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市场调查报告书
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1858828

以个人化产品为导向的情感人工智慧市场机会、成长驱动因素、产业趋势分析及预测（2025-2034年）

Emotion AI for Personalized Products Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034
出版日期: | 出版商: Global Market Insights Inc. | 英文 250 Pages | 商品交期: 2-3个工作天内

价格
简介目录

2024 年全球个人化产品情感人工智慧市场价值为 30 亿美元，预计到 2034 年将以 21.3% 的复合年增长率成长至 265 亿美元。

面向个人化产品的情感人工智慧市场 - IMG1

随着企业将情感辨识技术融入数位体验，连结人机互动与人工智慧，情感人工智慧市场正在迅速发展。客户服务、医疗保健、零售和汽车等行业对即时情感追踪的需求日益增长，促使企业开发更先进、更注重隐私的工具。主要厂商正在投资多模式人工智慧系统，这些系统结合了脸部分析、语音语调和文字情绪分析，以提供精准的情感洞察。同时，边缘运算和去中心化资料处理的兴起，正在解决人们日益关注的资料隐私和延迟问题。新的法规，尤其是在欧洲等地区，正在影响设计决策，推动合规人工智慧架构的创新。情感人工智慧如今已深度整合到消费品、数位助理、穿戴式装置和企业解决方案中，实现更深层的个人化体验，并提升跨平台互动。随着科技巨头和新创公司竞相提供可扩展的情绪智慧系统，市场竞争日益激烈。

市场范围
起始年份 2024
预测年份 2025-2034
起始值 30亿美元
预测值 265亿美元
复合年增长率 21.3%

到2024年，脸部表情辨识市占率将达到33.9%，预计到2034年将以22.3%的复合年增长率成长。这一增长主要得益于日常产品和系统中摄影机设备的广泛应用，使得非接触式情绪分析成为可能。这些工具依靠深度学习演算法来分析脸部结构、动作和表情，从而提供即时情绪回馈。零售、汽车、消费性电子和安防等行业正在加速采用脸部辨识技术，因为这些工具易于整合且准确率高。

2024年，情绪感知模组市占率达到31.4%，预计在预测期内将以20.6%的复合年增长率成长。这些模组整合了感测器、相机、麦克风和处理器等硬体和软体组件，能够收集和解读情绪资料。随着市场向边缘系统转型，对能够进行即时离线情绪处理的模组的需求日益增长。这些组件构成了情绪人工智慧基础设施的基石，并且正变得越来越精密、节能，以支援穿戴式装置、车载系统和消费性电子设备等各种应用场景。

预计到2024年，北美个人化产品情感人工智慧市场将占据39.3%的份额，复合年增长率（CAGR）将达到20.5%。光是美国就占据了该地区近85%的市场份额，这主要得益于其高额的研发投入、各垂直领域对人工智慧的早期应用以及完善的创新生态系统。 Meta Platforms、NVIDIA、微软、亚马逊网路服务和苹果等主要科技公司正透过持续的产品开发和对人工智慧新创公司的投资，塑造着该地区的市场格局。医疗保健和汽车等行业正在快速采用情感人工智慧，它在心理健康应用、患者监测和车载驾驶员警报系统等领域发挥着越来越重要的作用。

全球个人化产品情感人工智慧市场的主要参与者包括软银机器人集团、Affectiva、Kairos AR、国际商业机器公司（IBM）、Realeyes Data Services、英伟达（NVIDIA）、audEERING、微软、Element Human、亚马逊网路服务（AWS）、Meta Platforms、Eyesight Technologies、Nemesysco、NemephaingNemepha）和苹果。为了保持在该市场的领先地位，领导企业正优先开发多模式演算法，以同时分析脸部、语音和文字线索，从而提高辨识精度。他们还在扩展边缘人工智慧功能，使情感处理能够直接在本地设备上进行，从而降低延迟并保护用户隐私。策略性收购和与新创公司的合作正在加速创新週期。此外，各组织正透过整合差分隐私、联邦学习和合规架构，使解决方案与全球监管趋势保持一致。

