Edge AI Hardware Market by Component, Device, Power Consumption, Function, End-Use

List of Tables

[191 Pages Report] The Edge AI Hardware Market size was estimated at USD 24.46 billion in 2023 and expected to reach USD 28.13 billion in 2024, at a CAGR 16.75% to reach USD 72.33 billion by 2030.

The edge AI hardware Market encompasses the technologies and devices that facilitate data processing localized at or near the source of data generation. This field focuses on integrating AI capabilities directly into hardware devices such as smartphones, wearables, industrial machines, and sensors, unlike traditional cloud-based AI, which requires data transmission to a central server. The localized data processing by edge AI hardware enables quicker decision-making, enhanced privacy, and reduced latency while minimizing bandwidth use. The expansion of this market is propelled by several factors, including advancements in chip technology and AI algorithms, heightened data privacy concerns, the increasing demand for real-time processing, and the proliferation of IoT and smart devices. However, the market faces challenges such as the high costs associated with developing and implementing edge AI solutions, the complexity in integrating these systems with existing infrastructure, limitations in device capabilities, and a shortage of skilled professionals. Moreover, the proliferation of the Internet of Things (IoT) and automated technologies across various sectors, including healthcare, automotive, and manufacturing, is creating a surge in data points generated at the edge of networks. This expansion necessitates robust edge AI hardware capable of rapid, real-time processing without latency issues, thus opening extensive markets for edge AI hardware applications in these industries.

KEY MARKET STATISTICS
Base Year [2023]	USD 24.46 billion
Estimated Year [2024]	USD 28.13 billion
Forecast Year [2030]	USD 72.33 billion
CAGR (%)	16.75%

Regional Insights

The United States and Canada are pivotal in the Americas, with significant technological developments in processors and sensors that expedite data processing near its source. This advancement facilitates real-time decision-making capabilities crucial for operations that demand rapid responses, such as in the healthcare and automotive sectors, further supported by a consumer base that values privacy and offline functionalities. In Europe, stringent data privacy regulations such as GDPR significantly influence the designs and deployment of edge AI technologies. Nations, including Germany, the United Kingdom, and France, are at the forefront, enhancing local data processing, thus bolstering security and compliance. This integration is driven by a highly privacy-conscious consumer base requiring high-performance and real-time applications. In contrast, the Middle East emphasizes smart city projects, particularly in UAE and Saudi Arabia, while Africa, though still developing, sees localized adoption tailored to needs in mining and agriculture, often hindered by investment and import challenges. Moreover, the Asia-Pacific region demonstrates substantial activity, with China, Japan, and South Korea as significant innovations. China's state-led investments underscore a national strategy prioritizing tech advancements, while Japan and South Korea innovate in robotics and automotive industries. The regional market thrives on robust government support and a culture favoring consumer electronics rich in AI capabilities, aligning well with these nations' manufacturing strengths and consumer demands. Additionally, India is emerging as a significant player with rising interests in edge AI across healthcare, automotive, and consumer electronics, facilitated by increasing investments and an expanding understanding of edge AI capabilities.

Market Insights

Market Dynamics

The market dynamics represent an ever-changing landscape of the Edge AI Hardware Market by providing actionable insights into factors, including supply and demand levels. Accounting for these factors helps design strategies, make investments, and formulate developments to capitalize on future opportunities. In addition, these factors assist in avoiding potential pitfalls related to political, geographical, technical, social, and economic conditions, highlighting consumer behaviors and influencing manufacturing costs and purchasing decisions.

Market Drivers
- Increasing adoption of AI-based robots across the automotive industry
- Growing need for low latency and real-time processing on edge AI devices
- Surge in consumer demand for smart devices

Market Restraints
- Concerns regarding high power consumption with edge AI hardware

Market Opportunities
- Continuous innovations in edge AI hardware that enhance the performance of edge AI devices
- Rising investment in smart city projects with the advent of 5G network globally

Market Challenges
- Complexity in the integration of edge AI hardware

Market Segmentation Analysis
- Component: Advancements in the edge AI memory and processors to ensure real-time data storing operation effectively
- Function: Deployment of inference based AI in IoT devices to reduce delays in data processing and decision-making

Market Disruption Analysis
Porter's Five Forces Analysis
Value Chain & Critical Path Analysis
Pricing Analysis
Technology Analysis
Patent Analysis
Trade Analysis
Regulatory Framework Analysis

FPNV Positioning Matrix

The FPNV positioning matrix is essential in evaluating the market positioning of the vendors in the Edge AI Hardware Market. This matrix offers a comprehensive assessment of vendors, examining critical metrics related to business strategy and product satisfaction. This in-depth assessment empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success, namely Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The market share analysis is a comprehensive tool that provides an insightful and in-depth assessment of the current state of vendors in the Edge AI Hardware Market. By meticulously comparing and analyzing vendor contributions, companies are offered a greater understanding of their performance and the challenges they face when competing for market share. These contributions include overall revenue, customer base, and other vital metrics. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With these illustrative details, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Recent Developments

