Global Affective Computing Market is Estimated to Witness High Growth Owing to Rising Demand for AI-based Customer Service Solutions and Growing Need for Enhancing User Experience
The Global Affective Computing Market is estimated to be valued at US$ 65.02 Bn in 2024 and is expected to exhibit a CAGR of 24.3% over the forecast period 2024-2031. Furthermore, the rapidly growing artificial intelligence and cloud computing technologies are expected to propel the global affective computing market.
Market Dynamics:
Rising demand for AI-based customer service solutions: Affective computing helps enterprises to understand customer sentiments and emotions in real-time through various digital channels like websites, mobile apps, and virtual assistants etc. This helps companies to provide personalized customer support and enhance customer experience. The growing need to improve customer satisfaction is driving the adoption of affective computing solutions globally.
Growing need for enhancing user experience: With advancements in technologies like face and speech recognition, affective computing allows devices and software to detect human emotions. This capability is being leveraged by application developers to offer emotionally intelligent and contextual experiences to users. Many consumer electronics and IoT companies are integrating affective computing to understand user behavior and feedback to continuously enhance digital experiences. The focus on delivering superior UX is propelling the demand for affective computing.
Increasing Demand for Frictionless Customer Engagement
One of the major drivers for the growth of the global affective computing market is the increasing demand from organizations to offer frictionless and personalized customer engagement experiences. With technologies like facial recognition and emotion AI, companies can gain deeper insights into customer sentiments, pain points, and preferences. This allows them to customize their products, services, marketing strategies according to each customer's unique needs and enhance customer satisfaction levels. Many industries like automotive, healthcare, retail, and banking are actively adopting affective computing solutions to improve customer service and build stronger customer loyalty.
Growing Applications in Entertainment, Gaming and Media
Another key growth driver is the rising demand for affective computing in entertainment, gaming, and media industries. Developments in virtual reality, augmented reality and human-computer interaction have led to an increased focus on creating more immersive and engaging experiences for users. Technologies like facial expression recognition, bio-signal monitoring, and emotion AI are being leveraged to develop games and interactive media that can detect and respond to human emotions and behavior in real-time. This is expected to make experiences more personalized and help improve user engagement. The growing AR/VR industry and demand for interactive content are fueling investments in affective computing research and development.
Limitations in Accuracy and Reliability of Emotion Detection
One of the major challenges currently restricting faster adoption of affective computing is the limitations in accuracy and reliability of current emotion detection technologies. Factors like subtle variations in facial expressions, inability to detect certain micro-expressions, influence of external variables can reduce detection accuracy. Moreover, emotions are complex and subjective phenomena influenced by numerous internal and external factors which are difficult to measure precisely. This uncertainty over correctness of emotion inferences hampers user trust and acceptance of affective computing systems, especially in critical applications. Extensive research is still needed to enhance reliability.
High Development Costs and Infrastructure Requirements
Developing advanced affective computing solutions require substantial investments in multidisciplinary R&D involving areas like computer vision, machine learning, neuroscience and cognitive psychology. Extensive training datasets are also required to develop robust emotion recognition models. Additionally, deploying affective systems at scale necessitates high performance computing infrastructures, edge devices and cloud integration - making the overall development costs quite high. These high costs negatively impact adoption rates, especially among smaller companies and in emerging markets. Affordability issues remain a key limiting factor currently constraining faster market growth.
Application in Healthcare Sector
A major opportunity area is increasing application of affective computing in the healthcare industry. Technologies like virtual therapies, eldercare assistance, and emotion-aware clinical decision support systems have potential to revolutionize patient care and treatment outcomes. For example, tracking patient vital signs, emotions during rehabilitation or therapy sessions through wearable devices can help monitor treatment effectiveness in real-time. Similarly, emotion AI-enabled chatbots/virtual doctors that understand patient sentiments can enhance diagnosis and delivery of care. Growing focus on patient-centric healthcare models is expected to boost investments and adoption in the coming years.
Integration with Augmented and Virtual Reality
Another promising market expansion avenue lies in deeper integration of affective computing into augmented reality and virtual reality domains. As AR/VR experiences become more life-like and human-centered, technologies that enable seamless emotion detection will play a critical role in creating completely immersive experiences. Affective computing features like real-time facial expression analysis, biometrics monitoring can help develop emotionally intelligent AR characters, virtual therapies and training simulations. The anticipated widespread adoption of AR/VR technologies across sectors offers significant opportunities for affective computing vendors to growth their presence and revenues.
Link - https://www.coherentmarketinsights.com/market-insight/affective-computing-market-5069
Key Developments:
- In August 2022, CallMiner, a top provider of conversation intelligence focused on business enhancement, revealed new integrations with Genesys Cloud CX and Amazon Connect. These integrations allow organizations to easily access advanced real-time analytics within their current or upcoming Contact Center as a Service (CCaaS) setups. By utilizing CallMiner's platform, which processes live voice audio, organizations can improve agent support, onboarding, training, and other performance metrics.
- In June 2022, Nuance Communications, a leading provider of conversational AI and ambient intelligence, teamed up with SCIENTIA Puerto Rico, Inc. to expand access to its Dragon Medical One speech recognition solution for healthcare professionals in Puerto Rico. This partnership is designed to enhance the quality of clinical documentation and patient outcomes while reducing the administrative workload that can lead to clinician burnout. By utilizing Dragon Medical One, which is employed by over 550,000 physicians worldwide, the collaboration aims to optimize workflows for both English- and Spanish-speaking clinicians using the MEDITECH electronic health record system.
- In June 2022, Aural Analytics, Inc., a leader in clinical-grade speech analytics, formed a partnership with Koneksa, a key figure in digital biomarker development. The goal of this collaboration is to enhance Koneksa's platform and research capabilities by integrating Aural Analytics' Speech Vitals technology, thereby improving the processes and results of clinical trials.
- In May 2020, Microsoft Corp., a prominent player in cloud computing and AI, joined forces with Sony Semiconductor Solutions Corporation, known for its expertise in image sensors, to create advanced smart camera solutions. This collaboration is focused on incorporating Microsoft Azure AI technologies into Sony's intelligent vision sensor IMX500, allowing for the extraction of valuable data from images taken by smart cameras and other devices. Additionally, Sony intends to develop a smart camera management app utilizing Azure IoT and Cognitive Services to further enhance video analytics capabilities for enterprise clients.
Key Players:
Affectiva Inc., Amazon Web Services Inc., Apple Inc., Cognitec Systems, Elliptic Labs, Google Inc., IBM Corporation, Intel Corporation, Kairos, Microsoft Corporation, nViso, PointGrab, Pyreos, Qualcomm Inc., and Sony Depthsensing Solutions
