세계의 감정 AI 시장 : 제공 제품별, 유형별, 기술별, 용도별, 업계별, 지역별 - 예측(-2030년)
Emotion AI Market by Solutions (Emotion Recognition, Emotion AI SDKs and APIs, Emotion Analytics), Type (Text-Focused, Voice-Focused, Video & Multimodal), Technology (Machine Learning, NLP, Computer Vision) - Global Forecast to 2030
상품코드:1618945
리서치사:MarketsandMarkets
발행일:2024년 12월
페이지 정보:영문 300 Pages
라이선스 & 가격 (부가세 별도)
ㅁ Add-on 가능: 고객의 요청에 따라 일정한 범위 내에서 Customization이 가능합니다. 자세한 사항은 문의해 주시기 바랍니다.
한글목차
감정 AI 시장 규모는 2024년에 27억 4,000만 달러로 평가되었고, 2030년에는 90억 1,000만 달러에 달할 것으로 보이며, 2024년부터 2030년까지 CAGR은 21.9%로 예측되고 있습니다.
감정 AI 시장은 감정 중심의 마케팅, IoT 및 웨어러블과의 통합, 원격 근무 환경에 대한 도입으로 급성장하고 있습니다. 감정 AI는 마케팅 담당자가 잡힌 캠페인을 만들고 높은 참여율과 전환율을 홍보하는 데 사용됩니다. IoT 및 웨어러블 디바이스를 통한 실시간 감정 추적은 의료 및 피트니스에 적용할 수 있습니다. 감정 AI를 이용한 원격 근무은 감정의 단서를 처리하여 가상 협업의 능력을 높이고, 커뮤니케이션을 개선하고, 생산성을 향상시키고, 다양한 업계에서 감정 인텔리전스의 미래를 확립합니다.
조사 범위
조사 대상년도
2019-2030년
기준년
2023년/td
예측 기간
2024-2030년
검토 단위
달러(10억 달러)
부문별
제공 제품별, 유형별, 기술별, 용도별, 업계별, 지역별
대상 지역
북미, 유럽, 아시아태평양, 중동, 아프리카, 라틴아메리카
머신러닝(ML) 기술은 엄청난 양의 데이터를 처리하고 인간의 감정의 복잡한 패턴을 학습하는 능력이 있기 때문에 감정 AI 시장에서 가장 높은 시장 점유율을 차지합니다. ML 알고리즘은 표정, 음성 톤, 텍스트 감정을 분석하여 정확한 감정 감지와 실시간 의사 결정을 가능하게 합니다. 이러한 기술은 다양한 데이터 세트에서의 교육을 통해 지속적으로 개선되므로 소매, 건강 관리, 고객 서비스 등 다양한 산업에 적응성이 높습니다. ML 기반 감정 인식 시스템은 개인화된 마케팅, 가상 어시스턴트, 정신 건강 모니터링 등의 분야에 점점 통합되어 고객 참여와 만족도를 높이고 있습니다. 머신러닝 모델의 확장성, 효율성 및 진화하는 성질은 감정 AI의 지배적인 기술이며, 급속한 성장과 다양한 분야에서 광범위한 채택을 지원합니다.
텍스트에 특화된 감정 AI는 다양한 업계에서 널리 적용 가능하며, 매일 생성되는 텍스트 데이터의 양이 증가하고 있기 때문에 감정 AI 시장에서 가장 급성장하고 있는 분야입니다. 자연언어처리(NLP)와 기계학 실습의 진보로 텍스트 기반의 감정 분석은 고객 리뷰, 소셜 미디어 게시, 커뮤니케이션 플랫폼에서의 기쁨, 분노, 슬픔 등의 감정을 검출하는 정밀도가 높아지고 있습니다. 이 기술은 기업이 고객 경험 관리를 개선하고 마케팅 전략을 최적화하며 브랜드 참여도를 높이는 데 도움이 됩니다. 중요한 역할을 수행합니다. 디지털 커뮤니케이션에 대한 의존도가 높아짐에 따라 텍스트에 중점을 둔 감정 분석에 대한 수요가 증가하고 있으며 감정 AI 시장의 주요 성장 촉진요인이 되었습니다.