Intel Unveils New Edge AI Technologies at MWC 2024 to Revolutionize Local Data Processing for Enhanced Speed and Efficiency

Intel introduced its latest edge platform at the Mobile World Congress 2024, with enhancements aimed at expanding the capabilities of edge AI technology. This new platform is set to revolutionize the data processed locally on devices, minimizing latency and ensuring more efficient and rapid processing than centralized data solutions. These technological advancements promise to catalyze innovation across various industries, including healthcare, automotive, and manufacturing, by enabling smarter and faster decision-making at the device level. Additionally, improved edge AI solutions are expected to facilitate the development of new, more responsive applications capable of operating with significant autonomy. [Published On: 2024-02-25]

Avnet and Syntiant Partnered to Advance Edge AI Technology Distribution

Avnet, a global technology solutions provider, has partnered strategically with Syntiant Corp., a notable innovator in edge artificial intelligence solutions. This partnership focuses on distributing advanced AI technology that enables devices to process data locally, enhancing responsiveness and efficiency while minimizing latency and privacy concerns. The partnership aims to leverage Avnet's vast distribution network to broaden the accessibility of Syntiant's ultra-low-power, deep-learning processors across various markets. These processors are designed for edge applications, aligning with the growing demand for smarter, autonomous devices that operate at the network's edge. This alliance not only expands Avnet's portfolio in the burgeoning field of AI technology but also promises to enhance the capabilities of IoT and consumer devices, pushing forward the frontiers of what edge AI can achieve. [Published On: 2024-01-04]

STMicroelectronics Unveils Advanced Edge AI Processor Series for Enhanced Computational Capabilities

STMicroelectronics introduced a new series of edge AI processors to improve computational abilities and energy efficiency in AI applications. The STM32Cube.AI, an integral component of the new range, allows seamless conversion of neural networks into optimized code for faster, more efficient use at the edge. This development targets a broad spectrum of applications, including industrial IoT, automotive systems, and consumer products, where local data processing is crucial for responsiveness and privacy. By enhancing processing power directly on devices, the series minimizes reliance on cloud-based systems, reducing latency and ensuring robust operation even with intermittent connectivity. This initiative underlines STMicroelectronics' commitment to advancing edge computing technologies and promises substantial improvements in the functionality and efficiency of AI-driven applications. [Published On: 2023-06-15]

Strategy Analysis & Recommendation

The strategic analysis is essential for organizations seeking a solid foothold in the global marketplace. Companies are better positioned to make informed decisions that align with their long-term aspirations by thoroughly evaluating their current standing in the Edge AI Hardware Market. This critical assessment involves a thorough analysis of the organization's resources, capabilities, and overall performance to identify its core strengths and areas for improvement.

Key Company Profiles

The report delves into recent significant developments in the Edge AI Hardware Market, highlighting leading vendors and their innovative profiles. These include Advanced Micro Devices, Inc., Aetina Corporation, Apple Inc., Arm Holdings plc, Huawei Technologies Co., Ltd., Imagination Technologies, Intel Corporation, International Business Machines Corporation, MediaTek Inc., Micron Technology, Inc., Microsoft Corporation, Murata Manufacturing Co., Ltd., NVIDIA Corporation, Premier Farnell Limited, Qualcomm Technologies, Inc., Renesas Electronics Corporation, Samsung Electronics Co., Ltd., Sony Group Corporation, STMicroelectronics N.V., Super Micro Computer, Inc., Texas Instruments Incorporated, and Xailient Inc..

Market Segmentation & Coverage

This research report categorizes the Edge AI Hardware Market to forecast the revenues and analyze trends in each of the following sub-markets:

Component
- Memory
- Networking Sensor
- Processor
  - ASICs
  - CPU
  - FPGA
  - GPU
Device
- Automotive
- Edge servers
- Robots
- Smart mirrors
- Smart speakers
- Smartphones
- Surveillance cameras
- Wearables

Power Consumption
- 1-3 W
- 3-5 W
- 5-10W
- Less than 1W
- More than 10W

Function
- Inference
- Training

End-Use
- Aerospace
- Automotive
- Consumer Electronics
- Healthcare
- Industrial

Region
- Americas
  - Argentina
  - Brazil
  - Canada
  - Mexico
  - United States
    - California
    - Florida
    - Illinois
    - New York
    - Ohio
    - Pennsylvania
    - Texas
- Asia-Pacific
  - Australia
  - China
  - India
  - Indonesia
  - Japan
  - Malaysia
  - Philippines
  - Singapore
  - South Korea
  - Taiwan
  - Thailand
  - Vietnam

