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市场调查报告书
商品编码
1802986

全球情绪辨识人工智慧市场：未来预测（至 2032 年）—按组件、部署模式、技术、应用、最终用户和地区进行分析

Emotional Recognition AI Market Forecasts to 2032 - Global Analysis By Component (Software, Hardware and Services), Deployment Mode, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球情绪辨识 AI 市场预计在 2025 年达到 36 亿美元，到 2032 年将达到 149 亿美元，预测期内的复合年增长率为 22.7%。

情绪感知人工智慧是人工智慧的一个高级分支，旨在透过分析面部表情、语调、肢体语言和生理讯号来检测、解读和回应人类情绪。透过利用机器学习演算法和深度神经网络，可以即时评估快乐、愤怒、悲伤和压力等情绪状态。这项技术正越来越多地应用于医疗保健、教育、客户服务和行销等领域，以增强人机互动、提升用户体验并提供个人化解决方案。虽然它功能强大，但也引发了隐私、知情同意和资料安全方面的伦理问题，因此需要负责任地实施。

增强客户参与

增强的客户参与正推动情绪辨识人工智慧市场的成长，推动零售、医疗保健和娱乐整体超个人化体验的需求。随着品牌透过即时情绪分析和自适应介面深化其情绪智商，人工智慧解决方案也不断发展，能够更准确地解读人类细微的表情。这种反馈循环加速了创新，增强了消费者信任，并扩大了各行业的应用范围。最终，参与度将推动资料丰富化，从而打造更具同理心和情境感知能力的人工智慧系统，重新定义人机互动。

隐私和道德问题

隐私和伦理问题对情绪辨识人工智慧市场的成长构成了重大障碍。围绕着资料收集、知情同意以及敏感情绪资讯滥用日益严格的审查，引发了监管机构和公众的担忧。企业在赢得使用者信任、遵守严格的隐私法规以及确保符合伦理道德的部署方面面临挑战。这些问题减缓了人工智慧的普及，增加了营运成本，并阻碍了全球市场的整体扩张。

技术进步

深度学习、边缘运算和多模态感知技术的进步正在显着加速市场发展。脸部微表情分析、语音语调检测和情境情绪映射的准确性提升，正在推动医疗保健、汽车和消费技术领域的采用。即时情绪追踪可实现个人化使用者体验、心理健康诊断和自适应学习平台。随着人工智慧越来越以人性化，这些创新正在再形成机器的情绪智商，释放新的商业性和治疗领域，并带来显着的影响。

实施成本高

高昂的实施成本是情感辨识人工智慧应用的一大障碍。尤其是中小企业，他们难以承受昂贵的硬体、软体和整合成本，限制了其广泛应用。这些经济负担减缓了市场渗透，减少了创新投资，并阻碍了潜在用户采用先进的情感感知技术，最终抑制了整个情感识别人工智慧市场的成长和扩张。

COVID-19的影响

随着远距办公、虚拟通讯和远端医疗在全球的激增，新冠疫情显着加速了情绪辨识人工智慧的应用。各组织机构纷纷寻求人工智慧主导的工具来衡量情绪、增强客户参与，并在保持社交距离的环境中监测心理健康。然而，研究中断、资金筹措延迟和供应链限制暂时减缓了硬体和软体的开发，以各种方式影响了市场发展，但总体上推动了市场成长。

语音辨识部分预计将成为预测期内最大的部分

语音和语音辨识领域预计将在预测期内占据最大的市场占有率，因为它能够基于声调和语调进行即时情绪分析。这种协同效应将增强人机互动，并为医疗保健、客户服务和行销等领域的情绪识别系统提供支援。透过解读语音中微妙的情绪状态，这些人工智慧模型可以提供个人化的回应，从而提高用户参与度和满意度。该领域的发展将推动可扩展且适应不同文化的情绪检测解决方案的发展，从而显着提升其商业性潜力。