아시아태평양은 기술의 상승 속도, 디지털 도입 증가, 다양한 분야에서의 감정 AI의 광범위한 용도를 이유로 감정 AI 시장 내에서 가장 높은 성장률을 나타내는 것으로 추정됩니다. 중국, 일본, 인도를 포함한 많은 국가들이 감정인식 AI 등의 분야인 AI 연구개발에 많은 투자를 하고 있습니다. e커머스, 소매, 헬스케어의 각 영역의 조직은 현재 일관되게 고객 경험을 향상시키는 개인화된 서비스를 제공하기 위해 감정 인식 AI를 이용하기 시작하고 있습니다. 또한 이 지역은 모바일 기기, IoT, 웨어러블 기술의 보급이 한창이며 실시간 감정 트래킹을 위한 우수한 기반으로 기능하고 있습니다. 아시아 태평양 지역의 주요 정부 및 민간 기업들은 전략적 성장 분야로서 AI에 결집하고 있으며, 이것이 감정 인식 AI 기술의 채택에도 박차를 가하고 있습니다. 기술, 경제, 인구 통계학적 요인이 맞물려 아시아 태평양은 대규모 시장 성장을 이룰 것으로 전망되고 있습니다.
본 보고서에서는 세계의 감정 AI 시장에 대해 조사했으며, 제공 제품별, 유형별, 기술별, 용도별, 업계별, 지역별 동향 및 시장 진출기업 프로파일 등을 정리했습니다.
목차
제1장 서론
제2장 조사 방법
제3장 주요 요약
제4장 중요 인사이트
제5장 시장 개요 및 업계 동향
서문
시장 역학
감정 AI의 진화
생태계 분석
사례 연구 분석
공급망 분석
관세 및 규제 상황
가격 분석
기술 분석
특허 분석
Porter's Five Forces 분석
고객사업에 영향을 주는 동향 및 혼란
주요 이해관계자와 구매 기준
주된 회의 및 이벤트(2024-2025년)
감정 AI 시장의 기술 로드맵
감정 AI의 모범 사례
현재의 비즈니스 모델 및 새로운 비즈니스 모델
감정 AI에서 사용되는 도구, 프레임 워크 및 기술
무역 분석
투자와 자금조달 시나리오
AI 및 생성형 AI가 감정 AI 시장에 미치는 영향
제6장 감정 AI 시장 : 제공 제품별
서문
솔루션
서비스
제7장 감정 AI 시장 : 유형별
서문
텍스트 중심
음성 중시
비디오 및 멀티모달
제8장 감정 AI 시장 : 기술별
서문
머신러닝
자연언어처리
컴퓨터 비전
생리학적 신호 처리
제9장 감정 AI 시장 : 용도별
서문
고객 경험 경영
마케팅, 판매, 광고
퍼스널 어시스턴트 및 가상 에이전트
정신 건강 및 건강 상태 모니터링
드라이버의 안전과 감시
인사 및 채용
기타
제10장 감정 AI 시장 : 업계별
서문
소매 및 E-Commerce
IT 및 ITES
헬스케어
교육, 학술, 조사
자동차
미디어 및 엔터테인먼트
여행 및 접객
기타
제11장 감정 AI 시장 : 지역별
서문
북미
북미의 거시경제 전망
미국
캐나다
유럽
유럽의 거시 경제 전망
영국
독일
프랑스
이탈리아
스페인
북유럽 국가
기타
아시아태평양
아시아태평양의 거시 경제 전망
중국
일본
인도
호주 및 뉴질랜드
한국
기타
중동 및 아프리카
중동 및 아프리카의 거시경제 전망
아랍에미리트(UAE)
사우디아라비아
쿠웨이트
바레인
남아프리카
기타
라틴아메리카
라틴아메리카의 거시 경제 전망
브라질
멕시코
기타
제12장 경쟁 구도
서문
주요 진입기업의 전략 및 강점
수익 분석
시장 점유율 분석
기업평가 매트릭스 : 주요 진입기업(2023년)
기업평가 매트릭스 : 스타트업 및 중소기업(2023년)
경쟁 시나리오 및 동향
브랜드 및 제품 비교
주요 감정 AI 솔루션 공급자의 기업 평가 및 재무 지표
제13장 기업 프로파일
주요 진출기업
IBM
MICROSOFT
GOOGLE
AMAZON
SMART EYE
ENTROPIK
UNIPHORE
AUDEERING GMBH
VIER GMBH
COGNITEC
기타 기업
SYMANTO
REALEYES
CIPIA VISION
NOLDUS
COGITO
MORPHCAST
VOICESENSE
SUPERCEED
SIENA AI
OPSIS
BEHAVIORAL SIGNALS
HUME
KAIROS
BEEMOTION.AI
INTELLIGENT VOICE
DAVI
UTRIGG
ATTENTIONKART
VERN AI
제14장 인접 시장 및 관련 시장
제15장 부록
AJY
영문 목차
영문목차
The Emotion AI market is estimated to be USD 2.74 billion in 2024 to USD 9.01 billion in 2030 at a CAGR of 21.9% from 2024 to 2030. The Emotion AI market is undergoing rapid growth due to emotion driven marketing, integration with IoT and wearables, and adoption to the remote work environment. Emotion AI is used by marketers to create catchy campaigns, driving high engagement and conversion rates. Real-time emotion tracking with IoT and wearable devices makes healthcare and fitness applications possible. Remote work with Emotion AI boosts the capability for virtual collaboration by processing emotion cues to improve communication, increase productivity, and establish the future of emotional intelligence within different industries.
