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市場調查報告書
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1914625

邊緣人工智慧硬體市場－全球產業規模、佔有率、趨勢、機會及預測（依設備、功耗、功能、處理器、垂直產業、區域和競爭格局分類），2021-2031年

Edge AI Hardware Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Device, By Power Consumption, By Function, By Processor, By Vertical, By Region & Competition, 2021-2031F
出版日期: | 出版商: TechSci Research | 英文 180 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球邊緣人工智慧硬體市場預計將從2025年的261.1億美元大幅成長至2031年的688.5億美元，複合年成長率（CAGR）達17.54%。此細分市場涵蓋專用實體元件，具體包括神經處理單元（NPU）、圖形處理單元（GPU）和專用積體電路（ASIC），這些元件旨在本地處理機器學習演算法，而無需依賴集中式雲端連接。推動該市場成長的根本因素是決策流程中對超低延遲的迫切需求，以及透過減少資料傳輸需求來最佳化頻寬利用率的驅動。此外，嚴格的資料隱私法規的實施和物聯網（IoT）設備的指數級成長也發揮了重要的催化作用，從而催生了對強大的設備端處理能力的迫切需求。

市場概覽
預測期 2027-2031
市場規模：2025年 261.1億美元
市場規模：2031年 688.5億美元
複合年成長率：2026-2031年 17.54%
成長最快的細分市場 智慧型手機
最大的市場 北美洲

然而，在能源效率方面，它們面臨著巨大的挑戰，因為將高效能運算整合到資源受限的電池供電設備中是一項艱鉅的技術難題。硬體需求的激增反映了整個晶片行業的趨勢。根據半導體產業協會（SIA）預測，到2024年，全球半導體銷售額將達到6,276億美元，這數字主要受汽車和工業領域對人工智慧能力的爆炸性需求所驅動。對底層矽晶片的如此大規模的資本投入，凸顯了整個產業向智慧分散式硬體架構轉型的趨勢。

市場促進因素

物聯網和智慧互聯設備的快速擴張正成為邊緣人工智慧硬體市場的關鍵加速器，有效地將處理工作負載從集中式雲端基礎設施轉移到本地環境。隨著數十億感測器和終端部署在工業應用中，傳輸原始資料相關的延遲和頻寬成本已達到難以承受的程度，因此亟需採用片上處理解決方案。這種分散式策略能夠實現即時數據過濾和分析，這對於從智慧城市基礎設施到工業監控系統等各種應用至關重要。互聯終端數量的龐大也凸顯了這個趨勢的規模。根據愛立信於2024年6月發布的《行動報告》，預計到2025年底，蜂巢式物聯網連接總數將達到約45億，這迫切需要能夠在網路邊緣實現低功耗、高效能推理的硬體。

同時，人工智慧在自動駕駛汽車和機器人領域的日益融合，正推動硬體朝著兼具高性能和高能效的推理引擎方向發展。這些自主系統依靠先進的神經網路在非結構化環境中安全導航，從而帶動了對專用神經網路處理器（NPU）和圖形處理器（GPU）的需求，這些處理器無需依賴網路即可執行複雜的邏輯運算。根據國際機器人聯合會（IFR）於2024年9月發布的《2024年世界運作報告》，2023年全球工業機器人數量將達到創紀錄的428萬台，顯示智慧自動化的基礎正在不斷深化。為了滿足這些應用所需的計算強度，記憶體頻寬和處理速度都至關重要。事實上，世界半導體貿易統計（WSTS）2024年12月的預測顯示，2024年記憶體積體電路市場將成長81.0%，這凸顯了基礎設施調整以支援高階人工智慧工作負載的必要性。

