세계의 엣지 AI 시장 예측(-2032년) : 컴포넌트별, 프로세서 유형별, 용도별, 최종사용자별, 지역별 세계 분석

According to Stratistics MRC, the Global Edge AI Market is accounted for $31.19 billion in 2025 and is expected to reach $192.59 billion by 2032 growing at a CAGR of 29.7% during the forecast period. Edge AI involves running artificial intelligence models on devices located at the network's edge, including cameras, wearables, gateways, and industrial equipment, instead of sending data to cloud platforms. Processing data locally accelerates response times, strengthens privacy, and minimizes network load. This technology enables instant insights for areas such as robotics, connected healthcare, transportation, and smart cities. By merging on-device computation with advanced AI, Edge AI delivers quicker operations, better security, and higher performance for decentralized applications.

Market Dynamics:

Driver:

Demand for real-time processing

Organizations are increasingly shifting critical workloads closer to the data source to reduce latency and improve responsiveness. Applications such as autonomous vehicles, industrial automation, and intelligent surveillance rely heavily on real-time inference. Edge AI enables faster decision-making without depending on centralized cloud processing. This capability significantly enhances operational efficiency and user experience across diverse industries. As digital interactions become more immediate, demand for rapid on-device processing continues to intensify.

Restraint:

Limited compute & power resources

Limited battery life and thermal thresholds further hinder performance in demanding scenarios. Many enterprises struggle to optimize AI workloads for lightweight hardware without compromising accuracy. These limitations lead to higher model compression requirements and additional engineering efforts. In remote or mobile environments, sustaining consistent power supply adds another layer of complexity. Such constraints remain a significant challenge to scaling Edge AI deployments globally.

Opportunity:

AI-as-a-Service (AIaaS) and model marketplaces

Model marketplaces allow developers to access pre-built algorithms optimized for edge environments. These platforms accelerate innovation by reducing time-to-market for AI-driven edge applications. Businesses can easily subscribe to scalable inference services tailored to their hardware needs. This ecosystem fosters collaboration among AI providers, device manufacturers, and solution integrators. As AIaaS expands, it is expected to unlock substantial growth for Edge AI adoption across industries.

Threat:

Competition from optimized cloud AI

Cloud-based AI solutions continue to evolve with faster compute power and more sophisticated model capabilities. Many organizations still prefer cloud AI due to its scalability and minimal device-side requirements. As hyperscalers introduce cost-efficient inference engines, competition for edge deployments intensifies. Cloud platforms also offer simplified development environments that appeal to enterprise developers. The growing performance gap between cloud AI and edge hardware remains a competitive threat for the Edge AI market.

Covid-19 Impact:

The pandemic accelerated the use of edge-powered devices for remote monitoring and contactless operations. Industries such as healthcare and retail turned to on-device intelligence to reduce human interaction. Edge AI supported real-time analytics for temperature checks, occupancy tracking, and automated logistics. Supply chain disruptions highlighted the need for decentralized processing and reduced cloud dependency. Organizations invested in edge infrastructure to ensure business continuity and resilience.

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

The hardware segment is expected to account for the largest market share during the forecast period, as demand grows for powerful and efficient edge processors. Dedicated AI chips, microcontrollers, and accelerators are becoming essential for on-device inference. Manufacturers are enhancing hardware capabilities to support complex models with minimal latency. Increased investments in edge-optimized GPUs and NPUs are further driving this segment's expansion. Hardware innovations are enabling broader applications across automotive, industrial, and consumer electronics.

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

Over the forecast period, the healthcare segment is predicted to witness the highest growth rate, due to rising adoption of intelligent diagnostics and real-time patient monitoring. Edge AI enables immediate analysis of medical images, vital signs, and wearable device data. Hospitals are integrating edge solutions to improve clinical decision-making and reduce dependence on cloud connectivity. On-device processing also enhances data privacy and regulatory compliance in sensitive healthcare environments. Remote healthcare services are benefiting from fast and reliable edge-based analytics.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to its strong technological ecosystem and early adoption of advanced AI solutions. The region benefits from robust investments in edge infrastructure and 5G deployment. Major technology players are accelerating innovation in semiconductors, IoT devices, and AI accelerators. Enterprises across industries prioritize edge deployment to enhance automation and operational intelligence. Government initiatives supporting AI research further strengthen market momentum.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid urbanization and the expansion of smart city initiatives. Countries such as China, Japan, and South Korea are heavily investing in edge-enabled robotics and industrial automation. Telecom operators are deploying extensive 5G networks that amplify edge computing opportunities. Growing adoption of IoT devices across manufacturing, transportation, and retail is boosting demand for on-device AI. Government-backed digital transformation programs are accelerating enterprise investments in edge technologies.

Key players in the market

Some of the key players in Edge AI Market include Microsoft, Hewlett Packard, Google, Schneider, Amazon Web, Siemens, IBM, Cisco Systems, Intel, Arm, NVIDIA, Apple, Qualcomm, Samsung Electronics, and Huawei.

