Artificial Intelligence (AI) - Emotion Recognition Market 2030 By Offering (Software, Services), Tools (Facial Expression Recognition, Speech and Voice Recognition, Gesture and Posture Recognition), Technology (Machine Learning, Bio sensors technology, Natural Language Processing, Feature Extraction), Application, End-use Verticals, and Region - Partner & Customer Ecosystem (Product Services, Proposition & Key Features) Competitive Index & Regional Footprints by MarketDigits

Industry : Information Technology | Pages : 180 Pages | Published On : Dec 2023

The Artificial Intelligence (AI)-Emotion Recognition Market size is estimated to grow from USD 24.4 Billion in 2022 to reach USD 73.51 Billion by 2030, growing at a CAGR of 14.78% during the forecast period from 2023 to 2030.

Major players in Artificial Intelligence (AI)-Emotion Recognition Market include IBM (US), Microsoft (US), Google (US), Apple (US), NEC (Japan), Elliptic Labs (Norway), Intel (US), Affectiva (US), Cognitec (Germany), Tobii (Sweden), NVISO (Switzerland), Pyreos (UK), Numenta (US), iMotions (Denmark), GestureTek (Canada), PointGrab (Israel), Ayonix (Japan), Noldus (Netherlands), Eyeris (US), Beyond Verbal (Israel), Kairos (US), Raydiant (US), Sentiance (Belgium), and Sony Depthsense Solutions (Belgium).

Advancements in AI and Deep Learning Technologies

AI and deep learning advancements have considerably accelerated the field of AI emotion recognition, enabling new possibilities and capacities in understanding and interpreting human emotions. These breakthroughs have transformed how robots perceive and respond to human emotions, resulting in more empathic, personalized, and context-aware interactions between humans and AI systems. The use of deep learning algorithms is one of the significant accomplishments in AI emotion recognition. Deep learning is a branch of machine learning that use multiple-layer neural networks to handle complex data and extract significant patterns. In emotion recognition tasks, two notable designs are Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).

The introduction of multimodal techniques is another key milestone in AI emotion recognition. Multimodal models include information from numerous sources, such as facial expressions, speech, body language, and physiological signs, rather than depending exclusively on facial expressions or voice data. These models take advantage of the complimentary nature of many modalities in order to increase emotion recognition accuracy and robustness. Furthermore, another area of improvement in AI emotion recognition is contextual awareness. Understanding the context in which emotions arise is critical for proper detection since emotions are context-dependent. Advanced AI models can now predict emotional states more accurately by taking into consideration the surrounding environment, conversation history, and situational information.

Real-time emotion recognition is a remarkable accomplishment made possible by advances in artificial intelligence and deep learning. Emotions must be processed in real-time for applications such as human-robot interaction, virtual assistants, and customer service. AI systems can now perceive and respond to human emotions in real-time thanks to streamlined architectures, hardware accelerations, and parallel processing, enabling more natural and intuitive interactions. 

Additionally, the combination of AI emotion recognition with other AI technologies such as natural language processing (NLP) and sentiment analysis has created new prospects for sentiment-aware applications. Chatbots and virtual assistants, for example, can now recognize users' emotional states and adjust responses appropriately, resulting in more empathic and engaging user experiences.

In conclusion, the enhancements have made it easier to incorporate emotion recognition AI into a variety of applications, including virtual assistants, customer service, healthcare, education, and entertainment, hence improving human-computer interactions and user experiences. As technology advances, we can anticipate even more advancements in the AI emotion recognition sector, leading to increasingly more advanced and emotionally intelligent AI systems.

Growing Adoption of AI in Healthcare

The implementation of Artificial Intelligence (AI) in healthcare is increasing, and AI emotion recognition is emerging as a viable application within the healthcare business. The incorporation of AI-emotion detection technology in healthcare settings is altering patient treatment, mental health diagnosis, and overall well-being by enabling a deeper knowledge of human emotions and their impact on health outcomes.