市場挑戰

能源效率仍是全球邊緣人工智慧硬體市場成長的一大障礙。製造商在尋求將先進的機器學習功能嵌入小型設備時，面臨著一個固有的權衡：既要提供高運算效能，也要保持低功耗。邊緣設備，尤其是那些用於遠端工業設施和穿戴式技術的設備，通常依賴有限的電池供電。即時人工智慧推理所需的繁重處理會迅速消耗這些電量，從而縮短硬體的運作並降低其可靠性。這種技術限制阻礙了潛在買家在關鍵任務應用中部署智慧邊緣解決方案，因為這些應用需要持續運作，從而影響了邊緣解決方案的商業性化應用。

這場電力挑戰的嚴峻性從待升級設備生態系統的龐大規模可見一斑。根據GSMA預測，到2024年，企業級物聯網連接數將達到107億，這將建構一個龐大的基礎設施，而高效運作需要節能的處理能力。除非開發出既能提供高效能又能嚴格控制功耗的硬體，否則如此龐大的連網設備將無法充分利用分散式人工智慧，從而直接限制市場的成長潛力。

市場趨勢

將專用神經處理單元 (NPU) 整合到行動系統晶片 (SoC) 中，正透過實現設備內複雜推理，為生成式人工智慧 (AI) 應用帶來革命性的變革。製造商正擴大將高效加速器直接嵌入智慧型手機處理器中，以本地處理即時語言翻譯和影像處理等任務，從而顯著降低延遲並減少對雲端服務的依賴。這種架構轉變正在推動商業性的重大升級，消費者對人工智慧旗艦設備的強勁需求便是最好的證明。正如三星電子在 2025 年 1 月發布的《2024 會計年度第四季及全年財務報告》中所述，該公司銷售業績強勁，其搭載 Galaxy AI 的旗艦 Galaxy S24 系列實現了兩位數成長，凸顯了市場向硬體賦能智慧的快速轉型。

同時，晶片組技術和異質整合技術的應用正在重新定義半導體設計，以克服邊緣硬體單晶粒在物理和經濟上的規模限制。透過將採用不同製程節點製造的小型模組化晶粒整合到單一封裝中，工程師可以提高產量比率，同時針對特定的人工智慧工作負載最佳化效能和成本。這種製造技術的演進對於滿足用於高效能運算的下一代邊緣處理器的頻寬和互連需求至關重要。根據台積電在2025年1月舉行的“2024年第四季財報電話會議”，該公司預測，在高效能運算解決方案的持續需求驅動下，到2025年，支持這些異質架構的先進封裝技術帶來的收入將超過其總收入的10%。

目錄

第1章概述

第2章調查方法

第3章執行摘要

第4章：客戶評價

第5章 全球邊緣人工智慧硬體市場展望

  • 市場規模及預測
    • 按金額
  • 市佔率及預測
    • 依裝置分類（智慧型手機、機器人、監視錄影機、穿戴式裝置、智慧音箱、汽車、智慧鏡子等）
    • 依功耗（小於1W、1-3W、3-5W、3-5W、大於10W）
    • 按功能（訓練、推理）
    • 按處理器類型（CPU、GPU、ASIC、其他）
    • 按產業分類（醫療保健與生命科學、零售與家用電子電器、汽車與運輸、航太與國防、政府、建築、其他）
    • 按地區
    • 按公司（2025 年）
  • 市場地圖

第6章：北美邊緣人工智慧硬體市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 北美洲：國家分析
    • 美國
    • 加拿大
    • 墨西哥

第7章：歐洲邊緣人工智慧硬體市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 歐洲：國家分析
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙

第8章：亞太邊緣人工智慧硬體市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 亞太地區：國家分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲

第9章：中東和非洲邊緣人工智慧硬體市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 中東和非洲：國家分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第10章：南美邊緣人工智慧硬體市場展望