Scope of the Report
Years Considered for the Study
2019-2030
Base Year
2023
Forecast Period
2024-2030
Units Considered
USD (Billion)
Segments
By Offering, Type, Technology, Application, Industry and Region
Regions covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
"During the forecast period, the Machine Learning technology contributed the largest market share in the Emotion AI market."
Machine learning (ML) technology holds the highest market share in the Emotion AI market due to its ability to process vast amounts of data and learn complex patterns in human emotions. ML algorithms can analyze facial expressions, voice tones, and textual sentiment, enabling accurate emotion detection and real-time decision-making. These technologies continuously improve through training on diverse datasets, making them highly adaptable to different industries such as retail, healthcare, and customer service. ML-based emotion recognition systems are increasingly integrated into applications such as personalized marketing, virtual assistants, and mental health monitoring, driving customer engagement and satisfaction. The scalability, efficiency, and evolving nature of machine learning models make it the dominant technology in Emotion AI, supporting its rapid growth and broad adoption across various sectors.
"The text focused type of Emotion AI is projected to register the highest CAGR during the forecast period."
Text-focused Emotion AI is the fastest-growing segment in the Emotion AI market due to its widespread applicability across various industries and the increasing volume of textual data generated daily. With advancements in natural language processing (NLP) and machine learning, text-based sentiment analysis has become more accurate in detecting emotions such as joy, anger, and sadness in customer reviews, social media posts, and communication platforms. This technology helps businesses improve customer experience management, optimize marketing strategies, and enhance brand engagement. It also plays a crucial role in healthcare for mental health assessments and in educational tools for personalized learning. As the reliance on digital communication grows, the demand for text-focused emotion analysis continues to rise, positioning it as a key driver of growth in the Emotion AI market.
"Asia Pacific will register the highest growth rate during the forecast period."
