Global Distributed Edge AI Market Research Report 2024

Publication ID:

PB512242568

Publication Date:

December 18, 2024

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

The global market for Distributed Edge AI was valued at US$ 6809 million in the year 2023 and is projected to reach a revised size of US$ 22740 million by 2030, growing at a CAGR of 18.8% during the forecast period.
Distributed Edge AI refers to the integration of artificial intelligence (AI) with edge computing, where data processing and decision-making are performed on local devices or nodes near the source of data generation, rather than sending all data to a centralized cloud. This approach improves response times, reduces latency, and enhances privacy and security by keeping sensitive data on the edge. Distributed Edge AI enables real-time processing for applications in IoT, autonomous vehicles, smart cities, and industrial automation.
North American market for Distributed Edge AI is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Asia-Pacific market for Distributed Edge AI is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The global market for Distributed Edge AI in Automotive is estimated to increase from $ million in 2023 to $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The major global companies of Distributed Edge AI include NVIDIA, Intel, Google, Qualcomm, Microsoft, Amazon Web Services (AWS), IBM, Huawei, EdgeQ, AImotive, etc. In 2023, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Distributed Edge AI, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Distributed Edge AI.
The Distributed Edge AI market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Distributed Edge AI market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Distributed Edge AI companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
NVIDIA
Intel
Google
Qualcomm
Microsoft
Amazon Web Services (AWS)
IBM
Huawei
EdgeQ
AImotive
Samsara
FogHorn
SensiML
Xilinx
Segment by Type
Hardware
Software
Segment by Application
Automotive
Drones
Head-Mounted Displays
Smart Speakers
Mobile Phones
PCs/Tablets
Security Cameras
Other
By Region
North America
United States
Canada
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Rest of Europe
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Distributed Edge AI company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Distributed Edge AI Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 Hardware
1.2.3 Software
1.3 Market by Application
1.3.1 Global Distributed Edge AI Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 Automotive
1.3.3 Drones
1.3.4 Head-Mounted Displays
1.3.5 Smart Speakers
1.3.6 Mobile Phones
1.3.7 PCs/Tablets
1.3.8 Security Cameras
1.3.9 Other
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global Distributed Edge AI Market Perspective (2019-2030)
2.2 Global Distributed Edge AI Growth Trends by Region
2.2.1 Global Distributed Edge AI Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Distributed Edge AI Historic Market Size by Region (2019-2024)
2.2.3 Distributed Edge AI Forecasted Market Size by Region (2025-2030)
2.3 Distributed Edge AI Market Dynamics
2.3.1 Distributed Edge AI Industry Trends
2.3.2 Distributed Edge AI Market Drivers
2.3.3 Distributed Edge AI Market Challenges
2.3.4 Distributed Edge AI Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Distributed Edge AI Players by Revenue
3.1.1 Global Top Distributed Edge AI Players by Revenue (2019-2024)
3.1.2 Global Distributed Edge AI Revenue Market Share by Players (2019-2024)
3.2 Global Distributed Edge AI Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by Distributed Edge AI Revenue
3.4 Global Distributed Edge AI Market Concentration Ratio
3.4.1 Global Distributed Edge AI Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Distributed Edge AI Revenue in 2023
3.5 Global Key Players of Distributed Edge AI Head office and Area Served
3.6 Global Key Players of Distributed Edge AI, Product and Application
3.7 Global Key Players of Distributed Edge AI, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 Distributed Edge AI Breakdown Data by Type
4.1 Global Distributed Edge AI Historic Market Size by Type (2019-2024)
4.2 Global Distributed Edge AI Forecasted Market Size by Type (2025-2030)
5 Distributed Edge AI Breakdown Data by Application
5.1 Global Distributed Edge AI Historic Market Size by Application (2019-2024)
5.2 Global Distributed Edge AI Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Distributed Edge AI Market Size (2019-2030)
6.2 North America Distributed Edge AI Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Distributed Edge AI Market Size by Country (2019-2024)
6.4 North America Distributed Edge AI Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Distributed Edge AI Market Size (2019-2030)
