Affective Computing Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, 2018-2028, Segmented By Component (Hardware, Software), By Deployment (Cloud, On-premise), By Organization Size (SMEs, Large Enterprises), By Technology (Touch, Touchless), By Application (Automotive, Healthcare, Retail, IT & Telecom, and Others), By Region and Competition

Global affective computing market is anticipated to thrive in the forecast period 2023-2028 due to the growing need for socially intelligent artificial agents as well as affective computing solutions connected to telemedicine. Additionally, it is expected that the market for affective computing will expand due to the growing use of wearable technology, increased internet penetration across industrial verticals, and global technical breakthroughs. Further predicted factors for the growth of the affective computing market are the rising desire for high operational excellence, increased resource utilisation, and better productivity. However, the rise in the cost of manufacturing affective computing systems and the disconnect between academic research and practical applications are further anticipated to restrain the development of the global affective computing market.

Artificial emotional intelligence is another name for affective computing. It represents a human-computer interaction where the computer recognizes the user's cues and responds appropriately. For Instance, a computer tool powered by emotional Artificial Intelligence can recognize when a student is having trouble understanding a concept by analyzing their facial expressions while exploring the concept and directing them to the right resources to help.The inputs in the form of various physical and facial movements are gathered with the assistance of a number of auxiliary devices, such as sensors and cameras, and supplied to various algorithms for analysis to determine the user's emotional state. To promote efficient interactions, relevant technologies and IT systems can also be used to meet users' subconscious or subliminal cues. In order to measure and analyse consumers' subconscious input, emotional computing is finding applications across several businesses and industrial verticals.

Depending on the user's mood, affective computing may also be utilised for customization, such as adjusting the music, lighting, and temperature. For instance, a Gestele prototype expands the gestures, emotions, or other types of communication that people with speech impairments or any other impairments can track. Affective computing is also becoming more popular as a result of the expanding use of robotics. Affective computing usage is anticipated to be significantly influenced throughout the forecast period by the expanding use of artificial intelligence (AI) in applications such as logistics, autonomous vehicles, parking assistance software, and surgical robots, among others.

Increased Automation in Contact Centers

Affective computing is an exceptional chance and has demonstrated its potential in the search for efficiency improvement in the retail industry and other industries, where consumer engagement is quite strong. They are already employed to determine from the voices of consumers how the client felt throughout their engagement with the customer care representative. Security personnel can utilise it to determine a caller's emotional state such as stress so they can respond more appropriately. The previous technologies used by legacy contact centres prevent them from supporting modern channels like social media, mobile app conversations, or videos. Increased automation is simple to implement and may assist businesses in meeting demand, particularly in cloud-based contact centres. Application programming interfaces (APIs) for communication can be used to incorporate modern channels. The use of analytics-led insights may then be made to provide individualised and context-rich consumer experiences. Additionally, because there is no centralised office, agents may work remotely to provide customer support services. For instance, Answer Connect, a US-based call centre provider, adopted a technology that permitted seasonal scalability without any negative financial effects. The organisation was able to scale up or down in response to call levels while keeping operations operating continuously because of Amazon's service, ‘Amazon Connect’. These facilities are equipped with the essential infrastructure to enable affective computing systems since they process enormous amounts of data and can further enhance the systems for accuracy and volume. The rise of contact centres is a result of the increased emphasis on providing the greatest customer service and experience, and the industry is predicted to expand as a result of the sectors' increased use of automation to increase production. In order to increase productivity, enhance the customer experience, and give customers self-service choices, automation is increasingly being employed in contact centres. For instance, a chatbot can converse with a customer through chat and respond to common inquiries. Automation is used in a broad variety of ways in contact centres. Customers' interactions with interactive voice response (IVR) systems, for instance, have transformed as a result of automated speech recognition (ASR), enabling them to self-serve more. Artificial intelligence (AI) technology assists customer service representatives in their phone or chat interactions with clients by providing solutions and suggested replies. Moreover, to facilitate automation in contact centres, businesses are also working to develop innovative affective computing technologies. Automation Anywhere, a pioneer in automated processes, released Automation Anywhere for contact centres in October 2021. This cloud-native, AI-driven automation solution aids businesses in providing better customer service more rapidly. These factors are driving the global affective computing market.

