INFORMATION & COMMUNICATION TECHNOLOGY
Global Edge AI Market - Industry Trends and Forecast to 2032
REPORT OVERVIEW
Global Edge AI Market, By Deployment Mode (On-Premise, Cloud-Based), Component (Hardware, Software, Services, Edge Cloud Infrastructure), End-Use Industry (IT & Telecom, Automotive, Government, Manufacturing, Healthcare, Consumers & Goods, Other End-Use Industries), Device type (Smartphones, Cameras, Robots, Wearables, Smart speakers, Surveillance Cameras, Edge Servers, Smart Mirrors, Others), Application (Video Surveillance, Access Management, Autonomous Vehicles, Energy Management, Others), Region (North America, Europe, Asia-Pacific, South America, Middle East and Africa) – Industry Trends and Forecast to 2032.
Market Insights
The global edge AI market size is valued to be USD xx million in 2023 and is expected to reach USD xx million by 2032, and it is expected to register a CAGR of xx% over the forecast period 2024-2032.
Edge AI is the deployment of artificial intelligence (AI) algorithms and models directly on local devices, such as smartphones, IoT devices, and edge servers, rather than depending on centralized cloud computing resources. This method allows for real-time data processing, reduces latency, improves privacy and security, and can work independently of internet connectivity. The Edge AI market consists of several components, including hardware (sensors, processors), software (AI frameworks, development tools), and services (integration, support). Real-time decision-making and data processing are crucial in a wide range of industries, including healthcare, manufacturing, retail, and smart cities. The market is driven by the need for effective, low-latency computing solutions, the growth of IoT devices, and advances in AI.
The respective global report analyses market trends, consumer behaviour and industry dynamics to guide towards entry into new markets with ease. Also, it assists in tailoring market specific and related products and services to meet the needs, preferences, and expectations of target audience by delving into their psychology. The report also specializes with comprehensive and extensive competitive analysis which offers useful insights into competitor strengths, weaknesses, opportunities, and threats. The respective report offers exclusive insights into the potential impact of disruptive developments and technologies that are expected to completely transform corporate operations. The context includes tailor-made research solutions to create a stronger footprint in their particular industries thereby offering dedicated customized solutions according to the client needs which helps in addressing unique business challenges with more simplified and efficient decision-making solutions.
Market Dynamics
DRIVERS
- Advancements in AI and machine learning
- Growing use of edge computing in healthcare and automotive sectors
RESTRAINTS
- High implementation costs
- Limited availability of skilled professionals
OPPORTUNITIES
- Rising investments in AI startups
- Expansion in emerging markets
CHALLENGES
- Standardization of edge AI technologies
- Managing data at scale
SEGMENTATION
- Deployment Mode
- On-Premise
- Cloud-Based
- Component
- Hardware
- Software
- Services
- Edge Cloud Infrastructure
- End-Use Industry
- IT & Telecom
- Automotive
- Government
- Manufacturing
- Healthcare
- Consumers & Goods
- Other End-Use Industries
- Device type
- Smartphones
- Cameras
- Robots
- Wearables
- Smart speakers
- Surveillance Cameras
- Edge Servers
- Smart Mirrors
- Others
- Application
- Video Surveillance
- Access Management
- Autonomous Vehicles
- Energy Management
- Others
The respective global report is completely customizable specific to regions (North America, Europe, Asia-Pacific, South America, Middle East and Africa), countries, and segments as per the client requirements.
REGIONAL SEGMENTATION
- North America
- U.S.
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- U.K.
- France
- Italy
- Spain
- Russia
- The Netherlands
- Belgium
- Turkey
- Rest of Europe
- Asia-Pacific
- China
- India
- Japan
- South Korea
- Singapore
- Malaysia
- Australia
- Thailand
- Philippines
- Rest of Asia-Pacific
- South America
- Brazil
- Argentina
- Chile
- Colombia
- Rest of South America
- Middle East and Africa
- Kingdom of Saudi Arabia
- South Africa
- U.A.E.
- Egypt
- Rest of Middle East and Africa
KEY MARKET PLAYERS
- NVIDIA Corporation
- Microsoft Corporation
- IBM Corporation
- Alphabet, Inc.
- Oracle Corporation
- Honeywell International Inc.
- Google LLC
- Intel Corporation
- Xilinx, Inc.
- Dell Technologies Inc.