The Asia Pacific region is estimated to have the highest growth rate within the Emotion AI market on account of its rising pace of technology, increased digital adoption, and extensive application of Emotion AI in various fields. Many countries, including China, Japan, and India, are investing a lot in AI research and development, which are fields such as emotional AI. Organizations within the e-commerce, retail, and healthcare domains are now starting to use Emotion AI to deliver personalized services that consistently improve customer experiences. Furthermore, the region is in the midst of wide dissemination of mobile devices, IoT, and wearable technology, which acts as an excellent basis for performing real-time emotion tracking. Leading governments and private enterprises in Asia Pacific are rallying around AI as a strategic growth area, which is also fueling the adoption of Emotional AI technologies. Technology, economic and demographic factors combine to put Asia Pacific in a position for massive market growth.
Breakdown of primaries
The study contains insights from various industry experts, from solution vendors to Tier 1 companies. The break-up of the primaries is as follows:
By Company Type: Tier 1 - 62%, Tier 2 - 23%, and Tier 3 - 15%
By Designation: C-level -50%, D-level - 30%, and Others - 20%
By Region: North America - 38%, Europe - 15%, Asia Pacific - 35%, Middle East & Africa- 7%, and Latin America- 5%.
The major players in the Emotion AI market are IBM (US), Microsoft (US), Google (US), Amazon (US), Smart Eye (Sweden), Entropik Tech (India), Uniphore (US), Audeering GmbH (Germany), VIER GmbH (Germany), Cognitec (Germany), Symanto (Germany), Realeyes (UK), CIPIA Vision (Israel), Noldus (Netherlands), Cogito (US), Morphcast (US), Voicesense (Israel), Superceed (Malaysia), Siena AI (US), Opsis (Singapore), Behavioral Signals (US), Hume (US), Kairos (US), Beemotion.AI (Australia), Intelligent Voice (UK), Davi (France), Utrigg (Ukraine), AttentionKart (India) and VERN AI (US). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, enhancements, and acquisitions to expand their Emotion AI footprint.
Research Coverage
The market study covers the Emotion AI market size across different segments. It aims to estimate the market size and the growth potential across various segments, including offering, technology, application, industry, and region. The study includes an in-depth competitive analysis of the leading market players, their company profiles, key observations related to product and business offerings, recent developments, and market strategies.
Key Benefits of Buying the Report
The report will help market leaders and new entrants with information on the closest approximations of the global Emotion AI market's revenue numbers and subsegments. It will also help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies. Moreover, the report will provide insights for stakeholders to understand the market's pulse and provide them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
Analysis of key drivers (improved Computational Power, increased adoption of Video Communication Platforms, increased applications in education, enhancing checkout experiences with AI-powered automation), restraints (lack of standardization, high dependence on data quality), opportunities (emotion-based content creation, development of driver monitoring systems, integration in educational platforms) and challenges (overcoming bias in AI systems, training complex models, integrating multimodal data) influencing the growth of the Emotion AI market.
Product Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and new product and service launches in the Emotion AI market. Market Development: Comprehensive information about lucrative markets - the report analyses various regions' Emotion AI markets. Market Diversification: Exhaustive information about new products and services, untapped geographies, recent developments, and investments in the Emotion AI market. Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players such as IBM (US), Microsoft (US), Google (US), Amazon (US), Smart Eye (Sweden), Entropik Tech (India), Uniphore (US), Audeering GmbH (Germany), VIER GmbH (Germany), Cognitec (Germany), Symanto (Germany), Realeyes (UK), CIPIA Vision (Israel), Noldus (Netherlands), Cogito (US), Morphcast (US), Voicesense (Israel), Superceed (Malaysia), Siena AI (US), Opsis (Singapore), Behavioral Signals (US), Hume (US), Kairos (US), Beemotion.AI (Australia), Intelligent Voice (UK), Davi (France), Utrigg (Ukraine), AttentionKart (India) and VERN AI (US).