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Cloud-Based Solutions and Online Solutions are Growing Increasingly Common

Industry use of cloud-based solutions has been escalating. They increase operational agility so that companies may easily update their services without worrying about the infrastructure expenditure. Since dangers and worries about data security have grown over time, this has been used for backup services across many sectors. Additionally, online training and e-learning have gained popularity recently since they employ cutting-edge technology to create the best possible learning environment. Emotional contact in the context of education is still lacking in these learning methods. They are unable to replicate the conventional learning setting in which the teacher and students are seated face to face. Such commercial difficulties can be readily handled using affective computing. Moreover, cloud solutions have become the most sought-after alternative for businesses and organisations coping with numerous file formats and variable file quantities. The adoption of a systematic strategy that improves performance, multichannel support and engagement, and analytics reporting has become a prerequisite for businesses to successfully serve a client base where the consumer preferences are always changing. Affective computing solutions have gained popularity because they continually process raw data that is always growing and learning from enormous data sets. Most organisations currently use cloud-based services. For instance, due to disjointed systems and ineffective task distribution, Vodafone Shared Services had several customer service challenges in its on-premise contact centre. This negatively impacted the company's ability to provide excellent customer care. As a result of a cloud-based solution was used by the business to add new functions, such more channels for assistance, which led to a 15% boost in productivity gains. For instance, due to disjointed systems and ineffective task distribution, Vodafone Shared Services had several customer service challenges in its on-premise contact centre. This negatively impacted the company's ability to provide excellent customer care. As a result of a cloud-based solution was used by the business to add new functions, such more channels for assistance, which led to a 15% boost in productivity gains. In response to changing consumer habits in the digital and social spheres as well as the need for secure and readily available electronic health records (EHRs), hospitals, clinics, and other medical organisations are increasingly relying on the cloud for document storage, marketing, and human resources. Corporate environments necessitate the most significant IT investment. By enhancing productivity, removing the need for a big security and maintenance team, and cutting the cost of server space, enterprise cloud adoption leads to considerable bottom-line savings. This will boost the adoption of affective computing in a wide array of verticals.

Market Segmentation

The affective computing market is segmented into component, deployment, enterprise size, technology, application, and region. Based on component, the market is segmented into hardware and software. Based on deployment, the market is segmented into on-premise and cloud. Based on enterprise size, the market is segmented into large enterprises and SMEs. Based on technology, the market is segmented into touch and touchless. Based on application, the market is segmented into automotive, healthcare, retail, IT & telecom, and others. Based on region, the market is further bifurcated into North America, Asia-Pacific, Europe, South America, and Middle East & Africa.

Market Player

Major market players in the global affective computing market are Amazon Web Services Inc., Affectiva Inc., Nuance Communications Inc., Nemesysco Ltd., Eyesight Technologies Ltd., Element Human Ltd.,Emotibot Technologies Limited, Kairos AR, Inc., Realeyes Data Services Ltd., and audEERING GmbH.

Recent Development

Affectiva was credited by Smart Eye, a provider of Driver Monitoring Systems and high-fidelity eye tracking technology, to help the two companies work together to become a worldwide AI powerhouse in 2021. Affectiva's extensive experience in machine learning, data collecting, annotation, and AI ethics ensures the sharp eye to provide Human Insight AI that explains, helps, and predicts human behaviour in complex environments.

Report Scope:

In this report, the global affective computing market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

• Affective Computing Market, By Component

o   Hardware

o   Software

• Affective Computing Market, By Deployment:

o   On-Premise

o   Cloud

• Affective Computing Market, By Enterprise Size:

o   Large Enterprises

o   SMEs

• Affective Computing Market, By Technology:

o   Touch

o   Touchless

• Affective Computing Market, By Application:

o   Automotive

o   Healthcare

o   Retail

o   IT & Telecom

o   Others

• Affective Computing Market, By Region:

o   North America

§  United States

§  Canada

§  Mexico

o   Asia-Pacific

§  India

§  China

§  Japan

§  South Korea

§  Australia

§  Singapore

§  Malaysia

o   Europe

§  Germany

§  United Kingdom

§  France

§  Russia

§  Spain

§  Belgium

§  Italy

o   South America

§  Brazil

§  Argentina

§  Colombia

§