Table OF CONTENTS
- SECTION 1 - INTRODUCTION
- 1.1 Taxonomy
- 1.2 Market Overview
- 1.3 Currency and Limitations
- 1.3.1 Currency
- 1.3.2 Limitations
- 1.4 Key Competitors
- SECTION 2 - RESEARCH METHODOLOGY
- 2.1 Research Approach
- 2.2 Data Collection and Validation
- 2.2.1 Secondary Research
- 2.2.2 Primary Research
- 2.3 Market Assessment
- 2.3.1 Market Size Estimation
- 2.3.2 Bottom-up Approach
- 2.3.3 Top-down Approach
- 2.3.4 Growth Forecast
- 2.4 Market Study Assumptions
- 2.5 Data Sources
- SECTION 3 - EXECUTIVE SUMMARY
- 3.1 Global Edge AI Market, by Deployment Mode
- 3.2 Global Edge AI Market, by Component
- 3.3 Global Edge AI Market, by End-Use Industry
- 3.4 Global Edge AI Market, by Device type
- 3.5 Global Edge AI Market, by Application
- 3.6 Global Edge AI Market, by Geography
- 3.7 Market Position Grid
- SECTION 4 - PREMIUM INSIGHTS
- 4.1 Regulatory Framework
- 4.1.1 Standards
- 4.1.2 Regulatory Landscape
- 4.2 Value Chain Analysis
- 4.3 Supply Chain Analysis
- 4.4 COVID-19 Impact
- 4.5 Russia-Ukraine War Impact
- 4.6 PORTER's Five Force Analysis
- 4.7 PESTLE Analysis
- 4.8 SWOT Analysis
- 4.9 Go to Market Strategy
- 4.10 Opportunity Orbit
- 4.11 Multivariate Modelling
- 4.12 Pricing Analysis
- SECTION 5 - MARKET DYNAMICS
- 5.1 Trends
- 5.1.1 Integration of AI into IoT devices
- 5.1.2 Increasing adoption in smart cities and industrial automation
- 5.1.3 Trend 3
- 5.2 Drivers
- 5.2.1 Advancements in AI and machine learning
- 5.2.2 Growing use of edge computing in healthcare and automotive sectors
- 5.2.3 Driver 3
- 5.2.4 Driver 4
- 5.3 Restraints
- 5.3.1 High implementation costs
- 5.3.2 Limited availability of skilled professionals
- 5.3.3 Restraint 3
- 5.4 Opportunities
- 5.4.1 Rising investments in AI startups
- 5.4.2 Expansion in emerging markets
- 5.4.3 Opportunity 3
- 5.4.4 Opportunity 4
- 5.5 Challenges
- 5.5.1 Standardization of edge AI technologies
- 5.5.2 Managing data at scale
- 5.5.3 Challenge 3
- SECTION 6 - GLOBAL EDGE AI MARKET, BY DEPLOYMENT MODE
- 6.1 Deployment Mode Summary
- 6.2 Market Attractive Index
- 6.3 Global Edge AI Market, by Deployment Mode (2019-2032)
- SECTION 7 - GLOBAL EDGE AI MARKET, BY COMPONENT
- 7.1 Component Summary
- 7.2 Market Attractive Index
- 7.3 Global Edge AI Market, by Component (2019-2032)
- SECTION 8 - GLOBAL EDGE AI MARKET, BY END-USE INDUSTRY
- 8.1 End-Use Industry Summary
- 8.2 Market Attractive Index
- 8.3 Global Edge AI Market, by End-Use Industry (2019-2032)
- SECTION 9 - GLOBAL EDGE AI MARKET, BY DEVICE TYPE
- 9.1 Device type Summary
- 9.2 Market Attractive Index
- 9.3 Global Edge AI Market, by Device type (2019-2032)
- SECTION 10 - GLOBAL EDGE AI MARKET, BY APPLICATION
- 10.1 Application Summary
- 10.2 Market Attractive Index
- 10.3 Global Edge AI Market, by Application (2019-2032)
- SECTION 11 - GLOBAL EDGE AI MARKET, BY GEOGRAPHY
- 11.1 Regional Summary
- 11.2 Market Attractive Index
- 11.3 Global Edge AI Market, by Geography (2019-2032)
- SECTION 12 - NORTH AMERICA EDGE AI MARKET
- 12.1 North America Summary
- 12.2 Market Attractive Index
- 12.3 North America Edge AI Market, by Deployment Mode (2019-2032)
- 12.4 North America Edge AI Market, by Component (2019-2032)
- 12.5 North America Edge AI Market, by End-Use Industry (2019-2032)
- 12.6 North America Edge AI Market, by Device type (2019-2032)
- 12.7 North America Edge AI Market, by Application (2019-2032)
- 12.8 North America Edge AI Market, by Country (2019-2032)
- 12.8.1 U.S.
