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市場調查報告書

商品編碼

1616054

情緒運算市場機會、成長動力、產業趨勢分析與預測 2024 - 2032

Affective Computing Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2024 - 2032

出版日期: 2024年09月16日 | 出版商:

Global Market Insights Inc. | 英文 250 Pages | 商品交期: 2-3個工作天內

價格

簡介目錄

全球情感運算市場到2023 年價值將達到620 億美元，預計從2024 年到2032 年將以25% 的複合年成長率成長。體驗的需求不斷成長推動的。隨著人們尋求更量身定做的交互，情感運算技術在利用情感資料客製化服務方面發揮關鍵作用。這些系統透過適應個人情緒來增強使用者參與度，使體驗更加相關和有意義。市場成長的一個重要動力是人們對情感人工智慧的興趣日益濃厚，這涉及開發能夠解釋和回應人類情感的系統。

對於那些希望透過聊天機器人和虛擬助理提供更具同理心的互動來改善客戶服務的企業來說，情感人工智慧已經變得至關重要。這些技術旨在捕捉情緒線索，提供更個人化和有效的回應。透過情感人工智慧增強用戶體驗的重點預計將為情感運算市場的擴張做出重大貢獻。就組件而言，市場分為硬體、軟體和服務。

軟體領域正在迅速發展，到 2023 年將佔據超過 45% 的市場。在人工智慧和機器學習進步的推動下，軟體在分析面部表情、語氣和生理訊號等輸入以解釋情緒狀態方面發揮關鍵作用。隨著企業尋求創造更具吸引力和同理心的技術，對複雜軟體演算法的需求持續成長，使該細分市場成為關鍵成長領域。該市場還按部署模型進行分類，提供本地和基於雲端的解決方案選項。

市場範圍
開始年份	2023年
預測年份	2024-2032
起始值	620 億美元
預測值	4,466 億美元
複合年成長率	25%

雲端部署因其能夠即時處理情感資料、同時提供可擴展性和可訪問性而受到關注。企業可以根據需求輕鬆調整資源並無縫整合更新，從而從雲端基礎設施中受益。這種靈活性支持情感運算技術在各行業的更廣泛採用。到2023年，北美將佔據全球情感運算市場約30%的佔有率，主導全球情感運算市場。此外，對心理健康個人化體驗和應用的需求也有助於該地區的市場領導地位。

產業生態系統分析
供應商格局
- 硬體提供者
- 軟體供應商
- 服務提供者
- 科技
- 終端用戶
利潤率分析
技術與創新格局
案例研究
專利分析
重要新聞和舉措
監管環境
衝擊力
- 成長動力
  - 對個人化體驗的需求不斷成長
  - 人們對情感人工智慧的興趣日益濃厚
  - 物聯網設備的採用不斷增加
  - 人機互動的擴展
- 產業陷阱與挑戰
  - 隱私和道德問題
  - 技術挑戰
成長潛力分析
波特的分析
PESTEL分析

第 4 章：競爭格局

介紹
公司市佔率分析
競爭定位矩陣
戰略展望矩陣

第 5 章：市場估計與預測：按組成部分，2021-2032 年

主要趨勢
硬體
軟體
- 分析軟體
- 企業軟體
- 人臉辨識
- 手勢識別
- 語音辨識
服務

第 6 章：市場估計與預測：按部署模型，2021-2032 年

主要趨勢
本地
雲

第 7 章：市場估計與預測：按技術分類，2021-2032 年

主要趨勢
觸控式
非接觸式

第 8 章：市場估計與預測：按最終用戶，2021-2032 年

主要趨勢
衛生保健
汽車
消費性電子產品
零售與電子商務
教育
遊戲和娛樂
行銷和廣告
其他

第 9 章：市場估計與預測：按地區，2021-2032 年

主要趨勢
北美洲
- 美國
- 加拿大
歐洲
- 英國
- 德國
- 法國
- 義大利
- 西班牙
- 俄羅斯
- 荷蘭
- 歐洲其他地區
亞太地區
- 中國
- 印度
- 日本
- 韓國
- 澳新銀行
- 東南亞
- 亞太地區其他地區
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
- 拉丁美洲其他地區
MEA
- 阿拉伯聯合大公國
- 沙烏地阿拉伯
- 南非
- MEA 的其餘部分

第 10 章：公司簡介

Affectiva
Amazon, Inc
Cognitec Systems
Emotibot Technologies Limited
EmoVu
EyeTech Digital Systems
Google LLC
Hanson Robotics
IBM Corporation
Intel Corporation
Kairos
Kairos AR Inc.
Microsoft Corporation
NeuroSky
Nviso
Qualcomm
Realeyes
Samsung Electronics
Sensory Inc.
Xilinx Inc.

