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市场调查报告书
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1698324

人工智慧（AI）终端市场机会、成长动力、产业趋势分析及2025-2034年预测

Artificial Intelligence (AI) Terminal Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025-2034
出版日期: | 出版商: Global Market Insights Inc. | 英文 190 Pages | 商品交期: 2-3个工作天内

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简介目录

2024 年全球人工智慧终端市场价值为 222 亿美元，预计 2025 年至 2034 年的复合年增长率将达到 19.6%。成长得益于人工智慧晶片组、神经处理单元 (NPU) 和人工智慧加速器的进步，这些进步在提高效能的同时也提高了能源效率。 AI终端受益于边缘AI，它在本地处理资料，减少对云端运算的依赖。这可以提高回应时间，增强安全性，并使企业能够实现低延迟的 AI 处理以进行即时决策。人工智慧物联网设备、消费性电子产品和智慧医疗解决方案的日益普及促进了市场扩张。人工智慧处理器的技术进步使得人工智慧终端成为下一代运算的关键。

人工智慧（AI）终端市场 - IMG1

市场依组件分为硬体和软体。 2024 年，硬体将占据该领域的主导地位，创造 152 亿美元的收入，预计在预测期内的复合年增长率为 19.9%。 AI终端依赖强大的处理器，包括GPU、FPGA和ASIC，这些处理器对于即时AI运算至关重要。汽车、医疗保健和製造等行业正在整合人工智慧推理硬件，以支援自动化并增强基于人工智慧的决策。对人工智慧晶片组、嵌入式设备和支援人工智慧的伺服器的投资增加进一步巩固了硬体的主导地位。人工智慧物联网、自主系统和人工智慧驱动的监控解决方案的扩展也在推动成长，从而加强了金融科技人工智慧硬体市场。

市场范围
起始年份 2024
预测年份 2025-2034
起始值 222亿美元
预测值 1035亿美元
复合年增长率 19.6%

AI终端市场部署模式包括本地部署、云端部署、混合式部署等。 2024 年，基于云端的解决方案以 47% 的份额引领市场，预计到 2034 年将以超过 20% 的复合年增长率成长。云端运算使企业无需大量硬体投资即可扩展 AI 应用，支援跨多个行业的 AI 模型训练、即时资料分析和推理。随着企业产生越来越多的人工智慧驱动资料，对云端基础设施的需求持续上升。与云端系统整合的AI终端，能够有效率地收集和处理资料，成为企业寻求高阶AI能力的必备工具。

根据技术，市场细分为机器学习 (ML) 和深度学习 (DL)、电脑视觉、机器人流程自动化、物联网感测器和其他人工智慧驱动技术。 ML 和 DL 仍然占据主导地位，因为它们能够处理大量资料、识别模式并即时执行操作。利用深度学习神经网路的人工智慧系统增强了自然语言处理 (NLP)、语音辨识和自主系统的能力。银行、零售和医疗保健领域对人工智慧解决方案的需求日益增长，正在加速该领域的应用。

2024年北美占最大市场份额，约占全球AI终端市场的40%，创造约90亿美元的收入。该地区受益于对人工智慧驱动硬体、边缘运算解决方案和半导体技术的大力投资。领先的科技公司和人工智慧晶片组製造商的存在支持了医疗保健、国防和零售等各个行业的市场扩张。基于边缘的人工智慧运算解决方案的增强开发进一步推动了其应用，特别是在需要改进资料隐私和安全性的应用中。

目录

第一章：方法论与范围

  • 研究设计
    • 研究方法
    • 资料收集方法
  • 基础估算与计算
    • 基准年计算
    • 市场估计的主要趋势
  • 预测模型
  • 初步研究与验证
    • 主要来源
    • 资料探勘来源
  • 市场定义

第二章：执行摘要

第三章：行业洞察

  • 产业生态系统分析
  • 供应商格局
    • 製造商
    • 感测器提供者
    • 软体开发者
    • 技术整合商
    • 最终用途
  • 利润率分析
  • 技术与创新格局
  • 专利分析
  • 重要新闻和倡议
  • 监管格局
  • 衝击力
    • 成长动力
      • 边缘人工智慧技术的进步
      • 对人工智慧设备的需求不断增长
      • 5G和物联网网路的扩展
      • 汽车和医疗保健领域人工智慧的融合日益加强
      • 政府和企业对人工智慧基础设施的投资
    • 产业陷阱与挑战
      • 初期投资和部署成本高
      • 资料隐私和安全问题
  • 成长潜力分析
  • 波特的分析
  • PESTEL 分析