The demand for more precise and individualized medical treatments is one of the key reasons behind the increased usage of AI in healthcare. AI-emotion recognition is a vital tool for healthcare providers to comprehend their patients' emotional states, which is crucial in diagnosis and therapy planning. AI systems can detect tiny emotional clues that may reveal underlying mental health issues or stress levels by studying facial expressions, speech tones, and physiological signs. The level of emotional knowledge improves medical providers' capacity to provide individualized treatment programs that address both physical and mental health issues.

Additionally, The increasing relevance of patient participation and adherence to treatment plans is another reason driving the implementation of AI-emotion recognition in healthcare. Motivational messages, reminders, and educational content that resonate with patients' emotional needs can be delivered using emotion-aware programs. This method encourages patient engagement and adherence to therapy, which leads to improved health outcomes and patient satisfaction.

In conclusion, AI-emotion recognition is transforming patient care by allowing for a better understanding of human emotions and their impact on health outcomes. It has the most potential for use in mental health diagnostics, telemedicine, patient participation, and doctor-patient communication. AI-emotion recognition's ability to recognize tiny emotional cues and evaluate massive volumes of emotional data is proving transformational in terms of patient treatment and well-being. As AI technologies progress and regulatory support for AI in healthcare grows, it is projected that the use of AI-emotion recognition in healthcare will expand, resulting in more emotionally intelligent and patient-centric healthcare services.

Regional Insight

Artificial Intelligence (AI)-emotion recognition has grown dramatically in North America, propelled by technology advances, increased demand for AI applications, and a user-centric strategy across industries. The region has emerged as a key center for AI development, with the United States dominating the market for AI emotion recognition. The region is home to a number of famous AI research institutions and tech startups that are pushing advances in emotion identification algorithms. These developments have significantly increased the accuracy and performance of AI emotion recognition models, making them more relevant across a wide range of industries. In addition, AI-based emotion identification has applications in a variety of areas, including healthcare, customer service, education, virtual assistants, and entertainment. The capacity to recognize and respond to user emotions has resulted in improved user experiences and higher consumer satisfaction.

The healthcare industry in North America has been an early adopter of AI emotion recognition. The technology is used in mental health diagnosis, patient monitoring, and telemedicine, supporting healthcare workers in spotting emotional patterns and offering better care. The healthcare industry in North America has been an early adopter of AI emotion recognition. The technology is used in mental health diagnosis, patient monitoring, and telemedicine, supporting healthcare workers in spotting emotional patterns and offering better care.

Furthermore, the US government's support for AI programs, as well as the country's advantageous regulatory framework, has boosted AI development. Leading AI conferences and events in the United States offer knowledge-sharing and networking opportunities for researchers and practitioners, furthering the field's advancement.  Canada has a thriving AI research community, government backing for AI programs, and AI-powered applications in a variety of industries.

Artificial Intelligence (AI)-Emotion Recognition Market Scope and Market Size

Analysis

Details

Report Forecast Period

2023-2030

Base Year

2022

CAGR Values

14.78%

Projection Values in 2022

USD 24.4 Billion

Projection Values in 2030

USD 73.51 Billion

Segment covered

Offerings, Tools, Technology, Application, End-use Verticals, and Region

Region

North America, Latin America, Europe, Asia-Pacific, Middle East & Africa

The Artificial Intelligence (AI)-Emotion Recognition Market research report provides an in-depth overview of the industry including market segmentation by Offerings, Tools, Technology, Applications, End-use Verticals, and Region. Analysis of the global market with a special focus on high-growth applications in each vertical and fast-growing market segment. It includes a detailed competitive landscape with identification of the key players concerning each type of market, in-depth market share analysis with individual revenue, market shares, and top players’ rankings. Impact analysis of the market dynamics with factors currently driving and restraining the growth of the market, along with their impact in the short, medium, and long-term landscapes. Competitive intelligence from the company profiles, key player strategies, and game-changing developments such as new product launches, collaborations, expansions, investment analysis, mergers, and acquisitions. The market analysis focuses on revenue and forecast by region/countries and by application in terms of revenue forecast for the period 2023-2030.