  • 市場規模及預測
  • 市佔率及預測
  • 南美洲：國家分析
    • 巴西
    • 哥倫比亞
    • 阿根廷

第11章 市場動態

  • 促進要素
  • 任務

第12章 市場趨勢與發展

  • 併購
  • 產品發布
  • 最新進展

第13章：全球邊緣人工智慧硬體市場：SWOT分析

第14章：波特五力分析

  • 產業競爭
  • 新進入者的可能性
  • 供應商電力
  • 顧客權力
  • 替代品的威脅

第15章 競爭格局

  • Qualcomm Technologies, Inc.
  • Huawei Technologies Co. Ltd.
  • Samsung Electronics Co. Ltd.
  • MediaTek Inc.
  • International Business Machines Corporation
  • Microsoft Corporation
  • NVIDIA Corporation
  • Google LLC
  • Apple Inc.
  • Intel Corporation

第16章 策略建議

第17章：關於研究公司及免責聲明

簡介目錄
Product Code: 15196

The Global Edge AI Hardware Market is projected to expand significantly, rising from a valuation of USD 26.11 Billion in 2025 to USD 68.85 Billion by 2031, reflecting a compound annual growth rate (CAGR) of 17.54%. This sector encompasses specialized physical components-specifically neural processing units (NPUs), graphics processing units (GPUs), and application-specific integrated circuits (ASICs)-engineered to process machine learning algorithms locally rather than depending on centralized cloud connectivity. The fundamental momentum behind this market stems from the urgent necessity for ultra-low latency in real-time decision-making processes and the drive to optimize bandwidth usage by reducing data transmission requirements. Additionally, the enforcement of strict data privacy regulations and the exponential increase in Internet of Things (IoT) devices act as primary catalysts, creating a distinct need for robust, on-device processing capabilities.

Market Overview
Forecast Period2027-2031
Market Size 2025USD 26.11 Billion
Market Size 2031USD 68.85 Billion
CAGR 2026-203117.54%
Fastest Growing SegmentSmartphones
Largest MarketNorth America

However, the market faces a substantial hurdle regarding power efficiency, as incorporating high-performance computing into resource-constrained, battery-powered devices presents significant technical difficulties. This surge in hardware demand mirrors trends in the wider chip industry; according to the Semiconductor Industry Association, global semiconductor sales hit $627.6 billion in 2024, a figure largely propelled by the explosive demand for artificial intelligence capabilities within automotive and industrial sectors. Such massive capital investment in foundational silicon underscores the industrial-scale transition toward intelligent, decentralized hardware architectures.

Market Driver

The rapid expansion of IoT and smart connected devices serves as a major accelerator for the Edge AI Hardware market, effectively migrating processing workloads from centralized cloud infrastructures to local environments. As industries implement billions of sensors and endpoints, the costs related to latency and bandwidth for transmitting raw data become unmanageable, thereby mandating on-chip processing solutions. This decentralized strategy enables immediate data filtering and analysis, a capability essential for diverse applications from smart city infrastructure to industrial monitoring systems. The scale of this trend is highlighted by the sheer volume of connected endpoints; the "Ericsson Mobility Report" from June 2024 estimates that total cellular IoT connections will reach roughly 4.5 billion by the end of 2025, creating an urgent need for hardware that delivers low-power, high-performance inference at the network edge.

Concurrently, the increasing incorporation of AI into autonomous vehicles and robotics is compelling a hardware evolution toward inference engines that balance high performance with energy efficiency. These autonomous systems depend on advanced neural networks to safely traverse unstructured environments, fueling the demand for specialized NPUs and GPUs capable of complex logic execution without network reliance. According to the International Federation of Robotics (IFR) "World Robotics 2024" report released in September 2024, the global operational stock of industrial robots hit a record 4.28 million units in 2023, signaling a deepening base for intelligent automation. To sustain the computational intensity these applications require, memory bandwidth has become as vital as processing speed; in fact, the World Semiconductor Trade Statistics (WSTS) December 2024 forecast projected the memory integrated circuit segment would jump by 81.0% in 2024, emphasizing the infrastructure adjustments necessary to support advanced AI workloads.