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKET SEGMENTATION
1.3.2 INCLUSIONS AND EXCLUSIONS
1.3.3 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
1.5 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.1.1 Key data from secondary sources
2.1.2 PRIMARY DATA
2.1.2.1 Breakup of primary interviews
2.1.2.2 Primary interviews with experts
2.1.2.3 Expert insights
2.2 MARKET SIZE ESTIMATION METHODOLOGY
2.2.1 TOP-DOWN APPROACH
2.2.1.1 Supply-side analysis
2.2.2 BOTTOM-UP APPROACH
2.2.2.1 Demand-side analysis
2.3 DATA TRIANGULATION
2.4 RESEARCH ASSUMPTIONS
2.5 RESEARCH LIMITATIONS
2.6 RISK ASSESSMENT
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR KEY PLAYERS IN EMOTION AI MARKET
4.2 EMOTION AI MARKET, BY OFFERING
4.3 EMOTION AI MARKET, BY SERVICE
4.4 EMOTION AI MARKET, BY TYPE
4.5 EMOTION AI MARKET, BY TECHNOLOGY
4.6 EMOTION AI MARKET, BY APPLICATION
4.7 EMOTION AI MARKET, BY INDUSTRY
4.8 ASIA PACIFIC: EMOTION AI MARKET, TOP THREE SOLUTIONS AND SERVICES
5 MARKET OVERVIEW AND INDUSTRY TRENDS
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Growing demand for customer experience enhancement
5.2.1.2 Advancements in AI and machine learning technologies
5.2.1.3 Increased application in healthcare and education
5.2.2 RESTRAINTS
5.2.2.1 Privacy and data security concerns
5.2.2.2 High implementation costs
5.2.3 OPPORTUNITIES
5.2.3.1 Expansion into new verticals
5.2.3.2 Integration with IoT and wearable devices
5.2.3.3 Growing demand in remote work and virtual environments
5.2.4 CHALLENGES
5.2.4.1 Addressing cultural and contextual variability
5.2.4.2 Gaining user trust and acceptance
5.3 EVOLUTION OF EMOTION AI
5.4 ECOSYSTEM ANALYSIS
5.5 CASE STUDY ANALYSIS
5.5.1 CASE STUDY 1: HOTEL AND CASINO LEADER LEVERAGES UNIPHORE'S SOLUTIONS TO ENHANCE CUSTOMER EXPERIENCE
5.5.2 CASE STUDY 2: META ENHANCES ADVERTISING EXPERIENCE USING REALEYES SOLUTIONS FOR EMOTIONAL RESPONSE MEASUREMENT
5.5.3 CASE STUDY 3: MCDONALD'S ENHANCES SITUATIONAL ADVERTISING FOCUSING ON DIRECT CONSUMER ENGAGEMENT AND PERSONALIZATION
5.5.4 CASE STUDY 4: ENTROPIK ENHANCES PRODUCT EXPERIENCES WITH REAL-TIME ANALYSIS OF CONSUMER EMOTIONS FOR CPG BRAND
5.5.5 CASE STUDY 5: SMARTBOX USES EYE-TRACKING SOLUTIONS FROM SMART EYE FOR ASSISTED LIVING
5.6 SUPPLY CHAIN ANALYSIS
5.7 TARIFF AND REGULATORY LANDSCAPE
5.7.1 TARIFF DATA (HSN: 854231) - PROCESSORS AND CONTROLLERS
5.7.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.7.3 KEY REGULATIONS
5.7.3.1 North America
5.7.3.1.1 SCR 17: Artificial Intelligence Bill (California)
5.7.3.1.2 S1103: Artificial Intelligence Automated Decision Bill (Connecticut)
5.7.3.1.3 National Artificial Intelligence Initiative Act (NAIIA)
5.7.3.1.4 The Artificial Intelligence and Data Act (AIDA) - Canada
5.7.3.2 Europe
5.7.3.2.1 The European Union (EU) - Artificial Intelligence Act (AIA)
