アフェクティブコンピューティングの市場規模：技術別、コンポーネント別、最終用途産業別、地域範囲別および予測

アフェクティブコンピューティングの市場規模と予測

アフェクティブコンピューティング市場規模は、2024年に937億1,000万米ドルと評価され、2026～2032年にかけて36.50%のCAGRで成長し、2032年には9,223億9,000万米ドルに達すると予測されます。

アフェクティブコンピューティングは、機械が人間の感情を知覚、解釈、模倣できるようにすることを目的とした技術セグメントです。これには、人工知能（AI）、機械学習、多数の感覚技術を組み合わせて、表情、声のトーン、生理的信号から感情の指標を認識できるシステムを開発することが含まれます。

アフェクティブコンピューティングは、メンタルヘルスのモニタリングや患者のケアを支援するヘルスケア、ドライバーの安全性と経験を向上させる自動車、感情を認識したインタラクションを可能にするカスタマーサービス、学習体験をパーソナライズする教育など、さまざまな産業で応用されています。

さらに、より没入感のあるダイナミック体験を生み出すために、エンターテインメントやゲームでも急速に利用が進んでいます。

世界のアフェクティブコンピューティング市場力学

感情コンピューティング市場を形成している主要市場力学は以下の通りです。

主要市場促進要因

ヘルスケアにおける感情認識システムに対する需要の増加：感情コンピューティング市場の原動力は、メンタルヘルスサポートと感情的幸福ソリューションに対するニーズの高まりです。世界保健機関（WHO）によると、うつ病は世界でおよそ2億8,000万人が罹患しており、不安障害はおよそ3億100万人が罹患しています。メンタルヘルス用途における感情コンピューティングの使用は、これらの病気の早期発見と管理に役立つ可能性があり、それゆえ市場成長を促進します。

顧客サービスにおける感情認識需要の高まり：より良い顧客体験の需要が、顧客サービス用途における感情コンピューティングの使用を促進しています。Gartnerによると、2026年までにカスタマーサービスに電話する顧客の75%は、現在の感情状態に基づいてカスタマイズ型対応を受けると予測しています。感情的にインテリジェントつながりへの期待の高まりが、感情コンピューティング市場の成長を促進しています。

AIと機械学習技術の採用増加：感情コンピューティング市場は、主にAIと機械学習技術の導入の高まりによって牽引されています。Verified Market Researchによると、世界の人工知能市場は2023年に2,295億2,000万米ドル規模であり、2023～2030年にかけて36.4%のCAGRで増加すると予測されています。このAI技術の増加は、感情コンピューティング市場の成長に直接貢献すると予測されています。

主要課題

高い開発・導入コスト：高い開発・実装コストが、感情コンピューティング市場のハードルとなっています。先進的アルゴリズムの開発、データ収集、研究開発にかかるコストは大きいです。こうしたコストが中小企業の参入を阻み、市場全体の拡大を遅らせています。

プライバシーとデータセキュリティ：プライバシーとデータセキュリティへの懸念は、感情コンピューティング市場にとって大きな制約となります。感情データの収集と分析に依存するため、個人情報の悪用や不正アクセスに対する懸念があり、ユーザーは感情コンピューティングシステムを受け入れることに慎重です。データプライバシーを管理する規制の枠組みも拡大しており、この産業の企業にとってコンプライアンス上の余計な問題が生じ、市場の成長を阻害する可能性があります。

主要動向

IoTデバイスとの統合の拡大：感情コンピューティング市場は、スマートホームオートメーション、音声制御ワークステーション、ナビゲーションシステムでジェスチャー制御を可能にするIoTデバイスの人気の高まりから恩恵を受けています。自動車エンターテイメントシステムとの統合は、感情コンピューティングによってより自然で直感的な人間と機械のインタラクションが可能になるため、今後の市場成長を押し上げる可能性が高いです。

AIと機械学習の進歩：人工知能（AI）と機械学習（ML）アルゴリズムの継続的な改善により、感情コンピューティングシステムの精度と信頼性が向上します。顔認識、音声分析、感情検出機能の向上により、人間の感情をより正確に理解できるようになりました。AIと機械学習が進歩するにつれて、感情コンピューティングはより複雑になり、広範囲に利用されるようになると考えられます。

パーソナライズされた体験に対する需要の高まり：人間と技術間のパーソナライズされた感情的インテリジェントインタラクションは、幅広いビジネスで高い需要があります。アフェクティブコンピューティングは、個人の嗜好や感情の状態に基づいた製品やサービスの創造を可能にします。この動向は、ヘルスケア、教育、エンターテインメント、顧客サービスなどの産業で特に顕著であり、アフェクティブコンピューティングは消費者のエンゲージメントと喜びを向上させます。