第四章：竞争格局

  • 介绍
  • 公司市占率分析
  • 竞争定位矩阵
  • 战略展望矩阵

第五章：市场估计与预测：按组件，2021 - 2034 年

  • 主要趋势
  • 硬体
  • 软体

第六章：市场估计与预测：依技术分类，2021 - 2034 年

  • 主要趋势
  • 机器学习和深度学习
  • 电脑视觉
  • 机器人流程自动化
  • 物联网感测器
  • 其他的

第七章：市场估计与预测：依部署模式，2021 - 2034 年

  • 主要趋势
  • 本地
  • 基于云端
  • 杂交种

第八章：市场估计与预测：依最终用途，2021 - 2034 年

  • 主要趋势
  • 运输
  • 卫生保健
  • 零售
  • 金融服务业
  • 其他的

第九章：市场估计与预测：按地区，2021 - 2034 年

  • 主要趋势
  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 俄罗斯
    • 北欧人
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳新银行
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • 中东及非洲
    • 阿联酋
    • 沙乌地阿拉伯
    • 南非

第十章：公司简介

  • Adobe
  • Alibaba Group
  • Amazon
  • Apple
  • Bosch
  • Cisco
  • Dell Technologies
  • Google (Alphabet inc.)
  • Huawei Technologies
  • IBM
  • Intel
  • Meta Platforms
  • Microsoft
  • Nvidia
  • Oracle
  • Sony
  • Tencent Holdings
  • Tesla
  • VMware
  • Zoom Video Communications
简介目录
Product Code: 13176

The Global Artificial Intelligence Terminal Market was valued at USD 22.2 billion in 2024 and is expected to expand at a CAGR of 19.6% from 2025 to 2034. Growth is fueled by advancements in AI chipsets, neural processing units (NPUs), and AI accelerators, which enhance performance while improving energy efficiency. AI terminals benefit from edge AI, which processes data locally, reducing reliance on cloud computing. This improves response times, strengthens security, and enables businesses to achieve low-latency AI processing for real-time decision-making. Increasing adoption of AI-powered IoT devices, consumer electronics, and smart healthcare solutions contributes to market expansion. Technological improvements in AI processors are making AI terminals essential for next-generation computing.

Artificial Intelligence (AI) Terminal Market - IMG1

The market is categorized by component into hardware and software. In 2024, hardware dominated the sector, generating USD 15.2 billion in revenue, and is projected to grow at a CAGR of 19.9% through the forecast period. AI terminals rely on powerful processors, including GPUs, FPGAs, and ASICs, which are crucial for real-time AI computations. Industries such as automotive, healthcare, and manufacturing are integrating AI inference hardware to support automation and enhance AI-based decision-making. Increased investments in AI chipsets, embedded devices, and AI-enabled servers further reinforce hardware's dominance. The expansion of AIoT, autonomous systems, and AI-driven surveillance solutions is also driving growth, strengthening the market for fintech AI hardware.

Market Scope
Start Year2024
Forecast Year2025-2034
Start Value$22.2 Billion
Forecast Value$103.5 Billion
CAGR19.6%

Deployment modes in the AI terminal market include on-premises, cloud-based, and hybrid solutions. In 2024, cloud-based solutions led the market with a 47% share and are expected to grow at a CAGR exceeding 20% through 2034. Cloud computing allows enterprises to scale AI applications without substantial hardware investments, supporting AI model training, real-time data analysis, and inference across multiple industries. As businesses generate increasing amounts of AI-driven data, demand for cloud infrastructure continues to rise. AI terminals integrated with cloud-based systems enable efficient data collection and processing, making them an essential tool for enterprises seeking advanced AI capabilities.

By technology, the market is segmented into machine learning (ML) and deep learning (DL), computer vision, robotic process automation, IoT sensors, and other AI-driven technologies. ML and DL remain dominant due to their ability to process vast amounts of data, identify patterns, and execute actions in real-time. AI systems utilizing deep learning neural networks enhance capabilities in natural language processing (NLP), speech recognition, and autonomous systems. The increasing need for AI solutions across banking, retail, and healthcare is accelerating adoption in this segment.