5.7.3.2.2 General Data Protection Regulation (Europe)
5.7.3.3 Asia Pacific
5.7.3.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services (China)
5.7.3.3.2 The National AI Strategy (Singapore)
5.7.3.3.3 The Hiroshima AI Process Comprehensive Policy Framework (Japan)
5.7.3.4 Middle East & Africa
5.7.3.4.1 The National Strategy for Artificial Intelligence (UAE)
5.7.3.4.2 The National Artificial Intelligence Strategy (Qatar)
5.7.3.4.3 The AI Ethics Principles and Guidelines (Dubai)
5.7.3.5 Latin America
5.7.3.5.1 The Santiago Declaration (Chile)
5.7.3.5.2 The Brazilian Artificial Intelligence Strategy (EBIA)
5.8 PRICING ANALYSIS
5.8.1 PRICE TREND OF KEY PLAYERS, BY SOLUTION
5.8.2 INDICATIVE PRICING ANALYSIS, BY KEY PLAYER AND APPLICATION
5.8.3 INDICATIVE PRICING ANALYSIS, BY SME AND APPLICATION
5.9 TECHNOLOGY ANALYSIS
5.9.1 KEY TECHNOLOGIES
5.9.1.1 Speech recognition and audio analysis
5.9.1.2 Facial micro-expression recognition
5.9.1.3 Text emotion recognition
5.9.1.4 Pose-based emotion recognition
5.9.1.5 Behavioral analytics
5.9.1.6 Emotion recognition algorithms
5.9.2 COMPLEMENTARY TECHNOLOGIES
5.9.2.1 Internet of Things
5.9.2.2 Edge computing
5.9.2.3 Cloud computing
5.9.2.4 Biometrics
5.9.3 ADJACENT TECHNOLOGIES
5.9.3.1 Augmented reality and virtual reality
5.9.3.2 Human-computer interaction
5.9.3.3 Predictive analytics
5.10 PATENT ANALYSIS
5.10.1 METHODOLOGY
5.11 PORTER'S FIVE FORCES ANALYSIS
5.11.1 THREAT OF NEW ENTRANTS
5.11.2 THREAT OF SUBSTITUTES
5.11.3 BARGAINING POWER OF BUYERS
5.11.4 BARGAINING POWER OF SUPPLIERS
5.11.5 INTENSITY OF COMPETITIVE RIVALRY
5.12 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
5.13 KEY STAKEHOLDERS AND BUYING CRITERIA
5.13.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.13.2 BUYING CRITERIA
5.14 KEY CONFERENCES AND EVENTS, 2024-2025
5.15 TECHNOLOGY ROADMAP FOR EMOTION AI MARKET
5.15.1 EMOTION AI TECHNOLOGY ROADMAP TILL 2030
5.15.1.1 Short-term roadmap (2024-2026)
5.15.1.2 Mid-term roadmap (2026-2028)
5.15.1.3 Long-term roadmap (2028-2030)
5.16 BEST PRACTICES FOR EMOTION AI
5.17 CURRENT AND EMERGING BUSINESS MODELS
5.18 TOOLS, FRAMEWORKS, AND TECHNIQUES USED IN EMOTION AI
5.19 TRADE ANALYSIS
5.19.1 EXPORT SCENARIO OF PROCESSORS AND CONTROLLERS
5.19.2 IMPORT SCENARIO OF PROCESSORS AND CONTROLLERS
5.20 INVESTMENT AND FUNDING SCENARIO
5.21 IMPACT OF AI/GENERATIVE AI ON EMOTION AI MARKET
5.21.1 USE CASES OF GENERATIVE EMOTION AI
6 EMOTION AI MARKET, BY OFFERING
6.1 INTRODUCTION
6.1.1 OFFERINGS: EMOTION AI MARKET DRIVERS
6.2 SOLUTIONS
6.2.1 EMOTION RECOGNITION
6.2.1.1 Enhanced engagement and sales in retail to drive segment
6.2.2 EMOTION AI SDKS & APIS
6.2.2.1 Ability to integrate advanced emotion recognition and analysis capabilities to boost segment
6.2.3 EMOTION ANALYTICS