- 12.8.2 Canada
- 12.8.3 Mexico
- 12.8.4 Rest of North America
- SECTION 13 - EUROPE EDGE AI MARKET
- 13.1 Europe Summary
- 13.2 Market Attractive Index
- 13.3 Europe Edge AI Market, by Deployment Mode (2019-2032)
- 13.4 Europe Edge AI Market, by Component (2019-2032)
- 13.5 Europe Edge AI Market, by End-Use Industry (2019-2032)
- 13.6 Europe Edge AI Market, by Device type (2019-2032)
- 13.7 Europe Edge AI Market, by Application (2019-2032)
- 13.8 Europe Edge AI Market, by Country (2019-2032)
- 13.8.1 Germany
- 13.8.2 U.K.
- 13.8.3 France
- 13.8.4 Italy
- 13.8.5 Spain
- 13.8.6 Russia
- 13.8.7 The Netherlands
- 13.8.8 Belgium
- 13.8.9 Turkey
- 13.8.10 Rest of Europe
- SECTION 14 - ASIA-PACIFIC EDGE AI MARKET
- 14.1 Asia-Pacific Summary
- 14.2 Market Attractive Index
- 14.3 Asia-Pacific Edge AI Market, by Deployment Mode (2019-2032)
- 14.4 Asia-Pacific Edge AI Market, by Component (2019-2032)
- 14.5 Asia-Pacific Edge AI Market, by End-Use Industry (2019-2032)
- 14.6 Asia-Pacific Edge AI Market, by Device type (2019-2032)
- 14.7 Asia-Pacific Edge AI Market, by Application (2019-2032)
- 14.8 Asia-Pacific Edge AI Market, by Country (2019-2032)
- 14.8.1 China
- 14.8.2 India
- 14.8.3 Japan
- 14.8.4 South Korea
- 14.8.5 Singapore
- 14.8.6 Malaysia
- 14.8.7 Australia
- 14.8.8 Thailand
- 14.8.9 Philippines
- 14.8.10 Rest of Asia-Pacific
- SECTION 15 - SOUTH AMERICA EDGE AI MARKET
- 15.1 South America Summary
- 15.2 Market Attractive Index
- 15.3 South America Edge AI Market, by Deployment Mode (2019-2032)
- 15.4 South America Edge AI Market, by Component (2019-2032)
- 15.5 South America Edge AI Market, by End-Use Industry (2019-2032)
- 15.6 South America Edge AI Market, by Device type (2019-2032)
- 15.7 South America Edge AI Market, by Application (2019-2032)
- 15.8 South America Edge AI Market, by Country (2019-2032)
- 15.8.1 Brazil
- 15.8.2 Argentina
- 15.8.3 Chile
- 15.8.4 Colombia
- 15.8.5 Rest of South America
- SECTION 16 - MIDDLE EAST AND AFRICA EDGE AI MARKET
- 16.1 Middle East and Africa Summary
- 16.2 Market Attractive Index
- 16.3 Middle East and Africa Edge AI Market, by Deployment Mode (2019-2032)
- 16.4 Middle East and Africa Edge AI Market, by Component (2019-2032)
- 16.5 Middle East and Africa Edge AI Market, by End-Use Industry (2019-2032)
- 16.6 Middle East and Africa Edge AI Market, by Device type (2019-2032)
- 16.7 Middle East and Africa Edge AI Market, by Application (2019-2032)
- 16.8 Middle East and Africa Edge AI Market, by Country (2019-2032)
- 16.8.1 Kingdom of Saudi Arabia
- 16.8.2 South Africa
- 16.8.3 U.A.E.
- 16.8.4 Egypt
- 16.8.5 Rest of Middle East and Africa
- SECTION 17 - COMPANY SHARE ANALYSIS
- 17.1 Global Edge AI Market, Company Share Analysis
- 17.2 North America Edge AI Market, Company Share Analysis
- 17.3 Europe Edge AI Market, Company Share Analysis
- 17.4 Asia-Pacific Edge AI Market, Company Share Analysis
- SECTION 18 - COMPANY PROFILES
- 18.1 NVIDIA Corporation
- 18.1.1 Company Snapshot
- 18.1.2 Financial Overview
- 18.1.3 Product Portfolio
- 18.1.4 Recent Developments
- 18.2 Microsoft Corporation
- 18.2.1 Company Snapshot
- 18.2.2 Financial Overview
- 18.2.3 Product Portfolio
- 18.2.4 Recent Developments
- 18.3 IBM Corporation
- 18.3.1 Company Snapshot
- 18.3.2 Financial Overview
- 18.3.3 Product Portfolio
- 18.3.4 Recent Developments
- 18.4 Alphabet, Inc.