簡介目錄

Product Code: 11446

The Global Affective Computing Market, valued at USD 62 billion in 2023, is projected to grow at a CAGR of 25% from 2024 to 2032. This rapid expansion is largely fueled by the increasing demand for personalized experiences across both consumer and business platforms. As people seek more tailored interactions, affective computing technologies play a critical role in customizing services by utilizing emotional data. These systems enhance user engagement by adapting to individual emotions, making experiences more relevant and meaningful. A significant driver of market growth is the rising interest in emotional AI, which involves the development of systems that can interpret and respond to human emotions.

Emotional AI has become crucial for businesses aiming to improve customer service by offering more empathetic interactions through chatbots and virtual assistants. These technologies are designed to pick up on emotional cues, delivering more personalized and effective responses. The focus on enhancing user experience through emotional AI is expected to contribute significantly to the expansion of the affective computing market. In terms of components, the market is segmented into hardware, software, and services.

The software segment, which accounted for over 45% of the market share in 2023, is evolving rapidly. Driven by advancements in artificial intelligence and machine learning, software plays a pivotal role in analyzing inputs like facial expressions, vocal tones, and physiological signals to interpret emotional states. As businesses seek to create more engaging and empathetic technology, the demand for sophisticated software algorithms continues to rise, making this segment a key growth area. The market is also categorized by deployment models, with options for on-premises and cloud-based solutions.

Market Scope
Start Year	2023
Forecast Year	2024-2032
Start Value	$62 Billion
Forecast Value	$446.6 Billion
CAGR	25%

Cloud deployment is gaining traction due to its ability to offer real-time processing of emotional data while providing scalability and accessibility. Businesses benefit from cloud infrastructure by easily adjusting resources according to demand and integrating updates seamlessly. This flexibility supports the wider adoption of affective computing technologies across industries. North America, holding around 30% of the market share in 2023, dominates the global affective computing market.The region's strong technological infrastructure and substantial investments in AI and machine learning drive the rapid deployment of these solutions. Additionally, the demand for personalized experiences and applications for mental health contributes to the region's market leadership.

Chapter 1 Methodology & Scope

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

Chapter 2 Executive Summary

2.1 Industry 360° synopsis, 2021 - 2032

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
3.2 Supplier landscape
- 3.2.1 Hardware providers
- 3.2.2 Software providers
- 3.2.3 Service providers
- 3.2.4 Technology
- 3.2.5 End-user
3.3 Profit margin analysis
3.4 Technology & innovation landscape
3.5 Case study
3.6 Patent analysis
3.7 Key news and initiatives
3.8 Regulatory landscape
3.9 Impact forces
- 3.9.1 Growth drivers
  - 3.9.1.1 Increasing demand for personalized experiences
  - 3.9.1.2 Rising interest in emotional AI
  - 3.9.1.3 Increasing adoption of IoT devices
  - 3.9.1.4 Expansion of human-computer interaction
- 3.9.2 Industry pitfalls & challenges
  - 3.9.2.1 Privacy and ethical concerns
  - 3.9.2.2 Technical challenges
3.10 Growth potential analysis
3.11 Porter's analysis
3.12 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

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, 2021-2032 ($Bn)

5.1 Key trends
5.2 Hardware
5.3 Software
- 5.3.1 Analytics software
- 5.3.2 Enterprise software
- 5.3.3 Facial recognition
- 5.3.4 Gesture recognition
- 5.3.5 Speech recognition
5.4 Services

Chapter 6 Market Estimates & Forecast, By Deployment Model, 2021-2032 ($Bn)

6.1 Key trends
6.2 On-premises
6.3 Cloud

Chapter 7 Market Estimates & Forecast, By Technology, 2021-2032 ($Bn)

7.1 Key trends
7.2 Touch-based
7.3 Touchless

Chapter 8 Market Estimates & Forecast, By End-user, 2021-2032 ($Bn)

8.1 Key trends
8.2 Healthcare
8.3 Automotive
8.4 Consumer electronics
8.5 Retail & e-commerce
8.6 Education
8.7 Gaming and entertainment
8.8 Marketing and advertising
8.9 Others

Chapter 9 Market Estimates & Forecast, By Region, 2021-2032 ($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 Netherlands
- 9.3.8 Rest of Europe
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
- 9.4.6 Southeast Asia
- 9.4.7 Rest of Asia Pacific
9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Argentina
- 9.5.4 Rest of LATAM
9.6 MEA
- 9.6.1 UAE
- 9.6.2 Saudi Arabia
- 9.6.3 South Africa
- 9.6.4 Rest of MEA