6.2.3.1 Ability to provide personalized customer experiences to drive market
6.2.4 OTHER SOLUTIONS
6.3 SERVICES
6.3.1 PROFESSIONAL SERVICES
6.3.1.1 Ensure seamless integration, optimal utilization, and consistent performance of AI systems
6.3.1.2 Training & development
6.3.1.3 Deployment & system integration
6.3.1.4 Support & maintenance
6.3.2 MANAGED SERVICES
6.3.2.1 Optimize solutions without additional internal resources to boost market
7 EMOTION AI MARKET, BY TYPE
7.1 INTRODUCTION
7.1.1 TYPES: EMOTION AI MARKET DRIVERS
7.2 TEXT-FOCUSED
7.3 VOICE-FOCUSED
7.4 VIDEO & MULTIMODAL
8 EMOTION AI MARKET, BY TECHNOLOGY
8.1 INTRODUCTION
8.1.1 TECHNOLOGIES: EMOTION AI MARKET DRIVERS
8.2 MACHINE LEARNING
8.2.1 PROCESSES LARGE DATASETS TO IDENTIFY PATTERNS THAT CORRELATE WITH EMOTIONS
8.3 NATURAL LANGUAGE PROCESSING
8.3.1 PROVIDES SENTIMENT ANALYSIS THAT CAN CLASSIFY EMOTIONAL TONE OF TEXT
8.4 COMPUTER VISION
8.4.1 USES DEEP LEARNING MODELS TO RECOGNIZE HUMAN FACIAL EXPRESSIONS, BODY MOVEMENTS, AND GESTURES
8.5 PHYSIOLOGICAL SIGNAL PROCESSING
8.5.1 DETECTS EMOTIONAL STATES SUCH AS STRESS, EXCITEMENT, OR RELAXATION
9 EMOTION AI MARKET, BY APPLICATION
9.1 INTRODUCTION
9.1.1 APPLICATIONS: EMOTION AI MARKET DRIVERS
9.2 CUSTOMER EXPERIENCE MANAGEMENT
9.2.1 USED TO IDENTIFY CUSTOMERS' EMOTIONAL STATES AND ENHANCE SERVICE QUALITY
9.3 MARKETING, SALES, AND ADVERTISING
9.3.1 OPTIMIZATION OF MARKETING STRATEGIES FOR BETTER EMOTIONAL RESONANCE
9.4 PERSONAL ASSISTANTS & VIRTUAL AGENTS
9.4.1 OFFER TAILORED RESPONSES AND PERSONALIZED INTERACTIONS
9.5 MENTAL HEALTH & WELL-BEING MONITORING
9.5.1 HELP WITH EARLY DETECTION ANXIETY, DEPRESSION, OR STRESS
9.6 DRIVER SAFETY & MONITORING
9.6.1 DETECT SIGNS OF FATIGUE, DISTRACTION, OR STRESS AND ALERT DRIVER
9.7 HUMAN RESOURCES & RECRUITMENT
9.7.1 ASSESS EMOTIONAL INTELLIGENCE DURING HIRING AND TRACK EMPLOYEE SENTIMENT
9.8 OTHER APPLICATIONS
10 EMOTION AI MARKET, BY INDUSTRY
10.1 INTRODUCTION
10.1.1 INDUSTRIES: EMOTION AI MARKET DRIVERS
10.2 RETAIL & E-COMMERCE
10.2.1 PERSONALIZED SHOPPING EXPERIENCES TO CATER TO EMOTIONAL NEEDS OF CUSTOMERS
10.3 IT & ITES
10.3.1 BOOSTS EMPLOYEE ENGAGEMENT THROUGH ANALYSIS OF WORKER SENTIMENT AND WORKLOAD ADJUSTMENT
10.4 HEALTHCARE
10.4.1 NLP AND EMOTIONAL INTELLIGENCE PROVIDE THERAPY SUPPORT
10.5 EDUCATION, ACADEMIA, AND RESEARCH
10.5.1 HELPS EDUCATORS UNDERSTAND LEVEL OF ENGAGEMENT OR STRESS AMONG STUDENTS
10.6 AUTOMOTIVE
10.6.1 ENHANCES ROAD SAFETY AND ENABLES PERSONALIZED DRIVING EXPERIENCE
10.7 MEDIA & ENTERTAINMENT
10.7.1 ENHANCES CONTENT CREATION, ADVERTISING, AND CONSUMER ENGAGEMENT
10.8 TRAVEL & HOSPITALITY
10.8.1 TAILORED, RESPONSIVE, AND EMPATHETIC SERVICES TO BOOST SEGMENT
10.9 OTHER INDUSTRIES
11 EMOTION AI MARKET, BY REGION
11.1 INTRODUCTION
11.2 NORTH AMERICA
11.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA
