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市场调查报告书
商品编码
1889217

边缘人工智慧市场预测至2032年：按组件、处理器类型、应用、最终用户和地区分類的全球分析

Edge AI Market Forecasts to 2032 - Global Analysis By Component (Hardware, Software, and Services), Processor Type, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的一项研究，预计到 2025 年，全球边缘人工智慧市场规模将达到 311.9 亿美元，到 2032 年将达到 1925.9 亿美元，预测期内复合年增长率为 29.7%。

边缘人工智慧 (Edge AI) 是一种在网路边缘设备（例如摄影机、穿戴式装置、网关和工业设备）上运行人工智慧模型的技术，它无需将资料传送到云端平台。本地资料处理能够加快回应速度、增强隐私保护并最大限度地降低网路负载。这项技术能够为机器人、连线健诊医疗、交通运输和智慧城市等领域提供即时洞察。透过将设备端运算与先进的人工智慧相结合，边缘人工智慧为分散式应用提供更快的运行速度、更高的安全性和更优异的效能。

对即时处理的需求

为了降低延迟并提高回应速度，各组织机构正越来越多地将关键工作负载迁移到更靠近资料来源的位置。自动驾驶汽车、工业自动化和智慧监控等应用高度依赖即时推理。边缘人工智慧无需依赖集中式云端处理即可实现更快的决策。这种能力显着提升了各行各业的营运效率和使用者体验。随着数位化互动变得更加即时，对快速设备端处理的需求也持续成长。

有限的运算能力和电力资源

有限的电池续航时间和过热阈值进一步限制了高要求场景下的效能。许多公司都在努力优化轻量级硬体上的人工智慧工作负载，同时又不牺牲精确度。这些限制增加了模型压缩的要求，并带来了额外的工程工作。在远端和行动环境中，保持稳定的电源供应也增加了复杂性。这些限制仍然是边缘人工智慧在全球大规模部署的主要挑战。

人工智慧即服务 (AIaaS) 和模型市场

模型市场为开发者提供边缘环境最佳化的预建演算法。这些平台缩短了人工智慧驱动的边缘应用上市时间，从而加速了创新。企业可以轻鬆订阅根据自身硬体需求量身定制的可扩展推理服务。该生态系统促进了人工智慧提供者、设备製造商和解决方案整合商之间的合作。随着人工智慧即服务 (AIaaS) 的扩展，预计各行业边缘人工智慧的采用率将显着增长。

与优化的云端人工智慧竞争

云端基础的AI解决方案不断发展，拥有更快的运算能力和更先进的模型功能。许多组织仍然青睐云端AI，因为它具有可扩展性，且对设备端的要求极低。随着超大规模资料中心业者推出经济高效的推理引擎，边缘部署的竞争日益激烈。云端平台也提供简化的开发环境，对企业开发人员极具吸引力。云端AI与边缘硬体之间日益扩大的效能差距，持续对边缘AI市场构成竞争威胁。

新冠疫情的影响：

疫情加速了边缘运算设备在远端监控和非接触式操作的应用。医疗保健和零售等行业纷纷转向设备端智能，以减少人与人之间的接触。边缘人工智慧支援体温检测、人员追踪和即时分析，从而实现自动化物流。供应链中断凸显了分散式处理和减少对云端依赖的必要性。各组织纷纷投资边缘基础设施，以确保业务永续营运和韧性。

预计在预测期内，硬体细分市场将占据最大的市场份额。

由于对高效能、高效率边缘处理器的需求不断增长，预计硬体领域在预测期内将占据最大的市场份额。专用人工智慧晶片、微控制器和加速器正成为设备端推理的关键组件。製造商正在提升硬体性能，以支援延迟极低的复杂模型。对边缘优化型GPU和NPU的投资不断增加，进一步推动了该领域的扩张。硬体创新正在赋能包括汽车、工业和家用电子电器在内的众多领域的应用。

预计在预测期内，医疗保健产业将实现最高的复合年增长率。

预计在预测期内，医疗保健领域将实现最高成长率，这主要得益于智慧诊断和即时病患监测的日益普及。边缘人工智慧能够即时分析医学影像、生命征象和穿戴式装置数据。医院正越来越多地整合边缘解决方案，以改善临床决策并减少对云端连接的依赖。设备端处理还能增强敏感医疗环境中的资料隐私和合规性。远端医疗服务也受益于快速可靠的边缘分析技术。

