI technologies as they become more prevalent across various industries. As smart cities become more common, more people are becoming interested in the concept of a smart home. The use of automated services in people's daily lives is expected to increase as more people move to cities. Smart homes are transitioning from a luxury to a necessity.


Limitations associated with ai edge devices

In edge AI, pre-trained ML models are currently used for inference. These models automatically adjust based on user data and requirements. Training a model requires a significant amount of computer power, and because edge AI has limited access to training data, it is more susceptible to uncertainty and unpredictability. Furthermore, while edge AI can perform small transfer learning tasks, it cannot perform deep learning tasks. Concerns about cloud computing include latency issues, privacy concerns, and bandwidth limitations. Such factors hinder the market growth.


Emergence of 5G networks that integrate it with telecommunications

With the introduction of 5G networks, IT and telecoms are collaborating to deliver new capabilities for high-end apps and reduce network latency. Using virtualization and software-defined networking principles, the 5G network enables the development of data centers at edge modules as well as the implementation of industry-specific networks in a single environment. Autonomous vehicles, industrial automation, surgery, and robotics all require extremely low latency. The emergence of 5g networks across various applications is expected to increase the volume of data transferred to data centers, which increases the need for edge networks.


High costs and security concerns

Edge AI hardware can be costly to develop and manufacture, limiting adoption, particularly for small and medium-sized businesses. To prevent unauthorised access and ensure data privacy, edge AI hardware must be secure, which can be difficult given the complexity of AI systems. However, with ongoing research and development efforts, these issues are expected to be overcome, resulting in continued growth and adoption of Edge AI hardware in a variety of industries.

Covid-19 Impact:

The COVID-19 breakout has had a significant impact on the operations of the production and manufacturing industries, stifling the growth of the edge AI hardware market. Furthermore, the COVID-19 pandemic has had an impact on the electronics industry, as production facilities have been shut down, resulting in an increase in demand for electronics and semiconductor products across industries. It has a significant impact on European manufacturing and Chinese exports, which may stifle market growth.

The Smartphones segment is expected to be the largest during the forecast period

The smartphones segment has the highest revenue share in the edge AI hardware market and is expected to witness largest share during the forecast period due to the increasing demand for smartphones. Edge AI improves smartphone imaging and photography capabilities, as well as power efficiency and security. Until now, most AI-related processing tasks on mobile apps and assistants, such as prediction, detection, pattern matching, and classification, have been performed primarily in the cloud. However, with AI processors built into phones, these AI tasks could be performed directly on the device, even without any connectivity. Such aspects are propelling the segment’s growth.

The Training segment is expected to have the highest CAGR during the forecast period

The Training segment is estimated to witness the highest CAGR over the projection period. The process of developing an algorithm that will be used to infer the output is known as training. Machine learning models are trained to understand a data set and act on new data. Because mobile devices lack high-performance computing capabilities, ML models are trained in the cloud. Furthermore, on-device training will be limited to specific devices such as automotive systems and robots and will not be required for all applications. Given its benefits, on-device training is expected to grow in the coming years.

Region with largest share:

North America had the highest revenue share and is expected to maintain its lead throughout the forecast period due to the increasing number of IoT devices, the growing need for faster processing devices, increased government funding, and the region's strong technical base. The United States is the largest revenue generator for North American players dealing in edge AI hardware. The United States is a key market for AI application processors due to the country's high demand for smartphones, smart home appliances, and advanced products such as IoT devices, wearable electronics, and vehicles with high-security features.

Region with highest CAGR:

Due to the advent of 5G in the region and the increasing number of IoT-incorporated devices, the Asia-Pacific region is expected to experience the highest growth rate in the global edge AI hardware market. The growing smartphone penetration in China, Japan, India, and South Korea is expected to boost AI hardware market adoption. China is the region's largest market, followed by Japan. Moreover, the presence of several significant vendors in the automobile, electronics, and semiconductor industries that are investing heavily in AI technology is driving the growth of the region's edge AI hardware market.

Key players in the market

Some of the key players in Edge AI Hardware market include Alibaba Group Holding Limited, Amazon.com Inc., Apple Inc., Continental AG, Denso Corporation, Google LLC (Alphabet Inc.), Huawei Technologies Co., Ltd, Imagination Technologies, Intel Corporation, International Business Machines Corporation (IBM), KALRAY Corporation, MediaTek Inc., MICROSOFT CORPORATION, NVIDIA CORPORATION, Qualcomm Technologies, Inc., Robert Bosch GmbH Samsung Electronics and Xilinx Inc.

Key Developments:

In November 2022, Network solutions provider Lumen Technologies began expanding its portfolio of Edge Computing Solutions into the Asia-Pacific Region, which will include its Edge Bare Metal pay-as-you-go hardware solution for servers, taking advantage of sites in Singapore and Japan.