目次

第1章 イントロダクション

• 市場の定義
• 市場セグメンテーション
• 調査手法

第2章 エグゼクティブサマリー

• 主要調査結果
• 市場概要
• 市場ハイライト

第3章 市場概要

• 市場規模と成長の可能性
• 市場動向
• 市場促進要因
• 市場抑制要因
• 市場機会
• ポーターのファイブフォース分析

第4章 アフェクティブコンピューティング市場：技術別

• タッチベース
• タッチレス

第5章 アフェクティブコンピューティング市場：コンポーネント別

• ハードウェア
• カメラ
• センサ
• ストレージデバイス＆プロセッサ
• その他
• ソフトウェア
• 分析ソフトウェア
• エンタープライズソフトウェア
• 顔認識
• ジェスチャー認識
• 音声認識

第6章 アフェクティブコンピューティング市場：エンドユーザー産業別

• 自動車
• 銀行、金融サービス、保険（BFSI）
• 政府機関
• ヘルスケア
• IT・テレコム
• メディア＆エンターテイメント
• 小売・eコマース
• その他

第7章 地域分析

• 北米
• 米国
• カナダ
• メキシコ
• 欧州
• 英国
• ドイツ
• フランス
• イタリア
• アジア太平洋
• 中国
• 日本
• インド
• オーストラリア
• ラテンアメリカ
• ブラジル
• アルゼンチン
• チリ
• 中東・アフリカ
• 南アフリカ
• サウジアラビア
• アラブ首長国連邦

第8章 市場力学

• 市場促進要因
• 市場抑制要因
• 市場機会
• COVID-19の市場への影響

第9章 競合情勢

• 主要企業
• 市場シェア分析

第10章 企業プロファイル

• Affectiva
• Beyond Verbal
• Emotient
• Galvanic
• iMotions
• OpenFace
• OpenAI
• Parrot Analytics
• Realeyes
• Sensory
• Synapse

第11章 市場展望と機会

• 新興技術
• 今後の市場動向
• 投資機会

第12章 付録

• 略語リスト
• 供給源と参考文献

Affective Computing Market Size and Forecast

Affective Computing Market size was valued at USD 93.71 Billion in 2024 and is projected to reach USD 922.39 Billion by 2032, growing at a CAGR of 36.50% from 2026 to 2032.

Affective computing is a field of technology that aims to help machines perceive, interpret, and imitate human emotions. This entails combining artificial intelligence (AI), machine learning, and numerous sensory technologies to develop systems that can recognize emotional indicators from facial expressions, voice tones, and physiological signals.

Affective computing has applications in a variety of industries, including healthcare, where it aids in mental health monitoring and patient care; automotive, where it improves driver safety and experience; customer service, where it enables emotion-aware interactions; and education, where it personalizes learning experiences.

Furthermore, it is rapidly being used in entertainment and gaming to create more immersive and dynamic experiences.

Global Affective Computing Market Dynamics

The key market dynamics that are shaping the affective computing market include:

Key Market Drivers

Increasing Demand for Emotion-aware Systems in Healthcare: The affective computing market is driven by an increasing need for mental health support and emotional well-being solutions. According to the World Health Organization (WHO), depression affects roughly 280 million individuals worldwide, while anxiety disorders impact approximately 301 million people. The use of affective computing in mental health applications might aid in the early detection and management of these illnesses, hence driving market growth.

Rising Demand for Emotion Recognition in Customer Service: The demand for better customer experiences is driving the use of affective computing in customer service applications. According to Gartner, by 2026, 75% of customers who call customer service anticipate receiving a tailored engagement based on their present emotional state. The growing expectation of emotionally intelligent connections is driving growth in the affective computing market.

Increasing Adoption of AI and Machine Learning Technologies: The affective computing market is being driven primarily by the rising deployment of AI and machine learning technologies. According to Verified Market Research, the global artificial intelligence market was worth USD 229.52 billion in 2023 and is expected to increase at a CAGR of 36.4% between 2023 and 2030. This increase in AI technologies is predicted to directly contribute to the growth of the affective computing market.

Key Challenges:

High Development and Implementation Costs: High development and implementation expenses present a hurdle to the affective computing market. The costs associated with developing advanced algorithms, collecting data, and undertaking research & development are significant. These costs dissuade smaller enterprises from entering the market and slow down the overall expansion of the market.