预计零售和电子商务领域在预测期内将以最高复合年增长率成长

在预测期内，零售和电子商务领域预计将实现最高成长率，因为该领域正在提升客户参与和个人化体验。透过分析脸部表情和情绪线索，品牌可以客製化产品推荐、优化使用者体验设计，并即时优化广告定位。这种情绪智商能够加深消费者的信任和忠诚度，提高转换率并减少客户流失。随着数位购物的发展，情感人工智慧将成为零售商在全球市场寻求竞争差异化和超个人化体验的策略资产。

比最大的地区

在预测期内，亚太地区预计将占据最大的市场占有率，这得益于其在医疗保健和零售领域的转型。解码脸部和声音线索可以增强心理健康诊断、驾驶安全性和个人化消费者参与。智慧型手机的高普及率正在推动情绪辨识应用的发展，而中国和新加坡的智慧城市计画正在加速其应用。行销公司正在利用即时情绪分析来优化宣传活动，提高投资回报率和品牌共鸣。这种激增反映了亚太地区对以情感主导、人性化的人工智慧创新的积极接受。

复合年增长率最高的地区：

预计北美将在预测期内实现最高的复合年增长率，因为先进的情绪识别系统能够增强心理健康诊断、实现远端医疗个人化，并透过疲劳检测提高驾驶员安全性。科技巨头和新兴企业都在利用人工智慧和物联网的融合，提供自适应情绪感知解决方案。在硅谷创新生态系统和日益增长的同理心界面需求的推动下，该地区在符合道德且具影响力的部署方面处于世界领先地位。

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此报告的订阅者可以从以下免费自订选项中选择一项：

  • 公司简介
    • 对最多三家其他市场公司进行全面分析
    • 主要企业的SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户兴趣对主要国家进行的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19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

5. 全球情绪辨识人工智慧市场（按组件）

  • 软体
  • 硬体
  • 服务

6. 全球情绪辨识AI市场（依部署模式）

  • 云端基础
  • 本地

7. 全球情绪辨识人工智慧市场（按技术）

  • 脸部表情辨识
  • 语音辨识
  • 生物感测（EEG、ECG、fNIRS、GSR 等）
  • 自然语言处理（NLP）

第八章 全球情绪辨识人工智慧市场（按应用）

  • 行销和广告
  • 安全与监控
  • 人机交互
  • 医疗保健和医疗诊断
  • 娱乐和游戏
  • 客户服务

第九章 全球情绪辨识人工智慧市场（按最终用户）

  • 银行、金融服务和保险（BFSI）
  • 零售与电子商务
  • 资讯科技/通讯
  • 车
  • 政府和国防
  • 教学
  • 其他最终用户

第 10 章全球情绪辨识人工智慧市场（按地区）

  • 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
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美
  • 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

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十二章 公司概况

  • Affectiva
  • Realeyes
  • Beyond Verbal
  • nViso
  • Kairos
  • Tobii AB
  • NEC Corporation
  • Microsoft Corporation
  • Apple Inc.
  • Amazon Web Services（AWS）
  • IBM Corporation
  • Google LLC
  • Cognitec Systems GmbH
  • Sentiance
  • Emotibot Technologies
  • Eyeris Technologies Inc.
  • Noldus Information Technology
  • Sightcorp
  • Elliptic Labs
  • Aural Analytics
Product Code: SMRC30512

According to Stratistics MRC, the Global Emotional Recognition AI Market is accounted for $3.6 billion in 2025 and is expected to reach $14.9 billion by 2032 growing at a CAGR of 22.7% during the forecast period. Emotional Recognition AI is an advanced branch of artificial intelligence designed to detect, interpret, and respond to human emotions through analysis of facial expressions, vocal tones, body language, and physiological signals. By leveraging machine learning algorithms and deep neural networks, it can assess emotional states such as happiness, anger, sadness, or stress in real time. This technology is increasingly applied in sectors like healthcare, education, customer service, and marketing to enhance human-computer interaction, improve user experience, and provide personalized solutions. While powerful, it raises ethical considerations around privacy, consent, and data security, requiring responsible implementation.