The report further studies the market strategies of key players, recent development status, plans, and Artificial Intelligence (AI)-Emotion Recognition Market trends across the world. Also, it splits the market segmentation further to deep dive into research and reveals company profile and prospects.

Major Classifications are as follows:

  • By Offerings
    • Software
    • Services
  • By Tools
    • Facial Expression Recognition
    • Speech and Voice Recognition
    • Gesture and Posture Recognition
  • By Technology
    • Machine Learning
    • Bio sensors technology
    • Natural Language Processing
    • Feature Extraction
    • Pattern Recognition
  • By Application
    • Marketing and Advertising
    • Surveillance and Monitoring
    • Medical Emergency
    • Robotics and eLearning
    • Others
  • By End-use Verticals
    • BFSI
    • Healthcare & Life Sciences
    • IT & Telecommunication
    • Retail and eCommerce
    • Education
    • Media and Entertainment
    • Automotive
    • Others
  • By Region
    • North America
      • US
      • Canada
    • Latin America
      • Brazil
      • Mexico
      • Argentina
      • Rest of Latin America
    • Europe
      • UK
      • Germany
      • France
      • Italy
      • Spain
      • Russia
      • Rest of Europe
    • Asia Pacific
      • China
      • Japan
      • India
      • South Korea
      • Rest of Asia Pacific
    • Rest of the World
      • Middle East
        • UAE
        • Saudi Arabia
        • Israel
        • Rest of the Middle East
      • Africa
        • South Africa
        • Rest of the Middle East & Africa

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  • Strengthen your understanding of the market in terms of demand drivers, industry trends, and the latest technological developments, among others.
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  • Make correct business decisions based on a thorough analysis of the total competitive landscape of the sector with detailed profiles of the top Artificial Intelligence (AI)-Emotion Recognition Market providers worldwide, including information about their products, alliances, recent contract wins, and financial analysis wherever available.

TOC

  1. Executive Summary
  2. Introduction
    1. Key Takeaways
    2. Report Description
    3. Market Scope & Definition
    4. Stakeholders
    5. Research Methodology
      1. Market size
      2. Key data points from primary sources
      3. Key data points from secondary sources
      4. List of primary sources
      5. List of secondary sources
  3. Market Overview
    1. Introduction
    2. Industry Segmentation
    3. Market Trends Analysis
    4. Major Funding & Investments
    5. Market Dynamics
      1. Drivers
      2. Restraints
      3. Opportunities
    6. Value Chain Analysis
    7. Pricing Analysis
      1. Pricing Analysis, By Products
      2. Average Pricing Benchmark Analysis
  4. Artificial Intelligence (AI)-Emotion Recognition Market, By Offerings
    1. Software
    2. Services
  5. Artificial Intelligence (AI)-Emotion Recognition Market, By Tools
    1. Facial Expression Recognition
    2. Speech and Voice Recognition
    3. Gesture and Posture Recognition
  6. Artificial Intelligence (AI)-Emotion Recognition Market, By Technology
    1. Machine Learning
    2. Bio sensors technology
    3. Natural Language Processing
    4. Feature Extraction
    5. Pattern Recognition
  7. Artificial Intelligence (AI)-Emotion Recognition Market, By Application
    1. Marketing and Advertising
    2. Surveillance and Monitoring
    3. Medical Emergency
    4. Robotics and eLearning
    5. Others
  8. Artificial Intelligence (AI)-Emotion Recognition Market, By End-use Verticals
    1. BFSI
    2. Healthcare & Life Sciences
    3. IT & Telecommunication
    4. Retail and eCommerce
    5. Education
    6. Media and Entertainment
    7. Automotive
    8. Others
  9. Artificial Intelligence (AI)-Emotion Recognition Market, By Geography
    1. Artificial Intelligence (AI)-Emotion Recognition Market, North America
      1. U.S.
      2. Canada
    2. Artificial Intelligence (AI)-Emotion Recognition Market, Latin America
      1. Brazil
      2. Mexico
      3. Argentina
      4. Rest of Latin America
    3. Artificial Intelligence (AI)-Emotion Recognition Market, Europe
      1. UK
      2. Germany
      3. France
      4. Italy
      5. Spain
      6. Russia
      7. Rest of Europe
    4. Artificial Intelligence (AI)-Emotion Recognition Market, Asia Pacific
      1. China
      2. Japan
      3. India
      4. South Korea
      5. Rest of Asia Pacific
    5. Artificial Intelligence (AI)-Emotion Recognition Market, Rest of the world
      1. Middle East
        1. UAE
        2. Saudi Arabia
        3. Israel
      2. Africa
        1. South Africa
        2. Rest of Africa
  10. Competitive Analysis
    1. Introduction
    2. Top Companies Ranking
    3. Competitive Landscape
      1. Competition Dashboard
      2. Market Analysis (2022)
      3. Emerging company case studies
    4. Company Profiles
      1. IBM (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      2. Microsoft (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      3. Google (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      4. Apple (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      5. NEC (Japan)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      6. Elliptic Labs (Norway)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      7. Intel (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      8. Affectiva (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      9. Cognitec (Germany)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      10. Tobii (Sweden)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      11. NVISO (Switzerland)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      12. Pyreos (UK)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      13. Numenta (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      14. iMotions (Denmark)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      15. GestureTek (Canada)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      16. PointGrab (Israel)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      17. Ayonix (Japan)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      18. Noldus (Netherlands)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      19. Eyeris (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      20. Beyond Verbal (Israel)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      21. Kairos (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      22. Raydiant (US)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      23. Sentiance (Belgium)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition
      24. Sony Depthsense Solutions (Belgium)
        1. Business Overview
        2. Product Portfolio
        3. Market Segments (Business Segment/Region)
        4. Sales Footprint
        5. Recent Developments
          1. New Product Launch
          2. Mergers & Acquisitions
          3. Collaborations, Partnerships & Agreements
          4. Rewards & Recognition