- 18.4.1 Company Snapshot
- 18.4.2 Financial Overview
- 18.4.3 Product Portfolio
- 18.4.4 Recent Developments
- 18.5 Oracle Corporation
- 18.5.1 Company Snapshot
- 18.5.2 Financial Overview
- 18.5.3 Product Portfolio
- 18.5.4 Recent Developments
- 18.6 Honeywell International Inc.
- 18.6.1 Company Snapshot
- 18.6.2 Financial Overview
- 18.6.3 Product Portfolio
- 18.6.4 Recent Developments
- 18.7 Google LLC
- 18.7.1 Company Snapshot
- 18.7.2 Financial Overview
- 18.7.3 Product Portfolio
- 18.7.4 Recent Developments
- 18.8 Intel Corporation
- 18.8.1 Company Snapshot
- 18.8.2 Financial Overview
- 18.8.3 Product Portfolio
- 18.8.4 Recent Developments
- 18.9 Xilinx, Inc.
- 18.9.1 Company Snapshot
- 18.9.2 Financial Overview
- 18.9.3 Product Portfolio
- 18.9.4 Recent Developments
- 18.10 Dell Technologies Inc.
- 18.10.1 Company Snapshot
- 18.10.2 Financial Overview
- 18.10.3 Product Portfolio
- 18.10.4 Recent Developments
- SECTION 19 - RELATED REPORTS
- SECTION 20 - DISCLAIMER
RESEARCH METHODOLOGY
The research methodology employed in Uniprism Market Research involves four basic steps namely research and data collection, data pre-processing, modeling and forecasting, quality assurance and output.
RESEARCH AND DATA COLLECTION
A tripod model research technique is followed for research and data collection in which various approaches such as primary research, secondary research, and product mapping are considered.
Primary research basically involves the process of conducting personalized interviews with market related professionals of major market players, investors, distributors, vendors and many more.
The secondary research include data published by government, annual reports, press releases, investor presentations of companies, white papers, certified publications, annual manufacturing limit of the respective industries related to the market, production consumption analysis of certain products respective to the market and many more.
Below mention are few of the sources which we have considered while estimating the market size:
For instance,
- Research articles published on Technium
- Science and MDPI
- Research publications by government approved associations and societies
Product mapping means the process of mapping the list of products that a key player contributes to the market as well as estimating the revenue of those products in order to define the Global Company share analysis of the respective Global Company in global, regional, and country level markets.
DATA PRE-PROCESSING
The term "data pre-processing" refers to the collection of procedures and methods used to clean, modify, and make ready for analysis the raw data gathered during research and data collection. The completion of this phase is necessary to guarantee that the data are reliable, consistent, and appropriate for statistical analysis and other data-driven tasks. The data pre-processing ensures that the information gathered from research and data collection is comparable and expressed in standard units, by the integration of missing data pointers and algorithmic approaches.
MODELING AND FORECASTING
The process of developing mathematical, statistical, or computational representations of real-world occurrences or relationships is known as modelling. These models are intended to replicate and explain market interactions, interdependence, and dynamics. These models are used by Uniprism Market Research to acquire a better knowledge of numerous market characteristics such as customer preferences, pricing elasticity, competition dynamics, and more. Depending on the individual study aims, many types of models are utilized, such as regression models, econometric models, decision tree models, and machine learning models.
Forecasting is the process of predicting future market conditions, trends, and occurrences using past data and models. Forecasting is used by Uniprism Market Research to estimate future sales, demand for products or services, market growth, and other important performance metrics. Forecasting accurately can assist organizations in making educated decisions about resource allocation, pricing, inventory management, and marketing tactics.
We create standardized bottom-up or top-down models that scale by leveraging data science and machine learning technology. All our market models consider the unique market characteristics of each country. Forecasting is based on major market indicators and a combination of traditional methodologies, such as exponential smoothing, time series analysis, regression analysis, and more modern techniques such as machine learning algorithms are all forecasting methodologies. The method chosen is determined on the nature of the data and the specific forecasting aims.
QUALITY ASSURANCE AND OUTPUT
Quality assurance and output involves the process of validation, adjustments, further publications of key market indicators. Extensive plausibility and consistency tests are performed on derived time series to ensure the high degree of quality of our market analysis. This quality assurance procedure also includes rigorous inspection, validation, and editing by an experienced management team to assure the dependability of the published data.