目录

第一章：方法论与范围

第二章：执行概要

第三章：行业洞察

  • 产业生态系分析
    • 供应商格局
    • 利润率
    • 每个阶段的价值增加
    • 影响价值链的因素
  • 产业影响因素
    • 成长驱动因素
      • 企业人工智慧应用加速与数位转型
      • 多模态人工智慧发展与技术能力提升
      • 汽车安全法规和驾驶员监控要求
    • 产业陷阱与挑战
      • 隐私问题和监管合规的复杂性
      • 情绪辨识系统中的技术与文化偏见
    • 机会
      • 将情感人工智慧扩展到消费产品领域
      • 即时个人化体验平台
  • 成长潜力分析
  • 未来市场趋势
  • 技术与创新格局
    • 当前技术趋势
    • 新兴技术
  • 价格趋势
    • 按地区
    • 透过技术
  • 监管环境
    • 标准和合规要求
    • 区域监理框架
  • 波特的分析
  • PESTEL 分析

第四章：竞争格局

  • 介绍
  • 公司市占率分析
    • 按地区
  • 公司矩阵分析
  • 主要市场参与者的竞争分析
  • 竞争定位矩阵
  • 关键进展
    • 併购
    • 合作伙伴关係与合作
    • 新产品发布
    • 扩张计划

第五章：市场估计与预测：依技术划分，2021-2034年

  • 主要趋势
  • 脸部表情辨识系统
  • 语音情绪辨识解决方案
  • 生理讯号处理平台
  • 多模态融合系统
  • 自然语言处理情感分析

第六章：市场估算与预测：依部署模式划分，2021-2034年

  • 主要趋势
  • 基于云端（SaaS/API）
  • 设备端/边缘端
  • 杂交种

第七章：市场估算与预测：依解法划分，2021-2034年

  • 主要趋势
  • 情绪感知模组
  • 情绪分析/模型（人工智慧）
  • 个人化引擎/决策
  • 最终用途/产品
  • 服务

第八章：市场估算与预测：依优先矩阵划分，2021-2034年

  • 主要趋势
  • 高优先级
  • 中等优先级
  • 选择性

第九章：市场估计与预测：依应用领域划分，2021-2034年

  • 主要趋势
  • 医疗保健和健康应用
  • 汽车与运输解决方案
  • 零售与电子商务个人化
  • 教育与培训应用
  • 娱乐和游戏解决方案
  • 客户服务与支援提升

第十章：市场估计与预测：依最终用途产业划分，2021-2034年

  • 主要趋势
  • 消费性电子产业
  • 医疗保健和生命科学领域
  • 汽车和运输业
  • 零售和消费品产业
  • 媒体与娱乐产业
  • 金融服务业

第十一章：市场估计与预测：按地区划分，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
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 韩国
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • MEA
    • 阿联酋
    • 南非
    • 沙乌地阿拉伯

第十二章：公司简介

  • Affectiva
  • Amazon Web Services
  • Apple
  • audEERING
  • Element Human
  • Eyesight Technologies
  • Google (Alphabet)
  • International Business Machines
  • Kairos AR
  • Meta Platforms
  • Microsoft
  • Nemesysco
  • NVIDIA
  • Realeyes Data Services
  • SoftBank Robotics Group
简介目录
Product Code: 14917

The Global Emotion AI for Personalized Products Market was valued at USD 3 billion in 2024 and is estimated to grow at a CAGR of 21.3% to reach USD 26.5 billion by 2034.

Emotion AI for Personalized Products Market - IMG1

This market is evolving rapidly as companies integrate emotion recognition into digital experiences, bridging human interaction with artificial intelligence. The growing need for real-time emotion tracking across customer service, healthcare, retail, and automotive sectors is pushing companies to develop more sophisticated, privacy-conscious tools. Major players are investing in multimodal AI systems that combine facial analysis, voice tonality, and text sentiment to deliver accurate emotional insights. At the same time, the shift toward edge computing and decentralized data processing is addressing growing concerns around data privacy and latency. New regulations, especially in regions like Europe are influencing design decisions, prompting innovation in compliant AI architecture. Emotion AI is now deeply integrated into consumer products, digital assistants, wearables, and enterprise solutions, creating deeper personalization and improving engagement across platforms. The market is becoming increasingly competitive as tech giants and startups alike race to provide scalable, emotionally intelligent systems.

Market Scope
Start Year2024
Forecast Year2025-2034
Start Value$3 Billion
Forecast Value$26.5 Billion
CAGR21.3%

The facial expression recognition segment held a 33.9% share in 2024, growing at a CAGR of 22.3% through 2034. This growth is fueled by the widespread use of camera-equipped devices across everyday products and systems, enabling non-contact emotional analysis. These tools rely on deep learning algorithms to analyze facial structures, movements, and expressions, offering real-time emotion feedback. Industries like retail, automotive, consumer electronics, and security are accelerating adoption due to the ease of integration and high accuracy levels of facial recognition tools.