占比最大的地区：

在预测期内，北美预计将占据最大的市场份额，这得益于其强大的技术生态系统和先进人工智慧解决方案的早期应用。该地区正受益于对边缘基础设施和5G部署的大力投资。领先的科技公司正在加速半导体、物联网设备和人工智慧加速器领域的创新。各行各业的公司都在优先考虑边缘部署，以增强自动化和营运智慧。政府支持人工智慧研究的措施也进一步巩固了市场发展动能。

复合年增长率最高的地区：

在预测期内，亚太地区预计将实现最高的复合年增长率，这主要得益于快速的都市化和智慧城市计划的持续推进。中国、日本和韩国等国家正大力投资边缘机器人和工业自动化。通讯业者正在广泛部署5G网络，为边缘运算拓展了机会。物联网设备在製造业、运输业和零售业的日益普及，推动了对设备端人工智慧的需求。政府主导的数位转型计画正在加速企业对边缘技术的投资。

免费客製化服务：

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  • 公司概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
    • 主要参与者（最多3家公司）的SWOT分析
  • 区域细分
    • 根据客户要求，提供主要国家的市场估算和预测，以及复合年增长率（註：可行性需确认）。
  • 竞争基准化分析
    • 根据主要参与者的产品系列、地理覆盖范围和策略联盟基准化分析

目录

第一章执行摘要

第二章 前言

  • 摘要
  • 相关利益者
  • 调查范围
  • 调查方法
  • 研究材料

第三章 市场趋势分析

  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

第五章 全球边缘人工智慧市场（按组件划分）

  • 硬体
    • 边缘伺服器
    • 闸道
    • 感应器
    • 人工智慧晶片
  • 软体
    • 人工智慧框架
    • SDK
    • 中介软体
    • 边缘编配平台
  • 服务
    • 配置
    • 一体化
    • 咨询
    • 託管服务

第六章 全球边缘人工智慧市场（按处理器类型划分）

  • CPU
  • GPU
  • FPGA
  • ASIC

第七章 全球边缘人工智慧市场（按应用划分）

  • 智慧城市
    • 交通管理
    • 监测
    • 公共
  • 车
    • ADAS
    • 自动驾驶
    • 车载资讯娱乐系统
  • 家用电子电器
    • 智慧型手机
    • 穿戴式装置
    • AR/VR设备
  • 工业IoT
    • 预测性维护
    • 机器人技术
    • 流程自动化
  • 医疗保健
    • 远端监控
    • 诊断
    • 医学影像
  • 零售

第八章 全球边缘人工智慧市场（按最终用户划分）

  • 电讯
  • 能源与公共产业
  • 製造业
  • 国防/航太
  • 运输/物流
  • 其他最终用户

第九章 全球边缘人工智慧市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美国家
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十章：重大进展

  • 协议、伙伴关係、合作和合资企业
  • 併购
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十一章 企业概况

  • Microsoft
  • Hewlett Packard Enterprise（HPE）
  • Google
  • Schneider Electric
  • Amazon Web Services（AWS）
  • Siemens
  • IBM
  • Cisco Systems
  • Intel
  • Arm
  • NVIDIA
  • Apple
  • Qualcomm
  • Samsung Electronics
  • Huawei
Product Code: SMRC32677

