A few years back, it seemed like science fiction to imagine machines understanding human emotions. However, due to technological advancements and the emergence of artificial intelligence (AI), it has been observed that AI systems become capable of recognising, processing and responding to human emotions in the most effective ways. Now, organisations from various sectors are using AI technologies for the understanding and recognition of emotions and implementing that knowledge for the improvement of various activities, starting from marketing campaigns and customer support to health care.
These technologies are better known as “emotion AI” which have multifaceted implications in different sectors. However, due to the consideration of the complex nature of human emotion, it becomes the topic of debate whether machines can truly understand the feelings and experiences of human beings.
Evolution of AI from logical interpretation to human emotion
In the early development stages of AI, the fundamental principle of AI was based on logical processing and data analysis. Previously, AI systems have been designed as effective tools that can perform tasks requiring significant computational power in the most efficient manner, like human beings or even better. Though these tasks are often found to be complex and rigid, emotional context is not required for these tasks to be solved. The concept of AI was once predominantly related to the vast databases, server rooms, and command lines.
However, with the recognition of the increasing importance of emotional intelligence in the interpretation, communication and decision-making process, the landscape of AI development has started to change. There is a greater influence of human emotion on the preferences, requirements, relationships and activities of human beings. Human actions are based on both sentiment and cognition rather than based on only logical reasoning.
The recognition of the significant influence of emotions on human actions and behaviours empowers researchers and innovators to consider the integration of emotional intelligence capabilities in the frameworks of AI. As a result, a new era of AI has come, which not only emphasises logical reasoning, data analytics and computational tasks but also focuses on sentiment analysis and emotional understanding to bridge the gap in effective communication between machines and humans.
Current capabilities of AI in emotion recognition
The capability of AI in the recognition of emotions is mainly focused on two major technologies which are facial recognition and NLP (Natural Language Processing). Through the analysis of facial expressions, text-based communications, and voice tone, AI-powered machines nowadays have the ability to identify the emotional states of human beings, including sadness, anger, happiness and fear.
AI-enabled emotion recognition systems utilise various cutting-edge technologies such as deep learning, machine learning and computer vision. These technologies are capable of observing the facial features and expressions of human beings through the movement of their eyes, eyebrows and mouth. In order to analyse these expressions accurately, the AI programs are previously trained with a vast amount of high-quality and unbiased data. For instance, based on the dataset previously implemented, an AI program can analyse the various types of emotions, considering the face of an individual as an object.
These systems are incorporated in multifaceted areas, from marketing campaigns to the fashion and automotive sectors, to capture the emotional state of the target group and respond effectively. As of 2025, the emotion detection and recognition technologies are around 68.41 billion US dollars and are forecasted to increase to 166.63 billion US dollars by 2030, reporting a CAGR of 19.41 per cent between 2025 and 2030.
AI and human emotion in practice
Emotion AI in the automotive sector
Affectiva, which is an AI development company, has developed an Emotion AI focused on the application in the automotive sector. The Emotion AI system of Affectiva uses in-cabin cameras and machine learning algorithms for the analysis of facial expressions and voice patterns. This system has been used for automotive safety. This AI system can capture the emotional state of drivers inside a vehicle environment and has the ability to potentially prevent accidents in terms of detecting whether the driver is drowsy or distracted.
Emotion AI in the fashion sector
With the support of the Ministry of Textile under the Indian government, the National Institute of Fashion Technology established the fashion forecasting initiative called “VisioNxt” in 2018. This initiative aims to identify the vast cultural diversity of India, which involves 121 languages, 22 official languages, 270 mother tongues and multiple religions and tribes. The identification of this cultural diversity with the help of this AI-powered initiative set the foundation to understand human expression and fashion consumption, which leads to the obtaining of valuable insights to shape the Indian fashion, textile and retail industries.
Emotion AI in the healthcare sector
Woebot is an AI chatbot which has been recognised as “the future of mental health”. Cognitive Behavioural Therapy (CBT) approaches are used by this chatbot for listening to problems and advising the solutions to anyone who seeks help from the bot. Woebot provides techniques and support for the navigation of mental health issues.
Can AI-powered machines truly feel and experience human emotion?
Human emotional responses are more complicated and relevant in comparison to AI generated responses. It is because of the inherent nature of human emotions and the influence of several factors, such as social, psychological and biological factors, in shaping human emotions. Biology is an integral part of human emotions. There is a significant role of hormones and neurotransmitters in influencing how human beings feel and respond to stimuli. For example, the release of cortisol hormone is related to stress, while serotonin or dopamine hormone can lead to a feel-good moment. The AI systems which operate without these biological frameworks are unable to exactly replicate the complexity of human emotional intelligence.
A wide range of emotions are experienced and expressed by human beings, which can be mixed in nature and can be rapidly evolving on the basis of memories, thoughts and reflections. For instance, both happiness and sadness feelings can be experienced by an individual at a farewell party, as collaboration can lead to happiness, while saying goodbye can lead to sad emotions. Therefore, it is quite difficult for AI to fully replicate complex and layered emotional expressions. While some of the parts of emotional intelligence can be recognised by AI through trained algorithms, the feelings as humans experience them are still beyond the current capabilities of AI.
FAQ
1. Can AI-powered machines truly understand human emotions?
Human emotional responses are more complicated and relevant in comparison to AI-generated responses. It is because of the inherent nature of human emotions and the influence of several factors, such as social, psychological, and biological factors, in shaping emotions. The AI systems which operate without these biological frameworks are unable to exactly replicate the complexity of human emotions.
2. What is the future of emotion recognition in AI?
As of 2025, the emotion detection and recognition technologies are around 68.41 billion US dollars and are forecasted to increase to 166.63 billion US dollars by 2030, reporting a CAGR of 19.41 per cent between 2025 and 2030.
3. Can AI help with mental health?
Woebot is an AI chatbot which has been recognised as “the future of mental health”. Cognitive Behavioural Therapy (CBT) approaches are used by this chatbot for listening to problems and advising the solutions to anyone who seeks help from the bot. Woebot provides techniques and support for the navigation of mental health issues.
4. How is Emotion AI used in the automotive industry?
The Emotion AI system of Affectiva uses in-cabin cameras and machine learning algorithms for the analysis of facial expressions and voice patterns to detect whether the driver is drowsy or distracted.
5. What are the limitations of AI in understanding emotions?
It is quite difficult for AI to fully replicate complex and layered emotional expressions. While some of the parts of emotional intelligence can be recognised by AI through trained algorithms, the feelings as humans experience them are still beyond the current capabilities of AI.