The emotion sensing modules segment held 31.4% share in 2024 and is expected to grow at a CAGR of 20.6% during the forecast period. These modules combine hardware and software elements such as sensors, cameras, microphones, and processors that enable emotional data collection and interpretation. As the market shifts toward edge-based systems, the demand for modules capable of real-time, offline emotion processing is increasing. These components form the backbone of emotion AI infrastructure and are becoming more sophisticated and power-efficient to support a wide range of use cases across wearables, in-vehicle systems, and consumer devices.

North America Emotion AI for Personalized Products Market held 39.3% share in 2024 with a projected CAGR of 20.5%. The United States alone accounts for nearly 85% of this regional market, fueled by high R&D spending, early adoption of AI across verticals, and supportive innovation ecosystems. Major technology companies such as Meta Platforms, NVIDIA, Microsoft, Amazon Web Services, and Apple are shaping the regional landscape with continuous product development and investments in AI startups. Sectors like healthcare and automotive are witnessing fast adoption, with emotion AI playing a growing role in mental health apps, patient monitoring, and in-car driver alert systems.

Prominent companies operating in the Global Emotion AI for Personalized Products Market include SoftBank Robotics Group, Affectiva, Kairos AR, International Business Machines, Realeyes Data Services, NVIDIA, audEERING, Microsoft, Element Human, Amazon Web Services, Meta Platforms, Eyesight Technologies, Nemesysco, Google (Alphabet), and Apple. To maintain a strong position in the emotion AI for personalized products market, leading companies are prioritizing the development of multimodal algorithms that analyze facial, voice, and textual cues simultaneously for greater accuracy. They're also expanding edge AI capabilities, allowing emotion processing to occur directly on local devices, reducing latency and preserving user privacy. Strategic acquisitions and partnerships with startups are helping accelerate innovation cycles. Moreover, organizations are aligning solutions with global regulatory trends by integrating differential privacy, federated learning, and compliance-ready architectures.

Table of Contents

Chapter 1 Methodology and Scope

  • 1.1 Market scope and definition
  • 1.2 Research design
    • 1.2.1 Research approach
  • 1.3 Data collection methods
  • 1.4 Data mining sources
    • 1.4.1 Global
    • 1.4.2 Regional/Country
  • 1.5 Base estimates and calculations
    • 1.5.1 Base year calculation
    • 1.5.2 Key trends for market estimation
  • 1.6 Primary research and validation
    • 1.6.1 Primary sources
  • 1.7 Forecast model
  • 1.8 Research assumptions and limitations

Chapter 2 Executive Summary

  • 2.1 Industry 3600 synopsis
  • 2.2 Key market trends
    • 2.2.1 Regional
    • 2.2.2 Technology
    • 2.2.3 Deployment mode
    • 2.2.4 Solution
    • 2.2.5 Prioritization matrix
    • 2.2.6 Application
    • 2.2.7 End use industry
  • 2.3 CXO perspectives: strategic imperatives
    • 2.3.1 Key decision points for industry executives
    • 2.3.2 Critical success factors for market players
  • 2.4 Future outlook and strategic recommendations

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
    • 3.1.1 Supplier landscape
    • 3.1.2 Profit margin
    • 3.1.3 Value addition at each stage
    • 3.1.4 Factors affecting the value chain
  • 3.2 Industry impact forces
    • 3.2.1 Growth drivers
      • 3.2.1.1 Enterprise ai adoption acceleration & digital transformation
      • 3.2.1.2 Multimodal ai advancement & technical capability enhancement
      • 3.2.1.3 Automotive safety regulations & driver monitoring requirements
    • 3.2.2 Industry pitfalls & challenges
      • 3.2.2.1 Privacy concerns & regulatory compliance complexity
      • 3.2.2.2 Technical & cultural bias in emotion recognition systems
    • 3.2.3 Opportunities
      • 3.2.3.1 Expansion of emotion AI into consumer products
      • 3.2.3.2 Real-time personalized experience platforms
  • 3.3 Growth potential analysis
  • 3.4 Future market trends
  • 3.5 Technology and innovation landscape
    • 3.5.1 Current technological trends
    • 3.5.2 Emerging technologies
  • 3.6 Price trends
    • 3.6.1 By region
    • 3.6.2 By Technology
  • 3.7 Regulatory landscape
    • 3.7.1 standards and compliance requirements
    • 3.7.2 Regional regulatory frameworks
  • 3.8 Porter's analysis
  • 3.9 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