Privacy and Data Security: Privacy and data security concerns are a big limitation on the affective computing market. Users are aware of embracing affective computing systems because they rely on the collecting and analysis of sensitive emotional data, raising concerns about misuse or illegal access to their personal information. Regulatory frameworks governing data privacy are also expanding, posing extra compliance problems for businesses in this industry and potentially impeding market growth.

Key Trends:

Growing Integration with IoT Devices: The affective computing market is benefiting from the growing popularity of IoT devices that enable gesture control in smart home automation, voice-controlled workstations, and navigation systems. The integration of in-car entertainment systems is likely to boost market growth in the future years, as affective computing allows for more natural and intuitive human-machine interactions.

Advancements in AI and Machine Learning: Continuous improvements in artificial intelligence (AI) and machine learning (ML) algorithms improve the accuracy and dependability of affective computing systems. Improved facial recognition, speech analysis, and sentiment detection capabilities allow for a more accurate understanding of human emotions. As AI and machine learning advance, affective computing will become more complex and extensively used.

Rising Demand for Personalized Experiences: Personalized and emotionally intelligent interactions between humans and technology are in high demand across a wide range of businesses. Affective computing enables the creation of products and services based on individual preferences and emotional states. This trend is especially apparent in industries like healthcare, education, entertainment, and customer service, where affective computing improves consumer engagement and pleasure.

Global Affective Computing Market Regional Analysis

Here is a more detailed regional analysis of the affective computing market:

North America:

According to Verified Market Research, North America is estimated to dominate in affective computing market over the forecast period. North America is the leader in technology innovation and affective computing research. According to the National Science Foundation's 2023 report, the United States alone spent more than $667 billion on research and development across all sectors in 2021. This significant investment in R&D, combined with the presence of large technology businesses and research institutions, is propelling the region's affective computing market forward.

The healthcare industry in North America is quickly integrating AI and affective computing technology. According to the American Hospital Association, 85% of healthcare executives predict that artificial intelligence will significantly enhance patient care by 2026. Also, the United States Food and Drug Administration (FDA) has approved over 100 AI-based medical solutions as of 2023, many of which integrate characteristics of affective computing for patient monitoring and diagnosis.

Furthermore, North American retailers are increasingly using emotion AI to improve their consumer experiences. According to a National Retail Federation Survey, 79% of US merchants intend to invest in AI and machine learning technology by 2025, with emotion identification a top priority. Amazon revealed that its personalized recommendation system, which combines features of affective computing, accounts for 35% of its total sales, demonstrating the importance of these technologies in the retail sector.

Asia Pacific:

The Asia Pacific region is estimated to exhibit the highest growth within the affective computing market during the forecast period. The increasing recognition of mental health issues in the Asia Pacific is boosting the demand for affective computing solutions. According to the World Health Organization, by 2021, around 20% of adults in the Western Pacific Region will have a mental health issue. The growing understanding of mental health challenges is driving the development of emotional AI technologies for early identification and management of mental health issues, resulting in market growth.

Furthermore, the Asia Pacific region is experiencing a spike in AI usage, which is driving growth in the affective computing market. According to the International Data Corporation (IDC), investment in AI systems in the Asia-Pacific region (excluding Japan) is predicted to reach USD 32 Billion by 2025, with a compound annual growth rate (CAGR) of 30.8% between 2020 and 2025. This increasing acceptance of AI technology is driving the growth of affective computing applications in a variety of industries throughout the region.

Europe:

Europe region is estimated to exhibit substantial growth during the forecast period. Europe has made significant investments in AI and robotics research, which directly affects the affective computing market. According to the European Commission, the EU plans to invest €20 billion per year in artificial intelligence over the next decade. This large investment is likely to increase research and development in affective computing technologies, resulting in market growth for the region.

The European automobile sector is increasingly using emotion AI to improve driver safety and experience. According to European Automobile Manufacturers Association (ACEA) research, by 2023, approximately 10% of new cars sold in the EU would have advanced driver monitoring systems, many of which contain emotion recognition technology. This trend is projected to accelerate, boosting the affective computing market in Europe.

Furthermore, the mental health crisis in Europe is driving the use of affective computing technology to provide mental health support. According to the World Health Organization's European Regional Office, around 84 million people in the European Region had mental health issues in 2021. This high prevalence is driving the development and implementation of emotion-aware digital health solutions, which is considerably contributing to the growth of the affective computing market in Europe.

Global Affective Computing Market: Segmentation Analysis

The Affective Computing Market is segmented based on Technology, Component, End-User Industry, and Geography.

Affective Computing Market, By Technology

• Touch-based
• Touchless

Based on Technology, the market is segmented into Touch-based and Touchless. The touch-based segment is estimated to dominate the affective computing market. Touch-based technologies are critical in the deployment of affective computing solutions since they often involve hardware components such as sensors, cameras, and controllers to detect facial emotions and physical gestures. The touch-based segment is projected to continue to grow significantly as the market advances.

