세계의 감정 AI 시장 : 제공 제품별, 유형별, 기술별, 용도별, 업계별, 지역별 - 예측(-2030년)

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.

"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
  • 12.6.1 PROGRESSIVE COMPANIES
  • 12.6.2 RESPONSIVE COMPANIES
  • 12.6.3 DYNAMIC COMPANIES
  • 12.6.4 STARTING BLOCKS
  • 12.6.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    • 12.6.5.1 Key startups/SMEs
    • 12.6.5.2 Competitive benchmarking of key startups/SMEs
• 12.7 COMPETITIVE SCENARIOS AND TRENDS
  • 12.7.1 PRODUCT LAUNCHES & ENHANCEMENTS
  • 12.7.2 DEALS
• 12.8 BRAND/PRODUCT COMPARISON
• 12.9 COMPANY VALUATION AND FINANCIAL METRICS OF KEY EMOTION AI SOLUTION PROVIDERS

13 COMPANY PROFILES

• 13.1 KEY PLAYERS
  • 13.1.1 IBM
    • 13.1.1.1 Business overview
    • 13.1.1.2 Products/Solutions/Services offered
    • 13.1.1.3 Recent developments
      • 13.1.1.3.1 Product enhancements
      • 13.1.1.3.2 Deals
    • 13.1.1.4 MnM view
      • 13.1.1.4.1 Right to win
      • 13.1.1.4.2 Strategic choices
      • 13.1.1.4.3 Weaknesses and competitive threats
  • 13.1.2 MICROSOFT
    • 13.1.2.1 Business overview
    • 13.1.2.2 Products/Solutions/Services offered
    • 13.1.2.3 Recent developments
      • 13.1.2.3.1 Product enhancements
      • 13.1.2.3.2 Deals
    • 13.1.2.4 MnM view
      • 13.1.2.4.1 Right to win
      • 13.1.2.4.2 Strategic choices
      • 13.1.2.4.3 Weaknesses and competitive threats
  • 13.1.3 GOOGLE
    • 13.1.3.1 Business overview
    • 13.1.3.2 Products/Solutions/Services offered
    • 13.1.3.3 Recent developments
      • 13.1.3.3.1 Product enhancements
      • 13.1.3.3.2 Deals
    • 13.1.3.4 MnM view
      • 13.1.3.4.1 Right to win
      • 13.1.3.4.2 Strategic choices
      • 13.1.3.4.3 Weaknesses and competitive threats
  • 13.1.4 AMAZON
    • 13.1.4.1 Business overview
    • 13.1.4.2 Products/Solutions/Services offered
    • 13.1.4.3 Recent developments
      • 13.1.4.3.1 Product enhancements
    • 13.1.4.4 MnM view
      • 13.1.4.4.1 Right to win
      • 13.1.4.4.2 Strategic choices
      • 13.1.4.4.3 Weaknesses and competitive threats
  • 13.1.5 SMART EYE
    • 13.1.5.1 Business overview
    • 13.1.5.2 Products/Solutions/Services offered
    • 13.1.5.3 Recent developments
      • 13.1.5.3.1 Deals
    • 13.1.5.4 MnM view
      • 13.1.5.4.1 Right to win
      • 13.1.5.4.2 Strategic choices
      • 13.1.5.4.3 Weaknesses and competitive threats
  • 13.1.6 ENTROPIK
    • 13.1.6.1 Business overview
    • 13.1.6.2 Products/Solutions/Services offered
    • 13.1.6.3 Recent developments
      • 13.1.6.3.1 Product enhancements
  • 13.1.7 UNIPHORE
    • 13.1.7.1 Business overview
    • 13.1.7.2 Products/Solutions/Services offered
    • 13.1.7.3 Recent developments
      • 13.1.7.3.1 Product launches
      • 13.1.7.3.2 Deals
  • 13.1.8 AUDEERING GMBH
    • 13.1.8.1 Business overview
    • 13.1.8.2 Products/Solutions/Services offered
    • 13.1.8.3 Recent developments
      • 13.1.8.3.1 Product enhancements
      • 13.1.8.3.2 Deals
  • 13.1.9 VIER GMBH
    • 13.1.9.1 Business overview
    • 13.1.9.2 Products/Solutions/Services offered
    • 13.1.9.3 Recent developments
      • 13.1.9.3.1 Deals
  • 13.1.10 COGNITEC
    • 13.1.10.1 Business overview
    • 13.1.10.2 Products/Solutions/Services offered
    • 13.1.10.3 Recent developments
      • 13.1.10.3.1 Deals
• 13.2 OTHER PLAYERS
  • 13.2.1 SYMANTO
  • 13.2.2 REALEYES
  • 13.2.3 CIPIA VISION
  • 13.2.4 NOLDUS
  • 13.2.5 COGITO
  • 13.2.6 MORPHCAST
  • 13.2.7 VOICESENSE
  • 13.2.8 SUPERCEED
  • 13.2.9 SIENA AI
  • 13.2.10 OPSIS
  • 13.2.11 BEHAVIORAL SIGNALS
  • 13.2.12 HUME
  • 13.2.13 KAIROS
  • 13.2.14 BEEMOTION.AI
  • 13.2.15 INTELLIGENT VOICE
  • 13.2.16 DAVI
  • 13.2.17 UTRIGG
  • 13.2.18 ATTENTIONKART
  • 13.2.19 VERN AI

14 ADJACENT/RELATED MARKETS

• 14.1 INTRODUCTION
• 14.2 LIMITATIONS
• 14.3 EMOTION DETECTION AND RECOGNITION MARKET - GLOBAL FORECAST 2027
  • 14.3.1 MARKET DEFINITION
  • 14.3.2 MARKET OVERVIEW
    • 14.3.2.1 Emotion detection and recognition market, by component
    • 14.3.2.2 Emotion detection and recognition market, by software
    • 14.3.2.3 Emotion detection and recognition market, by application area
    • 14.3.2.4 Emotion detection and recognition market, by end user
    • 14.3.2.5 Emotion detection and recognition market, by vertical
    • 14.3.2.6 Emotion detection and recognition market, by region
• 14.4 FACIAL RECOGNITION MARKET - GLOBAL FORECAST 2028
  • 14.4.1 MARKET DEFINITION
  • 14.4.2 MARKET OVERVIEW
    • 14.4.2.1 Facial recognition market, by offering
    • 14.4.2.2 Facial recognition market, by deployment mode
    • 14.4.2.3 Facial recognition market, by organization size
    • 14.4.2.4 Facial recognition market, by application
    • 14.4.2.5 Facial recognition market, by vertical
    • 14.4.2.6 Facial recognition market, by region

15 APPENDIX

• 15.1 DISCUSSION GUIDE
• 15.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 15.3 CUSTOMIZATION OPTIONS
• 15.4 RELATED REPORTS
• 15.5 AUTHOR DETAILS