Key Developments:

In November 2025, IBM and the University of Dayton announced an agreement for the joint research and development of next-generation semiconductor technologies and materials. The collaboration aims to advance critical technologies for the age of AI including AI hardware, advanced packaging, and photonics.

In October 2025, Oracle announced collaboration with Microsoft to develop an integration blueprint to help manufacturers improve supply chain efficiency and responsiveness. The blueprint will enable organizations using Oracle Fusion Cloud Supply Chain & Manufacturing (SCM) to improve data-driven decision making and automate key supply chain processes by capturing live insights from factory equipment and sensors through Azure IoT Operations and Microsoft Fabric.

Components Covered:

• Hardware
• Software
• Services

Processor Types Covered:

• CPU
• GPU
• FPGA
• ASIC

Applications Covered:

• Smart Cities
• Automotive
• Consumer Electronics
• Industrial IoT
• Healthcare
• Retail

End Users Covered:

• Telecom
• Energy And Utilities
• Manufacturing
• Defense And Aerospace
• Transportation And Logistics
• Other End Users

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • 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 2024, 2025, 2026, 2028, and 2032
• 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
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • 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 Application Analysis
• 3.7 End User Analysis
• 3.8 Emerging Markets
• 3.9 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 Market, By Component

• 5.1 Introduction
• 5.2 Hardware
  • 5.2.1 Edge Servers
  • 5.2.2 Gateways
  • 5.2.3 Sensors
  • 5.2.4 AI Chips
• 5.3 Software
  • 5.3.1 AI Frameworks
  • 5.3.2 SDKs
  • 5.3.3 Middleware
  • 5.3.4 Edge Orchestration Platforms
• 5.4 Services
  • 5.4.1 Deployment
  • 5.4.2 Integration
  • 5.4.3 Consulting
  • 5.4.4 Managed Services

6 Global Edge AI Market, By Processor Type

• 6.1 Introduction
• 6.2 CPU
• 6.3 GPU
• 6.4 FPGA
• 6.5 ASIC

7 Global Edge AI Market, By Application

• 7.1 Introduction
• 7.2 Smart Cities
  • 7.2.1 Traffic Management
  • 7.2.2 Surveillance
  • 7.2.3 Public Safety
• 7.3 Automotive
  • 7.3.1 ADAS
  • 7.3.2 Autonomous Driving
  • 7.3.3 In-Vehicle Infotainment
• 7.4 Consumer Electronics
  • 7.4.1 Smartphones
  • 7.4.2 Wearables
  • 7.4.3 AR/VR Devices
• 7.5 Industrial IoT
  • 7.5.1 Predictive Maintenance
  • 7.5.2 Robotics
  • 7.5.3 Process Automation
• 7.6 Healthcare
  • 7.6.1 Remote Monitoring
  • 7.6.2 Diagnostics
  • 7.6.3 Medical Imaging
• 7.7 Retail

8 Global Edge AI Market, By End User

• 8.1 Introduction
• 8.2 Telecom
• 8.3 Energy And Utilities
• 8.4 Manufacturing
• 8.5 Defense And Aerospace
• 8.6 Transportation And Logistics
• 8.7 Other End Users

9 Global Edge AI Market, By Geography

• 9.1 Introduction
• 9.2 North America
  • 9.2.1 US
  • 9.2.2 Canada
  • 9.2.3 Mexico
• 9.3 Europe
  • 9.3.1 Germany
  • 9.3.2 UK
  • 9.3.3 Italy
  • 9.3.4 France
  • 9.3.5 Spain
  • 9.3.6 Rest of Europe
• 9.4 Asia Pacific
  • 9.4.1 Japan
  • 9.4.2 China
  • 9.4.3 India
  • 9.4.4 Australia
  • 9.4.5 New Zealand
  • 9.4.6 South Korea
  • 9.4.7 Rest of Asia Pacific
• 9.5 South America
  • 9.5.1 Argentina
  • 9.5.2 Brazil
  • 9.5.3 Chile
  • 9.5.4 Rest of South America
• 9.6 Middle East & Africa
  • 9.6.1 Saudi Arabia
  • 9.6.2 UAE
  • 9.6.3 Qatar
  • 9.6.4 South Africa
  • 9.6.5 Rest of Middle East & Africa

10 Key Developments

• 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 10.2 Acquisitions & Mergers
• 10.3 New Product Launch
• 10.4 Expansions
• 10.5 Other Key Strategies

11 Company Profiling

• 11.1 Microsoft
• 11.2 Hewlett Packard Enterprise (HPE)
• 11.3 Google
• 11.4 Schneider Electric
• 11.5 Amazon Web Services (AWS)
• 11.6 Siemens
• 11.7 IBM
• 11.8 Cisco Systems
• 11.9 Intel
• 11.10 Arm
• 11.11 NVIDIA
• 11.12 Apple
• 11.13 Qualcomm
• 11.14 Samsung Electronics
• 11.15 Huawei