Affective Computing Market, By Component

• Hardware
• Cameras
• Sensors
• Storage Devices & Processors
• Others
• Software
• Analytics Software
• Enterprise Software
• Facial Recognition
• Gesture Recognition
• Speech Recognition

Based on Component, the market is divided into Hardware and Software. The hardware segment, particularly the camera is estimated to dominate the market over the forecast period. This dominance is being driven by an increase in demand for advanced video surveillance systems, as well as the integration of cameras into a variety of applications such as smart devices and security systems. Cameras play an important part in affective computing because they enable real-time emotion recognition and analysis, which improves user interaction and engagement in a variety of industries, including healthcare and retail.

Affective Computing Market, By End-User Industry

• Automotive
• Banking, Financial Services and Insurance (BFSI)
• Government
• Healthcare
• IT & Telecom
• Media & Entertainment
• Retail & E-commerce
• Others

Based on the End-User Industry, the affective computing market is divided into Automotive, BFSI, Government, Healthcare, IT& Telecom, Media & Entertainment, Retail & E-commerce, and Others. The healthcare segment is estimated to dominate the market over the forecast period due to the rising use of affective computing technologies in mental health applications, patient monitoring, and treatments. The ability to evaluate emotional states and responses enables healthcare providers to give more individualized care, resulting in better patient outcomes. Furthermore, the growing need for telehealth solutions and remote patient monitoring accelerates the adoption of affective computing in the healthcare industry.

Affective Computing Market, By Geography

• North America
• Europe
• Asia Pacific
• Rest of the World

Based on Geography, the Affective Computing Market is classified into North America, Europe, Asia Pacific, and the Rest of the World. North America is expected to dominate the affective computing market during the forecasted period owing to its superior technological infrastructure and high concentration of important players in the sector. The region benefits from strong R&D investments, particularly in artificial intelligence and machine learning, both of which are critical for affective computing applications. Furthermore, rising demand for emotion detection technology in a variety of industries, including healthcare and automotive, strengthens North America's market leadership.

Key Players

• The "Affective Computing Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are Affectiva, Beyond Verbal, Emotient, Galvanic, iMotions, OpenFace, OpenAI, Parrot Analytics, Realeyes, Sensory, and Synapse.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

• Affective Computing Market Recent Developments
• In February 2021, IBM Corporation partnered with Shree Cement Limited to host its database and key software products on IBM POWER9-based Power Systems running Red Hat and AIX. Shree Cement uses Oracle Enterprise Command Center on Red Hat Enterprise Linux to automate supply chain processes. This change will enhance the organization's operational decisions, procedures, supply chain efficiency, and cost and revenue management.

TABLE OF CONTENTS

1. Introduction

• Market Definition
• Market Segmentation
• Research Methodology

2. Executive Summary

• Key Findings
• Market Overview
• Market Highlights

3. Market Overview

• Market Size and Growth Potential
• Market Trends
• Market Drivers
• Market Restraints
• Market Opportunities
• Porter's Five Forces Analysis

4. Affective Computing Market, By Technology

• Touch-based
• Touchless

5. Affective Computing Market, By Component

• Hardware
• Cameras
• Sensors
• Storage Devices & Processors
• Others
• Software
• Analytics Software
• Enterprise Software
• Facial Recognition
• Gesture Recognition
• Speech Recognition

6. Affective Computing Market, By End-user Industry

• Automotive
• Banking, Financial Services and Insurance (BFSI)
• Government
• Healthcare
• IT & Telecom
• Media & Entertainment
• Retail & E-commerce
• Others

7. Regional Analysis

• North America
• United States
• Canada
• Mexico
• Europe
• United Kingdom
• Germany
• France
• Italy
• Asia-Pacific
• China
• Japan
• India
• Australia
• Latin America
• Brazil
• Argentina
• Chile
• Middle East and Africa
• South Africa
• Saudi Arabia
• UAE

8. Market Dynamics

• Market Drivers
• Market Restraints
• Market Opportunities
• Impact of COVID-19 on the Market

9. Competitive Landscape

• Key Players
• Market Share Analysis

10. Company Profiles

• Affectiva
• Beyond Verbal
• Emotient
• Galvanic
• iMotions
• OpenFace
• OpenAI
• Parrot Analytics
• Realeyes
• Sensory
• Synapse

11. Market Outlook and Opportunities

• Emerging Technologies
• Future Market Trends
• Investment Opportunities

12. Appendix

• List of Abbreviations
• Sources and References