North America held the largest market share in 2024, accounting for approximately 40% of the global AI terminal market, generating around USD 9 billion in revenue. The region benefits from strong investments in AI-driven hardware, edge computing solutions, and semiconductor technologies. The presence of leading technology firms and AI chipset manufacturers supports market expansion across industries, including healthcare, defense, and retail. Enhanced development of edge-based AI computing solutions is further fueling adoption, particularly in applications requiring improved data privacy and security.

Table of Contents

Chapter 1 Methodology & Scope

  • 1.1 Research design
    • 1.1.1 Research approach
    • 1.1.2 Data collection methods
  • 1.2 Base estimates and calculations
    • 1.2.1 Base year calculation
    • 1.2.2 Key trends for market estimates
  • 1.3 Forecast model
  • 1.4 Primary research & validation
    • 1.4.1 Primary sources
    • 1.4.2 Data mining sources
  • 1.5 Market definitions

Chapter 2 Executive Summary

  • 2.1 Industry 3600 synopsis, 2021 - 2034

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
  • 3.2 Supplier landscape
    • 3.2.1 Manufacturer
    • 3.2.2 Sensor providers
    • 3.2.3 Software developers
    • 3.2.4 Technology Integrators
    • 3.2.5 End Use
  • 3.3 Profit margin analysis
  • 3.4 Technology & innovation landscape
  • 3.5 Patent analysis
  • 3.6 Key news & initiatives
  • 3.7 Regulatory landscape
  • 3.8 Impact forces
    • 3.8.1 Growth drivers
      • 3.8.1.1 Advancements in edge AI technology
      • 3.8.1.2 Rising demand for AI-powered devices
      • 3.8.1.3 Expansion of 5G and IoT networks
      • 3.8.1.4 Growing AI integration in automotive and healthcare
      • 3.8.1.5 Government and enterprise investments in AI infrastructure
    • 3.8.2 Industry pitfalls & challenges
      • 3.8.2.1 High initial investment and deployment costs
      • 3.8.2.2 Data privacy and security concerns
  • 3.9 Growth potential analysis
  • 3.10 Porter's analysis
  • 3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

  • 4.1 Introduction
  • 4.2 Company market share analysis
  • 4.3 Competitive positioning matrix
  • 4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2034 ($Bn)

  • 5.1 Key trends
  • 5.2 Hardware
  • 5.3 Software

Chapter 6 Market Estimates & Forecast, By Technology, 2021 - 2034 ($Bn)

  • 6.1 Key trends
  • 6.2 ML and DL
  • 6.3 Computer vision
  • 6.4 Robotic process automation
  • 6.5 IOT sensors
  • 6.6 Others

Chapter 7 Market Estimates & Forecast, By Deployment Mode, 2021 - 2034 ($Bn)

  • 7.1 Key trends
  • 7.2 On-premises
  • 7.3 Cloud-based
  • 7.4 Hybrid

Chapter 8 Market Estimates & Forecast, By End Use, 2021 - 2034 ($Bn)

  • 8.1 Key trends
  • 8.2 Transportation
  • 8.3 Healthcare
  • 8.4 Retail
  • 8.5 BFSI
  • 8.6 Others

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2034 ($Bn)

  • 9.1 Key trends
  • 9.2 North America
    • 9.2.1 U.S.
    • 9.2.2 Canada
  • 9.3 Europe
    • 9.3.1 UK
    • 9.3.2 Germany
    • 9.3.3 France
    • 9.3.4 Italy
    • 9.3.5 Spain
    • 9.3.6 Russia
    • 9.3.7 Nordics
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 India
    • 9.4.3 Japan
    • 9.4.4 South Korea
    • 9.4.5 ANZ
  • 9.5 Latin America
    • 9.5.1 Brazil
    • 9.5.2 Mexico
    • 9.5.3 Argentina
  • 9.6 MEA
    • 9.6.1 UAE
    • 9.6.2 Saudi Arabia
    • 9.6.3 South Africa

Chapter 10 Company Profiles

  • 10.1 Adobe
  • 10.2 Alibaba Group
  • 10.3 Amazon
  • 10.4 Apple
  • 10.5 Bosch
  • 10.6 Cisco
  • 10.7 Dell Technologies
  • 10.8 Google (Alphabet inc.)
  • 10.9 Huawei Technologies
  • 10.10 IBM
  • 10.11 Intel
  • 10.12 Meta Platforms
  • 10.13 Microsoft
  • 10.14 Nvidia
  • 10.15 Oracle
  • 10.16 Sony
  • 10.17 Tencent Holdings
  • 10.18 Tesla
  • 10.19 VMware
  • 10.20 Zoom Video Communications