Market Dynamics:

Driver:

Enhanced Customer Engagement

Enhanced customer engagement is catalyzing growth in the Emotional Recognition AI market by driving demand for hyper-personalized experiences across retail, healthcare, and entertainment. As brands deepen emotional intelligence through real-time sentiment analysis and adaptive interfaces, AI solutions are evolving to decode nuanced human expressions with greater accuracy. This feedback loop accelerates innovation, boosts consumer trust, and expands adoption across sectors. Ultimately, engagement fuels data richness, enabling more empathetic, context-aware AI systems that redefine human-machine interaction.

Restraint:

Privacy and Ethical Concerns

Privacy and ethical concerns pose a significant barrier to the growth of the Emotional Recognition AI market. Increasing scrutiny over data collection, consent, and misuse of sensitive emotional information raises regulatory and public apprehension. Companies face challenges in gaining user trust, complying with strict privacy laws, and ensuring ethical deployment. These issues slow adoption, increase operational costs, and hinder overall market expansion globally.

Opportunity:

Advancements in Technology

Advancements in deep learning, edge computing, and multimodal sensing have significantly accelerated the market. Enhanced accuracy in facial micro-expression analysis, voice tonality detection, and contextual sentiment mapping is driving adoption across healthcare, automotive, and consumer tech. Real-time emotion tracking is enabling personalized user experiences, mental health diagnostics, and adaptive learning platforms. As AI becomes more human-centric, these innovations are reshaping emotional intelligence in machines, unlocking new commercial and therapeutic frontiers with measurable impact.

Threat:

High Implementation Costs

High implementation costs pose a significant barrier to the adoption of Emotional Recognition AI. Small and medium enterprises, in particular, struggle with the expensive hardware, software, and integration requirements, limiting widespread deployment. These financial burdens slow market penetration, reduce investment in innovation, and deter potential users from adopting advanced emotion-sensing technologies, ultimately restraining growth and hindering the overall expansion of the Emotional Recognition AI market.

Covid-19 Impact

The Covid-19 pandemic significantly accelerated the adoption of Emotional Recognition AI, as remote work, virtual communication, and telehealth surged globally. Organizations sought AI-driven tools to gauge emotions, enhance customer engagement, and monitor mental health in socially distanced environments. However, disruptions in research, funding delays, and supply chain constraints temporarily slowed hardware and software development, creating a mixed but overall driving impact on market growth.

The speech & voice recognition segment is expected to be the largest during the forecast period

The speech & voice recognition segment is expected to account for the largest market share during the forecast period as it enables real-time sentiment analysis through vocal cues like tone and cadence. This synergy enhances human-computer interaction, empowering emotionally aware systems across healthcare, customer service, and marketing. By decoding nuanced emotional states from speech, these AI models deliver personalized responses, boosting user engagement and satisfaction. The segment's evolution is driving scalable, culturally adaptive emotion detection solutions with transformative commercial potential.

The retail & e-commerce segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the retail & e-commerce segment is predicted to witness the highest growth rate as it enhances customer engagement and personalization. By analyzing facial expressions and sentiment cues, brands can tailor product recommendations, optimize UX design, and refine ad targeting in real time. This emotional intelligence fosters deeper consumer trust and loyalty, driving conversion rates and reducing churn. As digital shopping evolves, emotional AI becomes a strategic asset for retailers seeking competitive differentiation and hyper-personalized experiences across global markets.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share due to transformative change across healthcare and retail sectors. By decoding facial expressions and vocal cues, it enhances mental health diagnostics, driver safety, and personalized consumer engagement. High smartphone penetration fuels emotion-aware apps, while smart city initiatives in China and Singapore accelerate adoption. Marketing firms leverage real-time emotional analytics to optimize campaigns, boosting ROI and brand resonance. This surge reflects Asia Pacific's dynamic embrace of emotion-driven, human-centric AI innovation.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to advanced emotion-aware systems enhance mental health diagnostics, personalize telemedicine, and improve driver safety through fatigue detection. Tech giants and startups alike leverage AI and IoT integration to deliver adaptive, emotion-sensitive solutions. With Silicon Valley's innovation ecosystem and rising demand for empathetic interfaces, the region leads globally in ethical, impactful deployment-reshaping human-machine interaction with precision and emotional intelligence.