7.2 Europe Distributed Edge AI Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Distributed Edge AI Market Size by Country (2019-2024)
7.4 Europe Distributed Edge AI Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Distributed Edge AI Market Size (2019-2030)
8.2 Asia-Pacific Distributed Edge AI Market Growth Rate by Country: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Distributed Edge AI Market Size by Region (2019-2024)
8.4 Asia-Pacific Distributed Edge AI Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Distributed Edge AI Market Size (2019-2030)
9.2 Latin America Distributed Edge AI Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Distributed Edge AI Market Size by Country (2019-2024)
9.4 Latin America Distributed Edge AI Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Distributed Edge AI Market Size (2019-2030)
10.2 Middle East & Africa Distributed Edge AI Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Distributed Edge AI Market Size by Country (2019-2024)
10.4 Middle East & Africa Distributed Edge AI Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 NVIDIA
11.1.1 NVIDIA Company Details
11.1.2 NVIDIA Business Overview
11.1.3 NVIDIA Distributed Edge AI Introduction
11.1.4 NVIDIA Revenue in Distributed Edge AI Business (2019-2024)
11.1.5 NVIDIA Recent Development
11.2 Intel
11.2.1 Intel Company Details
11.2.2 Intel Business Overview
11.2.3 Intel Distributed Edge AI Introduction
11.2.4 Intel Revenue in Distributed Edge AI Business (2019-2024)
11.2.5 Intel Recent Development
11.3 Google
11.3.1 Google Company Details
11.3.2 Google Business Overview
11.3.3 Google Distributed Edge AI Introduction
11.3.4 Google Revenue in Distributed Edge AI Business (2019-2024)
11.3.5 Google Recent Development
11.4 Qualcomm
11.4.1 Qualcomm Company Details
11.4.2 Qualcomm Business Overview
11.4.3 Qualcomm Distributed Edge AI Introduction
11.4.4 Qualcomm Revenue in Distributed Edge AI Business (2019-2024)
11.4.5 Qualcomm Recent Development
11.5 Microsoft
11.5.1 Microsoft Company Details
11.5.2 Microsoft Business Overview
11.5.3 Microsoft Distributed Edge AI Introduction
11.5.4 Microsoft Revenue in Distributed Edge AI Business (2019-2024)
11.5.5 Microsoft Recent Development
11.6 Amazon Web Services (AWS)
11.6.1 Amazon Web Services (AWS) Company Details
11.6.2 Amazon Web Services (AWS) Business Overview
11.6.3 Amazon Web Services (AWS) Distributed Edge AI Introduction
11.6.4 Amazon Web Services (AWS) Revenue in Distributed Edge AI Business (2019-2024)
11.6.5 Amazon Web Services (AWS) Recent Development
11.7 IBM
11.7.1 IBM Company Details
11.7.2 IBM Business Overview
11.7.3 IBM Distributed Edge AI Introduction
11.7.4 IBM Revenue in Distributed Edge AI Business (2019-2024)
11.7.5 IBM Recent Development
11.8 Huawei
11.8.1 Huawei Company Details
11.8.2 Huawei Business Overview
11.8.3 Huawei Distributed Edge AI Introduction
11.8.4 Huawei Revenue in Distributed Edge AI Business (2019-2024)
11.8.5 Huawei Recent Development
11.9 EdgeQ
11.9.1 EdgeQ Company Details
11.9.2 EdgeQ Business Overview
11.9.3 EdgeQ Distributed Edge AI Introduction
11.9.4 EdgeQ Revenue in Distributed Edge AI Business (2019-2024)
11.9.5 EdgeQ Recent Development
11.10 AImotive
11.10.1 AImotive Company Details
11.10.2 AImotive Business Overview
11.10.3 AImotive Distributed Edge AI Introduction
11.10.4 AImotive Revenue in Distributed Edge AI Business (2019-2024)
11.10.5 AImotive Recent Development
11.11 Samsara
11.11.1 Samsara Company Details
11.11.2 Samsara Business Overview
11.11.3 Samsara Distributed Edge AI Introduction
11.11.4 Samsara Revenue in Distributed Edge AI Business (2019-2024)
11.11.5 Samsara Recent Development
11.12 FogHorn
11.12.1 FogHorn Company Details
11.12.2 FogHorn Business Overview
11.12.3 FogHorn Distributed Edge AI Introduction
11.12.4 FogHorn Revenue in Distributed Edge AI Business (2019-2024)
11.12.5 FogHorn Recent Development
11.13 SensiML
11.13.1 SensiML Company Details
11.13.2 SensiML Business Overview
11.13.3 SensiML Distributed Edge AI Introduction
11.13.4 SensiML Revenue in Distributed Edge AI Business (2019-2024)
11.13.5 SensiML Recent Development
11.14 Xilinx
11.14.1 Xilinx Company Details
11.14.2 Xilinx Business Overview
11.14.3 Xilinx Distributed Edge AI Introduction
11.14.4 Xilinx Revenue in Distributed Edge AI Business (2019-2024)
11.14.5 Xilinx Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.1.1 Research Programs/Design
13.1.1.2 Market Size Estimation
13.1.1.3 Market Breakdown and Data Triangulation
13.1.2 Data Source
13.1.2.1 Secondary Sources
13.1.2.2 Primary Sources
13.2 Author Details
13.3 Disclaimer

Companies Mentioned:

NVIDIA
Intel
Google
Qualcomm
Microsoft
Amazon Web Services (AWS)
IBM
Huawei
EdgeQ
AImotive
Samsara
FogHorn
SensiML
Xilinx

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