11.2.2 US
11.2.2.1 Strategic partnerships to drive emotion AI adoption
11.2.3 CANADA
11.2.3.1 Government initiatives and investments to drive market
11.3 EUROPE
11.3.1 MACROECONOMIC OUTLOOK FOR EUROPE
11.3.2 UK
11.3.2.1 Rapid cloud adoption and strong digital strategy to boost market
11.3.3 GERMANY
11.3.3.1 High demand from automotive industry - key driver
11.3.4 FRANCE
11.3.4.1 Strong growth prospects amid digital transformation and need for tailored experiences
11.3.5 ITALY
11.3.5.1 Increasing adoption of emotion detection technologies and government commitment to fostering innovation to drive market
11.3.6 SPAIN
11.3.6.1 Strategic initiatives in AI development sector to drive market
11.3.7 NORDIC COUNTRIES
11.3.7.1 Comprehensive AI strategies, robust talent pool to drive market
11.3.8 REST OF EUROPE
11.4 ASIA PACIFIC
11.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
11.4.2 CHINA
11.4.2.1 Increased government investment in new technologies to drive market
11.4.3 JAPAN
11.4.3.1 Healthcare and retail present market opportunities
11.4.4 INDIA
11.4.4.1 Focus on advanced technology usage through government initiatives to drive market
11.4.5 AUSTRALIA & NEW ZEALAND
11.4.5.1 Increasing need for enhanced customer experience to drive market
11.4.6 SOUTH KOREA
11.4.6.1 Strong focus on developing and enhancing public-private partnerships to drive market
11.4.7 REST OF ASIA PACIFIC
11.5 MIDDLE EAST & AFRICA
11.5.1 MACROECONOMIC OUTLOOK FOR MIDDLE EAST & AFRICA
11.5.2 UAE
11.5.2.1 Increasing use of AI in smart city development to drive market
11.5.3 SAUDI ARABIA
11.5.3.1 Substantial investments in digital infrastructure to drive market
11.5.4 KUWAIT
11.5.4.1 Focus on knowledge-based economy to drive market
11.5.5 BAHRAIN
11.5.5.1 Focus on alternative revenue options to drive market
11.5.6 SOUTH AFRICA
11.5.6.1 Growing focus on digital transformation and innovation to drive market
11.5.7 REST OF MIDDLE EAST & AFRICA
11.6 LATIN AMERICA
11.6.1 MACROECONOMIC OUTLOOK FOR LATIN AMERICA
11.6.2 BRAZIL
11.6.2.1 Increasing adoption of digital technology to drive market
11.6.3 MEXICO
11.6.3.1 Focus on advancing digital infrastructure to drive market
11.6.4 REST OF LATIN AMERICA
12 COMPETITIVE LANDSCAPE
12.1 INTRODUCTION
12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
12.2.1 OVERVIEW OF STRATEGIES ADOPTED BY KEY EMOTION AI VENDORS
12.3 REVENUE ANALYSIS
12.4 MARKET SHARE ANALYSIS
12.4.1 MARKET RANKING ANALYSIS
12.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
12.5.1 STARS
12.5.2 EMERGING LEADERS
12.5.3 PERVASIVE PLAYERS
12.5.4 PARTICIPANTS
12.5.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
12.5.5.1 Company footprint
12.5.5.2 Type footprint
12.5.5.3 Offering footprint
12.5.5.4 Regional footprint
12.6 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