Market Challenge

The issue of power efficiency remains a formidable barrier restricting the growth of the Global Edge AI Hardware Market. As manufacturers attempt to embed sophisticated machine learning features into compact devices, they encounter an inherent conflict between achieving high computational performance and maintaining low energy consumption. Edge devices, especially those utilized in remote industrial locations or wearable technology, often depend on limited battery power. The intensive processing needed for real-time AI inference rapidly depletes these energy reserves, thereby diminishing the hardware's operational lifespan and reliability. This technical limitation causes hesitation among potential buyers regarding the adoption of intelligent edge solutions for mission-critical operations where uninterrupted uptime is essential, consequently stalling widespread commercial acceptance.

The severity of this power challenge is highlighted by the massive scale of the device ecosystem awaiting upgrades. According to the GSMA, the enterprise segment accounted for 10.7 billion IoT connections in 2024, representing a vast infrastructure that necessitates energy-efficient processing to operate effectively. Unless hardware is developed that can provide high-level performance while rigorously managing power consumption, this enormous volume of connected devices will be unable to fully utilize decentralized AI, directly limiting the market's total addressable growth potential.

Market Trends

The integration of dedicated Neural Processing Units (NPUs) into Mobile SoCs is revolutionizing consumer electronics by facilitating complex on-device inference for generative AI applications. Manufacturers are increasingly embedding high-efficiency accelerators directly within smartphone processors to manage tasks such as real-time language translation and image manipulation locally, which significantly reduces latency and reliance on cloud services. This architectural transition is fueling substantial commercial upgrades, illustrated by strong consumer demand for AI-enabled flagship devices. As noted in Samsung Electronics' "Fourth Quarter and FY 2024 Results" report from January 2025, the company observed robust sales performance, with the flagship Galaxy S24 series featuring Galaxy AI achieving double-digit growth, highlighting the market's rapid shift toward hardware-enabled intelligence.

Simultaneously, the adoption of Chiplet Technology and Heterogeneous Integration is redefining semiconductor design to surpass the physical and economic scaling limitations associated with monolithic dies in edge hardware. By amalgamating smaller, modular dies manufactured on distinct process nodes into a single package, engineers can fine-tune performance and costs for specific AI workloads while enhancing yield rates. This evolution in manufacturing is essential for meeting the bandwidth and interconnect demands of next-generation edge processors utilized in high-performance computing. According to the TSMC "Fourth Quarter 2024 Earnings Conference" in January 2025, the company projected that revenue from advanced packaging technologies-which support these heterogeneous architectures-would surpass 10% of its total revenue in 2025, driven by sustained demand for high-performance computing solutions.

Key Market Players

  • Qualcomm Technologies, Inc.
  • Huawei Technologies Co. Ltd.
  • Samsung Electronics Co. Ltd.
  • MediaTek Inc.
  • International Business Machines Corporation
  • Microsoft Corporation
  • NVIDIA Corporation
  • Google LLC
  • Apple Inc.
  • Intel Corporation

Report Scope

In this report, the Global Edge AI Hardware Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Edge AI Hardware Market, By Device

  • Smartphones
  • Robots
  • Surveillance Cameras
  • Wearables
  • Smart Speakers
  • Automotive
  • Smart Mirrors
  • Others

Edge AI Hardware Market, By Power Consumption

  • Less Than 1W
  • 1-3W
  • 3-5W
  • 3-5W
  • More Than 10W

Edge AI Hardware Market, By Function

  • Training
  • Inference

Edge AI Hardware Market, By Processor

  • CPU
  • GPU
  • ASIC
  • Others

Edge AI Hardware Market, By Vertical

  • Healthcare & Life Science
  • Retail & Consumer Electronics
  • Automotive & Transportation
  • Aerospace & Defense
  • Government
  • Construction
  • Others

Edge AI Hardware Market, By Region

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • France
    • United Kingdom
    • Italy
    • Germany
    • Spain
  • Asia Pacific
    • China
    • India
    • Japan
    • Australia
    • South Korea
  • South America
    • Brazil
    • Argentina
    • Colombia
  • Middle East & Africa
    • South Africa
    • Saudi Arabia
    • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Edge AI Hardware Market.