Key players in the market

Some of the key players profiled in the Emotional Recognition AI Market include Affectiva, Realeyes, Beyond Verbal, nViso, Kairos, Tobii AB, NEC Corporation, Microsoft Corporation, Apple Inc., Amazon Web Services (AWS), IBM Corporation, Google LLC, Cognitec Systems GmbH, Sentiance, Emotibot Technologies, Eyeris Technologies Inc., Noldus Information Technology, Sightcorp, Elliptic Labs and Aural Analytics.

Key Developments:

In August 2025, Coherent and Apple have deepened their alliance through a new multiyear agreement to manufacture vertical-cavity surface-emitting lasers (VCSELs) at Coherent's Sherman, Texas facility. The partnership not only strengthens Apple's domestic supply chain but also positions both companies at the forefront of cutting-edge semiconductor innovation.

In January 2025, Telefonica Tech and IBM have entered a strategic partnership to develop quantum-safe cybersecurity solutions, anticipating the risks posed by future quantum computers. The collaboration aims to safeguard critical data against potential decryption by quantum computers, aligning with NIST's post-quantum cryptography standards.

In January 2025, Microsoft and OpenAI announced an evolved partnership to advance AI innovation. Microsoft will support OpenAI's expansion with additional capacity for research and model training. The agreement grants Microsoft rights to OpenAI's intellectual property, including models and infrastructure, for integration into Microsoft's products like Copilot.

Components Covered:

  • Software
  • Hardware
  • Services

Deployment Modes Covered:

  • Cloud-Based
  • On-Premises

Technologies Covered:

  • Facial Expression Recognition
  • Speech & Voice Recognition
  • Bio-Sensing (EEG, ECG, fNIRS, GSR, etc.)
  • Natural Language Processing (NLP)

Applications Covered:

  • Marketing & Advertising
  • Security & Surveillance
  • Human-Computer Interaction
  • Healthcare & Medical Diagnosis
  • Entertainment & Gaming
  • Customer Service

End Users Covered:

  • Banking, Financial Services, and Insurance (BFSI)
  • Retail & E-commerce
  • IT & Telecommunication
  • Automotive
  • Government & Defense
  • Education & Learning
  • 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 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 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 Emotional Recognition AI Market, By Component

  • 5.1 Introduction
  • 5.2 Software
  • 5.3 Hardware
  • 5.4 Services

6 Global Emotional Recognition AI Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 Cloud-Based
  • 6.3 On-Premises

7 Global Emotional Recognition AI Market, By Technology

  • 7.1 Introduction
  • 7.2 Facial Expression Recognition
  • 7.3 Speech & Voice Recognition
  • 7.4 Bio-Sensing (EEG, ECG, fNIRS, GSR, etc.)
  • 7.5 Natural Language Processing (NLP)

8 Global Emotional Recognition AI Market, By Application

  • 8.1 Introduction
  • 8.2 Marketing & Advertising
  • 8.3 Security & Surveillance
  • 8.4 Human-Computer Interaction
  • 8.5 Healthcare & Medical Diagnosis
  • 8.6 Entertainment & Gaming
  • 8.7 Customer Service

9 Global Emotional Recognition AI Market, By End User

  • 9.1 Introduction
  • 9.2 Banking, Financial Services, and Insurance (BFSI)
  • 9.3 Retail & E-commerce
  • 9.4 IT & Telecommunication
  • 9.5 Automotive
  • 9.6 Government & Defense
  • 9.7 Education & Learning
  • 9.8 Other End Users