Europe, Middle East & Africa
- Denmark
- Egypt
- Finland
- France
- Germany
- Israel
- Italy
- Netherlands
- Nigeria
- Norway
- Poland
- Qatar
- Russia
- Saudi Arabia
- South Africa
- Spain
- Sweden
- Switzerland
- Turkey
- United Arab Emirates
- United Kingdom

Product Code: MRR-8201ABF21A57

1. Preface

1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Stakeholders

2. Research Methodology

2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

5.1. Market Dynamics
- 5.1.1. Drivers
  - 5.1.1.1. Increasing adoption of AI-based robots across the automotive industry
  - 5.1.1.2. Growing need for low latency and real-time processing on edge AI devices
  - 5.1.1.3. Surge in consumer demand for smart devices
- 5.1.2. Restraints
  - 5.1.2.1. Concerns regarding high power consumption with edge AI hardware
- 5.1.3. Opportunities
  - 5.1.3.1. Continuous innovations in edge AI hardware that enhance the performance of edge AI devices
  - 5.1.3.2. Rising investment in smart city projects with the advent of 5G network globally
- 5.1.4. Challenges
  - 5.1.4.1. Complexity in the integration of edge AI hardware
5.2. Market Segmentation Analysis
- 5.2.1. Component: Advancements in the edge AI memory and processors to ensure real-time data storing operation effectively
- 5.2.2. Function: Deployment of inference based AI in IoT devices to reduce delays in data processing and decision-making
5.3. Market Disruption Analysis
5.4. Porter's Five Forces Analysis
- 5.4.1. Threat of New Entrants
- 5.4.2. Threat of Substitutes
- 5.4.3. Bargaining Power of Customers
- 5.4.4. Bargaining Power of Suppliers
- 5.4.5. Industry Rivalry
5.5. Value Chain & Critical Path Analysis
5.6. Pricing Analysis
5.7. Technology Analysis
5.8. Patent Analysis
5.9. Trade Analysis
5.10. Regulatory Framework Analysis

6. Edge AI Hardware Market, by Component

6.1. Introduction
6.2. Memory
6.3. Networking Sensor
6.4. Processor

7. Edge AI Hardware Market, by Device

7.1. Introduction
7.2. Automotive
7.3. Edge servers
7.4. Robots
7.5. Smart mirrors
7.6. Smart speakers
7.7. Smartphones
7.8. Surveillance cameras
7.9. Wearables

8. Edge AI Hardware Market, by Power Consumption

8.1. Introduction
8.2. 1-3 W
8.3. 3-5 W
8.4. 5-10W
8.5. Less than 1W
8.6. More than 10W

9. Edge AI Hardware Market, by Function

9.1. Introduction
9.2. Inference
9.3. Training

10. Edge AI Hardware Market, by End-Use

10.1. Introduction
10.2. Aerospace
10.3. Automotive
10.4. Consumer Electronics
10.5. Healthcare
10.6. Industrial

11. Americas Edge AI Hardware Market

11.1. Introduction
11.2. Argentina
11.3. Brazil
11.4. Canada
11.5. Mexico
11.6. United States

12. Asia-Pacific Edge AI Hardware Market

12.1. Introduction
12.2. Australia
12.3. China
12.4. India
12.5. Indonesia
12.6. Japan
12.7. Malaysia
12.8. Philippines
12.9. Singapore
12.10. South Korea
12.11. Taiwan
12.12. Thailand
12.13. Vietnam

13. Europe, Middle East & Africa Edge AI Hardware Market

13.1. Introduction
13.2. Denmark
13.3. Egypt
13.4. Finland
13.5. France
13.6. Germany
13.7. Israel
13.8. Italy
13.9. Netherlands
13.10. Nigeria
13.11. Norway
13.12. Poland
13.13. Qatar
13.14. Russia
13.15. Saudi Arabia
13.16. South Africa
13.17. Spain
13.18. Sweden
13.19. Switzerland
13.20. Turkey
13.21. United Arab Emirates
13.22. United Kingdom

14. Competitive Landscape

14.1. Market Share Analysis, 2023
14.2. FPNV Positioning Matrix, 2023
14.3. Competitive Scenario Analysis
- 14.3.1. Intel Unveils New Edge AI Technologies at MWC 2024 to Revolutionize Local Data Processing for Enhanced Speed and Efficiency
- 14.3.2. Avnet and Syntiant Partnered to Advance Edge AI Technology Distribution
- 14.3.3. STMicroelectronics Unveils Advanced Edge AI Processor Series for Enhanced Computational Capabilities
14.4. Strategy Analysis & Recommendation

15. Competitive Portfolio

15.1. Key Company Profiles
15.2. Key Product Portfolio