Available Customizations:

Global Edge AI Hardware Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Edge AI Hardware Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Device (Smartphones, Robots, Surveillance Cameras, Wearables, Smart Speakers, Automotive, Smart Mirrors, Others)
    • 5.2.2. By Power Consumption (Less Than 1W, 1-3W, 3-5W, 3-5W, More Than 10W)
    • 5.2.3. By Function (Training, Inference)
    • 5.2.4. By Processor (CPU, GPU, ASIC, Others)
    • 5.2.5. By Vertical (Healthcare & Life Science, Retail & Consumer Electronics, Automotive & Transportation, Aerospace & Defense, Government, Construction, Others)
    • 5.2.6. By Region
    • 5.2.7. By Company (2025)
  • 5.3. Market Map

6. North America Edge AI Hardware Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Device
    • 6.2.2. By Power Consumption
    • 6.2.3. By Function
    • 6.2.4. By Processor
    • 6.2.5. By Vertical
    • 6.2.6. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States Edge AI Hardware Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Device
        • 6.3.1.2.2. By Power Consumption
        • 6.3.1.2.3. By Function
        • 6.3.1.2.4. By Processor
        • 6.3.1.2.5. By Vertical
    • 6.3.2. Canada Edge AI Hardware Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Device
        • 6.3.2.2.2. By Power Consumption
        • 6.3.2.2.3. By Function
        • 6.3.2.2.4. By Processor
        • 6.3.2.2.5. By Vertical
    • 6.3.3. Mexico Edge AI Hardware Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Device
        • 6.3.3.2.2. By Power Consumption
        • 6.3.3.2.3. By Function
        • 6.3.3.2.4. By Processor
        • 6.3.3.2.5. By Vertical

7. Europe Edge AI Hardware Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Device
    • 7.2.2. By Power Consumption
    • 7.2.3. By Function
    • 7.2.4. By Processor
    • 7.2.5. By Vertical
    • 7.2.6. By Country
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany Edge AI Hardware Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Device
        • 7.3.1.2.2. By Power Consumption
        • 7.3.1.2.3. By Function
        • 7.3.1.2.4. By Processor
        • 7.3.1.2.5. By Vertical
    • 7.3.2. France Edge AI Hardware Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Device
        • 7.3.2.2.2. By Power Consumption
        • 7.3.2.2.3. By Function
        • 7.3.2.2.4. By Processor
        • 7.3.2.2.5. By Vertical
    • 7.3.3. United Kingdom Edge AI Hardware Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Device
        • 7.3.3.2.2. By Power Consumption
        • 7.3.3.2.3. By Function
        • 7.3.3.2.4. By Processor
        • 7.3.3.2.5. By Vertical
    • 7.3.4. Italy Edge AI Hardware Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Device
        • 7.3.4.2.2. By Power Consumption
        • 7.3.4.2.3. By Function
        • 7.3.4.2.4. By Processor
        • 7.3.4.2.5. By Vertical
    • 7.3.5. Spain Edge AI Hardware Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Device
        • 7.3.5.2.2. By Power Consumption
        • 7.3.5.2.3. By Function
        • 7.3.5.2.4. By Processor
        • 7.3.5.2.5. By Vertical

8. Asia Pacific Edge AI Hardware Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Device
    • 8.2.2. By Power Consumption
    • 8.2.3. By Function
    • 8.2.4. By Processor
    • 8.2.5. By Vertical
    • 8.2.6. By Country
  • 8.3. Asia Pacific: Country Analysis
    • 8.3.1. China Edge AI Hardware Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Device
        • 8.3.1.2.2. By Power Consumption
        • 8.3.1.2.3. By Function
        • 8.3.1.2.4. By Processor
        • 8.3.1.2.5. By Vertical
    • 8.3.2. India Edge AI Hardware Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Device
        • 8.3.2.2.2. By Power Consumption
        • 8.3.2.2.3. By Function
        • 8.3.2.2.4. By Processor
        • 8.3.2.2.5. By Vertical
    • 8.3.3. Japan Edge AI Hardware Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Device
        • 8.3.3.2.2. By Power Consumption
        • 8.3.3.2.3. By Function
        • 8.3.3.2.4. By Processor
        • 8.3.3.2.5. By Vertical
    • 8.3.4. South Korea Edge AI Hardware Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Device
        • 8.3.4.2.2. By Power Consumption
        • 8.3.4.2.3. By Function
        • 8.3.4.2.4. By Processor
        • 8.3.4.2.5. By Vertical
    • 8.3.5. Australia Edge AI Hardware Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Device
        • 8.3.5.2.2. By Power Consumption
        • 8.3.5.2.3. By Function
        • 8.3.5.2.4. By Processor
        • 8.3.5.2.5. By Vertical