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

List of Tables

  • Table 1 Global Edge AI Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Edge AI Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Edge AI Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 4 Global Edge AI Market Outlook, By Edge Servers (2024-2032) ($MN)
  • Table 5 Global Edge AI Market Outlook, By Gateways (2024-2032) ($MN)
  • Table 6 Global Edge AI Market Outlook, By Sensors (2024-2032) ($MN)
  • Table 7 Global Edge AI Market Outlook, By AI Chips (2024-2032) ($MN)
  • Table 8 Global Edge AI Market Outlook, By Software (2024-2032) ($MN)
  • Table 9 Global Edge AI Market Outlook, By AI Frameworks (2024-2032) ($MN)
  • Table 10 Global Edge AI Market Outlook, By SDKs (2024-2032) ($MN)
  • Table 11 Global Edge AI Market Outlook, By Middleware (2024-2032) ($MN)
  • Table 12 Global Edge AI Market Outlook, By Edge Orchestration Platforms (2024-2032) ($MN)
  • Table 13 Global Edge AI Market Outlook, By Services (2024-2032) ($MN)
  • Table 14 Global Edge AI Market Outlook, By Deployment (2024-2032) ($MN)
  • Table 15 Global Edge AI Market Outlook, By Integration (2024-2032) ($MN)
  • Table 16 Global Edge AI Market Outlook, By Consulting (2024-2032) ($MN)
  • Table 17 Global Edge AI Market Outlook, By Managed Services (2024-2032) ($MN)
  • Table 18 Global Edge AI Market Outlook, By Processor Type (2024-2032) ($MN)
  • Table 19 Global Edge AI Market Outlook, By CPU (2024-2032) ($MN)
  • Table 20 Global Edge AI Market Outlook, By GPU (2024-2032) ($MN)
  • Table 21 Global Edge AI Market Outlook, By FPGA (2024-2032) ($MN)
  • Table 22 Global Edge AI Market Outlook, By ASIC (2024-2032) ($MN)
  • Table 23 Global Edge AI Market Outlook, By Application (2024-2032) ($MN)
  • Table 24 Global Edge AI Market Outlook, By Smart Cities (2024-2032) ($MN)
  • Table 25 Global Edge AI Market Outlook, By Traffic Management (2024-2032) ($MN)
  • Table 26 Global Edge AI Market Outlook, By Surveillance (2024-2032) ($MN)
  • Table 27 Global Edge AI Market Outlook, By Public Safety (2024-2032) ($MN)
  • Table 28 Global Edge AI Market Outlook, By Automotive (2024-2032) ($MN)
  • Table 29 Global Edge AI Market Outlook, By ADAS (2024-2032) ($MN)
  • Table 30 Global Edge AI Market Outlook, By Autonomous Driving (2024-2032) ($MN)
  • Table 31 Global Edge AI Market Outlook, By In-Vehicle Infotainment (2024-2032) ($MN)
  • Table 32 Global Edge AI Market Outlook, By Consumer Electronics (2024-2032) ($MN)
  • Table 33 Global Edge AI Market Outlook, By Smartphones (2024-2032) ($MN)
  • Table 34 Global Edge AI Market Outlook, By Wearables (2024-2032) ($MN)
  • Table 35 Global Edge AI Market Outlook, By AR/VR Devices (2024-2032) ($MN)
  • Table 36 Global Edge AI Market Outlook, By Industrial IoT (2024-2032) ($MN)
  • Table 37 Global Edge AI Market Outlook, By Predictive Maintenance (2024-2032) ($MN)
  • Table 38 Global Edge AI Market Outlook, By Robotics (2024-2032) ($MN)
  • Table 39 Global Edge AI Market Outlook, By Process Automation (2024-2032) ($MN)
  • Table 40 Global Edge AI Market Outlook, By Healthcare (2024-2032) ($MN)
  • Table 41 Global Edge AI Market Outlook, By Remote Monitoring (2024-2032) ($MN)
  • Table 42 Global Edge AI Market Outlook, By Diagnostics (2024-2032) ($MN)
  • Table 43 Global Edge AI Market Outlook, By Medical Imaging (2024-2032) ($MN)
  • Table 44 Global Edge AI Market Outlook, By Retail (2024-2032) ($MN)
  • Table 45 Global Edge AI Market Outlook, By End User (2024-2032) ($MN)
  • Table 46 Global Edge AI Market Outlook, By Telecom (2024-2032) ($MN)
  • Table 47 Global Edge AI Market Outlook, By Energy And Utilities (2024-2032) ($MN)
  • Table 48 Global Edge AI Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 49 Global Edge AI Market Outlook, By Defense And Aerospace (2024-2032) ($MN)
  • Table 50 Global Edge AI Market Outlook, By Transportation And Logistics (2024-2032) ($MN)
  • Table 51 Global Edge AI Market Outlook, By Other End Users (2024-2032) ($MN)

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