In October 2022, Kneron bagged USD 50 million in funding for next-gen AI hardware solutions. The company plans to use the funds to accelerate its research and development to produce next-gen AI inference modules. Kneron anticipates increased adoption of on-device edge AI technology in the future. This involves placing AI computing power onto devices that include hardware rather than within cloud software.

Devices Covered:
• Smartphones
• Surveillance Cameras
• Wearables
• Robots
• Smart Speakers
• Edge Servers
• Smart Mirrors
• Automobiles

Power Consumptions Covered:
• Less than 1 W
• 1-3 W
• 3-5 W
• 5-10 W
• More Than 10 W

Processors Covered:
• Central Processing Unit (CPU)
• Graphics Processing Unit (GPU)
• Application Specific Integrated Circuit (ASIC)
• Other Processors

Functions Covered:
• Inference
• Training

Components Covered:
• Memory
• Sensor
• Other Components

End User Covered:
• Consumer Electronics
• Smart Home
• Automotive & Transportation
• Government
• Healthcare
• Industrial
• Aerospace & Defense
• Construction

Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o Qatar
o South Africa
o Rest of Middle East & Africa

What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2020, 2021, 2022, 2025, and 2028
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements

Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions

3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 End User Analysis
3.7 Emerging Markets
3.8 Impact of Covid-19

4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry

5 Global Edge AI Hardware Market, By Device
5.1 Introduction
5.2 Smartphones
5.3 Surveillance Cameras
5.4 Wearables
5.5 Robots
5.6 Smart Speakers
5.7 Edge Servers
5.8 Smart Mirrors
5.9 Automobiles

6 Global Edge AI Hardware Market, By Power Consumption
6.1 Introduction
6.2 Less than 1 W
6.3 1-3 W
6.4 3-5 W
6.5 5-10 W
6.6 More Than 10 W

7 Global Edge AI Hardware Market, By Processor
7.1 Introduction
7.2 Central Processing Unit (CPU)
7.3 Graphics Processing Unit (GPU)
7.4 Application Specific Integrated Circuit (ASIC)
7.5 Other Processors

8 Global Edge AI Hardware Market, By Function
8.1 Introduction
8.2 Inference
8.3 Training

9 Global Edge AI Hardware Market, By Component
9.1 Introduction
9.2 Memory
9.3 Sensor
9.4 Other Components

10 Global Edge AI Hardware Market, By End User
10.1 Introduction
10.2 Consumer Electronics
10.2.1 Entertainment Robots
10.3 Smart Home
10.3.1 Smart Cameras
10.3.2 Domestic Robots
10.4 Automotive & Transportation
10.4.1 Logistic Robots
10.5 Government
10.5.1 Drones
10.6 Healthcare
10.6.1 Medical Robots
10.7 Industrial
10.7.1 Industrial Robots
10.7.2 MV Cameras
10.8 Aerospace & Defense
10.9 Construction
10.9.1 Service Robots Professional Service Robots

11 Global Edge AI Hardware Market, By Geography
11.1 Introduction
11.2 North America
11.2.1 US
11.2.2 Canada
11.2.3 Mexico
11.3 Europe
11.3.1 Germany
11.3.2 UK
11.3.3 Italy
11.3.4 France
11.3.5 Spain
11.3.6 Rest of Europe
11.4 Asia Pacific
11.4.1 Japan
11.4.2 China
11.4.3 India
11.4.4 Australia
11.4.5 New Zealand
11.4.6 South Korea
11.4.7 Rest of Asia Pacific
11.5 South America
11.5.1 Argentina
11.5.2 Brazil
11.5.3 Chile
11.5.4 Rest of South America
11.6 Middle East & Africa
11.6.1 Saudi Arabia
11.6.2 UAE
11.6.3 Qatar
11.6.4 South Africa
11.6.5 Rest of Middle East & Africa

12 Key Developments
12.1 Agreements, Partnerships, Collaborations and Joint Ventures
12.2 Acquisitions & Mergers
12.3 New Product Launch
12.4 Expansions
12.5 Other Key Strategies

13 Company Profiling
13.1 Alibaba Group Holding Limited
13.2 Amazon.com Inc.
13.3 Apple Inc.
13.4 Continental AG
13.5 Denso Corporation
13.6 Google LLC (Alphabet Inc.)
13.7 Huawei Technologies Co., Ltd
13.8 Imagination Technologies
13.9 Intel Corporation
13.10 International Business Machines Corporation (IBM)
13.11 KALRAY Corporation
13.12 MediaTek Inc.
13.15 Qualcomm Technologies, Inc.
13.16 Robert Bosch GmbH
13.17 Samsung Electronics
13.18 Xilinx Inc