10 Global Emotional Recognition AI Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Affectiva
  • 12.2 Realeyes
  • 12.3 Beyond Verbal
  • 12.4 nViso
  • 12.5 Kairos
  • 12.6 Tobii AB
  • 12.7 NEC Corporation
  • 12.8 Microsoft Corporation
  • 12.9 Apple Inc.
  • 12.10 Amazon Web Services (AWS)
  • 12.11 IBM Corporation
  • 12.12 Google LLC
  • 12.13 Cognitec Systems GmbH
  • 12.14 Sentiance
  • 12.15 Emotibot Technologies
  • 12.16 Eyeris Technologies Inc.
  • 12.17 Noldus Information Technology
  • 12.18 Sightcorp
  • 12.19 Elliptic Labs
  • 12.20 Aural Analytics

List of Tables

  • Table 1 Global Emotional Recognition AI Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Emotional Recognition AI Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Emotional Recognition AI Market Outlook, By Software (2024-2032) ($MN)
  • Table 4 Global Emotional Recognition AI Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 5 Global Emotional Recognition AI Market Outlook, By Services (2024-2032) ($MN)
  • Table 6 Global Emotional Recognition AI Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 7 Global Emotional Recognition AI Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 8 Global Emotional Recognition AI Market Outlook, By On-Premises (2024-2032) ($MN)
  • Table 9 Global Emotional Recognition AI Market Outlook, By Technology (2024-2032) ($MN)
  • Table 10 Global Emotional Recognition AI Market Outlook, By Facial Expression Recognition (2024-2032) ($MN)
  • Table 11 Global Emotional Recognition AI Market Outlook, By Speech & Voice Recognition (2024-2032) ($MN)
  • Table 12 Global Emotional Recognition AI Market Outlook, By Bio-Sensing (EEG, ECG, fNIRS, GSR, etc.) (2024-2032) ($MN)
  • Table 13 Global Emotional Recognition AI Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 14 Global Emotional Recognition AI Market Outlook, By Application (2024-2032) ($MN)
  • Table 15 Global Emotional Recognition AI Market Outlook, By Marketing & Advertising (2024-2032) ($MN)
  • Table 16 Global Emotional Recognition AI Market Outlook, By Security & Surveillance (2024-2032) ($MN)
  • Table 17 Global Emotional Recognition AI Market Outlook, By Human-Computer Interaction (2024-2032) ($MN)
  • Table 18 Global Emotional Recognition AI Market Outlook, By Healthcare & Medical Diagnosis (2024-2032) ($MN)
  • Table 19 Global Emotional Recognition AI Market Outlook, By Entertainment & Gaming (2024-2032) ($MN)
  • Table 20 Global Emotional Recognition AI Market Outlook, By Customer Service (2024-2032) ($MN)
  • Table 21 Global Emotional Recognition AI Market Outlook, By End User (2024-2032) ($MN)
  • Table 22 Global Emotional Recognition AI Market Outlook, By Banking, Financial Services, and Insurance (BFSI) (2024-2032) ($MN)
  • Table 23 Global Emotional Recognition AI Market Outlook, By Retail & E-commerce (2024-2032) ($MN)
  • Table 24 Global Emotional Recognition AI Market Outlook, By IT & Telecommunication (2024-2032) ($MN)
  • Table 25 Global Emotional Recognition AI Market Outlook, By Automotive (2024-2032) ($MN)
  • Table 26 Global Emotional Recognition AI Market Outlook, By Government & Defense (2024-2032) ($MN)
  • Table 27 Global Emotional Recognition AI Market Outlook, By Education & Learning (2024-2032) ($MN)
  • Table 28 Global Emotional Recognition AI Market Outlook, By Other End Users (2024-2032) ($MN)

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