Table and Figures

Methodology:

At MarketDigits, we take immense pride in our 360° Research Methodology, which serves as the cornerstone of our research process. It represents a rigorous and comprehensive approach that goes beyond traditional methods to provide a holistic understanding of industry dynamics.

This methodology is built upon the integration of all seven research methodologies developed by MarketDigits, a renowned global research and consulting firm. By leveraging the collective strength of these methodologies, we are able to deliver a 360° view of the challenges, trends, and issues impacting your industry.

The first step of our 360° Research Methodology™ involves conducting extensive primary research, which involves gathering first-hand information through interviews, surveys, and interactions with industry experts, key stakeholders, and market participants. This approach enables us to gather valuable insights and perspectives directly from the source.

Secondary research is another crucial component of our methodology. It involves a deep dive into various data sources, including industry reports, market databases, scholarly articles, and regulatory documents. This helps us gather a wide range of information, validate findings, and provide a comprehensive understanding of the industry landscape.

Furthermore, our methodology incorporates technology-based research techniques, such as data mining, text analytics, and predictive modelling, to uncover hidden patterns, correlations, and trends within the data. This data-driven approach enhances the accuracy and reliability of our analysis, enabling us to make informed and actionable recommendations.

In addition, our analysts bring their industry expertise and domain knowledge to bear on the research process. Their deep understanding of market dynamics, emerging trends, and future prospects allows for insightful interpretation of the data and identification of strategic opportunities.

To ensure the highest level of quality and reliability, our research process undergoes rigorous validation and verification. This includes cross-referencing and triangulation of data from multiple sources, as well as peer reviews and expert consultations.

The result of our 360° Research Methodology is a comprehensive and robust research report that empowers you to make well-informed business decisions. It provides a panoramic view of the industry landscape, helping you navigate challenges, seize opportunities, and stay ahead of the competition.

In summary, our 360° Research Methodology is designed to provide you with a deep understanding of your industry by integrating various research techniques, industry expertise, and data-driven analysis. It ensures that every business decision you make is based on a well-triangulated and comprehensive research experience.

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