9. Middle East & Africa Edge AI Hardware Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Device
    • 9.2.2. By Power Consumption
    • 9.2.3. By Function
    • 9.2.4. By Processor
    • 9.2.5. By Vertical
    • 9.2.6. By Country
  • 9.3. Middle East & Africa: Country Analysis
    • 9.3.1. Saudi Arabia Edge AI Hardware Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Device
        • 9.3.1.2.2. By Power Consumption
        • 9.3.1.2.3. By Function
        • 9.3.1.2.4. By Processor
        • 9.3.1.2.5. By Vertical
    • 9.3.2. UAE Edge AI Hardware Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Device
        • 9.3.2.2.2. By Power Consumption
        • 9.3.2.2.3. By Function
        • 9.3.2.2.4. By Processor
        • 9.3.2.2.5. By Vertical
    • 9.3.3. South Africa Edge AI Hardware Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Device
        • 9.3.3.2.2. By Power Consumption
        • 9.3.3.2.3. By Function
        • 9.3.3.2.4. By Processor
        • 9.3.3.2.5. By Vertical

10. South America Edge AI Hardware Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Device
    • 10.2.2. By Power Consumption
    • 10.2.3. By Function
    • 10.2.4. By Processor
    • 10.2.5. By Vertical
    • 10.2.6. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Edge AI Hardware Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Device
        • 10.3.1.2.2. By Power Consumption
        • 10.3.1.2.3. By Function
        • 10.3.1.2.4. By Processor
        • 10.3.1.2.5. By Vertical
    • 10.3.2. Colombia Edge AI Hardware Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Device
        • 10.3.2.2.2. By Power Consumption
        • 10.3.2.2.3. By Function
        • 10.3.2.2.4. By Processor
        • 10.3.2.2.5. By Vertical
    • 10.3.3. Argentina Edge AI Hardware Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Device
        • 10.3.3.2.2. By Power Consumption
        • 10.3.3.2.3. By Function
        • 10.3.3.2.4. By Processor
        • 10.3.3.2.5. By Vertical

11. Market Dynamics

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends & Developments

  • 12.1. Merger & Acquisition (If Any)
  • 12.2. Product Launches (If Any)
  • 12.3. Recent Developments

13. Global Edge AI Hardware Market: SWOT Analysis

14. Porter's Five Forces Analysis

  • 14.1. Competition in the Industry
  • 14.2. Potential of New Entrants
  • 14.3. Power of Suppliers
  • 14.4. Power of Customers
  • 14.5. Threat of Substitute Products

15. Competitive Landscape

  • 15.1. Qualcomm Technologies, Inc.
    • 15.1.1. Business Overview
    • 15.1.2. Products & Services
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel
    • 15.1.5. SWOT Analysis
  • 15.2. Huawei Technologies Co. Ltd.
  • 15.3. Samsung Electronics Co. Ltd.
  • 15.4. MediaTek Inc.
  • 15.5. International Business Machines Corporation
  • 15.6. Microsoft Corporation
  • 15.7. NVIDIA Corporation
  • 15.8. Google LLC
  • 15.9. Apple Inc.
  • 15.10. Intel Corporation

16. Strategic Recommendations

17. About Us & Disclaimer