  • 4.1 Introduction
  • 4.2 Company market share analysis
    • 4.2.1 By region
      • 4.2.1.1 North America
      • 4.2.1.2 Europe
      • 4.2.1.3 Asia Pacific
      • 4.2.1.4 Latin America
      • 4.2.1.5 Middle East and Africa
  • 4.3 Company matrix analysis
  • 4.4 Competitive analysis of major market players
  • 4.5 Competitive positioning matrix
  • 4.6 Key developments
    • 4.6.1 Mergers & acquisitions
    • 4.6.2 Partnerships & collaborations
    • 4.6.3 New product launches
    • 4.6.4 Expansion plans

Chapter 5 Market Estimates & Forecast, By Technology, 2021 - 2034 ($Bn, Thousand Units)

  • 5.1 Key trends
  • 5.2 Facial expression recognition systems
  • 5.3 Speech emotion recognition solutions
  • 5.4 Physiological signal processing platforms
  • 5.5 Multimodal fusion systems
  • 5.6 Natural language processing for sentiment

Chapter 6 Market Estimates & Forecast, By Deployment Mode, 2021 - 2034 ($Bn, Thousand Units)

  • 6.1 Key trends
  • 6.2 Cloud-based (SaaS / API)
  • 6.3 On-device / edge
  • 6.4 Hybrid

Chapter 7 Market Estimates & Forecast, By Solution, 2021 - 2034 ($Bn, Thousand Units)

  • 7.1 Key trends
  • 7.2 Emotion sensing modules
  • 7.3 Emotion analytics / models (AI)
  • 7.4 Personalization engine / decisioning
  • 7.5 End use applications / products
  • 7.6 Services

Chapter 8 Market Estimates & Forecast, By Prioritization Matrix, 2021 - 2034 ($Bn, Thousand Units)

  • 8.1 Key trends
  • 8.2 High priority
  • 8.3 Medium priority
  • 8.4 Selective

Chapter 9 Market Estimates & Forecast, By Application, 2021 - 2034 ($Bn, Thousand Units)

  • 9.1 Key trends
  • 9.2 Healthcare & wellness applications
  • 9.3 Automotive & transportation solutions
  • 9.4 Retail & e-commerce personalization
  • 9.5 Education & training applications
  • 9.6 Entertainment & gaming solutions
  • 9.7 Customer service & support enhancement

Chapter 10 Market Estimates & Forecast, By End Use Industry, 2021 - 2034 ($Bn, Thousand Units)

  • 10.1 Key trends
  • 10.2 Consumer electronics industry
  • 10.3 Healthcare & life sciences sector
  • 10.4 Automotive & transportation industry
  • 10.5 retail & consumer goods sector
  • 10.6 Media & entertainment industry
  • 10.7 Financial services sector

Chapter 11 Market Estimates & Forecast, By Region, 2021 - 2034 ($Bn, Thousand Units)

  • 11.1 Key trends
  • 11.2 North America
    • 11.2.1 U.S.
    • 11.2.2 Canada
  • 11.3 Europe
    • 11.3.1 UK
    • 11.3.2 Germany
    • 11.3.3 France
    • 11.3.4 Italy
    • 11.3.5 Spain
    • 11.3.6 Russia
  • 11.4 Asia Pacific
    • 11.4.1 China
    • 11.4.2 India
    • 11.4.3 Japan
    • 11.4.4 Australia
    • 11.4.5 South Korea
  • 11.5 Latin America
    • 11.5.1 Brazil
    • 11.5.2 Mexico
    • 11.5.3 Argentina
  • 11.6 MEA
    • 11.6.1 UAE
    • 11.6.2 South Africa
    • 11.6.3 Saudi Arabia

Chapter 12 Company Profiles

  • 12.1 Affectiva
  • 12.2 Amazon Web Services
  • 12.3 Apple
  • 12.4 audEERING
  • 12.5 Element Human
  • 12.6 Eyesight Technologies
  • 12.7 Google (Alphabet)
  • 12.8 International Business Machines
  • 12.9 Kairos AR
  • 12.10 Meta Platforms
  • 12.11 Microsoft
  • 12.12 Nemesysco
  • 12.13 NVIDIA
  • 12.14 Realeyes Data Services
  • 12.15 SoftBank Robotics Group