List of Tables
1 Global Edge AI Hardware Market Outlook, By Region (2020-2028) ($MN)
2 Global Edge AI Hardware Market Outlook, By Device (2020-2028) ($MN)
3 Global Edge AI Hardware Market Outlook, By Smartphones (2020-2028) ($MN)
4 Global Edge AI Hardware Market Outlook, By Surveillance Cameras (2020-2028) ($MN)
5 Global Edge AI Hardware Market Outlook, By Wearables (2020-2028) ($MN)
6 Global Edge AI Hardware Market Outlook, By Robots (2020-2028) ($MN)
7 Global Edge AI Hardware Market Outlook, By Smart Speakers (2020-2028) ($MN)
8 Global Edge AI Hardware Market Outlook, By Edge Servers (2020-2028) ($MN)
9 Global Edge AI Hardware Market Outlook, By Smart Mirrors (2020-2028) ($MN)
10 Global Edge AI Hardware Market Outlook, By Automobiles (2020-2028) ($MN)
11 Global Edge AI Hardware Market Outlook, By Power Consumption (2020-2028) ($MN)
12 Global Edge AI Hardware Market Outlook, By Less than 1 W (2020-2028) ($MN)
13 Global Edge AI Hardware Market Outlook, By 1-3 W (2020-2028) ($MN)
14 Global Edge AI Hardware Market Outlook, By 3-5 W (2020-2028) ($MN)
15 Global Edge AI Hardware Market Outlook, By 5-10 W (2020-2028) ($MN)
16 Global Edge AI Hardware Market Outlook, By More Than 10 W (2020-2028) ($MN)
17 Global Edge AI Hardware Market Outlook, By Processor (2020-2028) ($MN)
18 Global Edge AI Hardware Market Outlook, By Central Processing Unit (CPU) (2020-2028) ($MN)
19 Global Edge AI Hardware Market Outlook, By Graphics Processing Unit (GPU) (2020-2028) ($MN)
20 Global Edge AI Hardware Market Outlook, By Application Specific Integrated Circuit (ASIC) (2020-2028) ($MN)
21 Global Edge AI Hardware Market Outlook, By Other Processors (2020-2028) ($MN)
22 Global Edge AI Hardware Market Outlook, By Function (2020-2028) ($MN)
23 Global Edge AI Hardware Market Outlook, By Inference (2020-2028) ($MN)
24 Global Edge AI Hardware Market Outlook, By Training (2020-2028) ($MN)
25 Global Edge AI Hardware Market Outlook, By Component (2020-2028) ($MN)
26 Global Edge AI Hardware Market Outlook, By Memory (2020-2028) ($MN)
27 Global Edge AI Hardware Market Outlook, By Sensor (2020-2028) ($MN)
28 Global Edge AI Hardware Market Outlook, By Other Components (2020-2028) ($MN)
29 Global Edge AI Hardware Market Outlook, By End User (2020-2028) ($MN)
30 Global Edge AI Hardware Market Outlook, By Consumer Electronics (2020-2028) ($MN)
31 Global Edge AI Hardware Market Outlook, By Entertainment Robots (2020-2028) ($MN)
32 Global Edge AI Hardware Market Outlook, By Smart Home (2020-2028) ($MN)
33 Global Edge AI Hardware Market Outlook, By Smart Cameras (2020-2028) ($MN)
34 Global Edge AI Hardware Market Outlook, By Domestic Robots (2020-2028) ($MN)
35 Global Edge AI Hardware Market Outlook, By Automotive & Transportation (2020-2028) ($MN)
36 Global Edge AI Hardware Market Outlook, By Logistic Robots (2020-2028) ($MN)
37 Global Edge AI Hardware Market Outlook, By Government (2020-2028) ($MN)
38 Global Edge AI Hardware Market Outlook, By Drones (2020-2028) ($MN)
39 Global Edge AI Hardware Market Outlook, By Healthcare (2020-2028) ($MN)
40 Global Edge AI Hardware Market Outlook, By Medical Robots (2020-2028) ($MN)
41 Global Edge AI Hardware Market Outlook, By Industrial (2020-2028) ($MN)
42 Global Edge AI Hardware Market Outlook, By Industrial Robots (2020-2028) ($MN)
43 Global Edge AI Hardware Market Outlook, By MV Cameras (2020-2028) ($MN)
44 Global Edge AI Hardware Market Outlook, By Aerospace & Defense (2020-2028) ($MN)
45 Global Edge AI Hardware Market Outlook, By Construction (2020-2028) ($MN)
46 Global Edge AI Hardware Market Outlook, By Service Robots (2020-2028) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.

List of Figures


Research Methodology

We at Stratistics opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.

Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.

Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.

Data Mining

The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.

Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.

Data Analysis

From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:

  • Product Lifecycle Analysis
  • Competitor analysis
  • Risk analysis
  • Porters Analysis
  • PESTEL Analysis
  • SWOT Analysis

The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.

Data Validation

The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.

We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.

The data validation involves the primary research from the industry experts belonging to:

  • Leading Companies
  • Suppliers & Distributors
  • Manufacturers
  • Consumers
  • Industry/Strategic Consultants

Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.

For more details about research methodology, kindly write to us at info@strategymrc.com

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