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AI in Emotion Recognition: Use Cases and Examples

As the demand for automation and predictive analytics continues to rise, businesses are increasingly looking for modern technologies that can help them comprehend their customers’ emotions toward a particular product or service. Accordingly, many enterprises these days leverage emotion AI to predict dissimilar users’ sentiments.

Emotion recognition has gained immense traction in recent years and is expected to grow exponentially in 2023 and beyond. According to Grand View Research, the global emotion detection market was valued at $32.95 billion in 2021 and is projected to expand at a CAGR of 16.7% from 2022 to 2030.

This tremendous growth of emotion AI comes as no surprise, considering its sheer volume and use cases across industries. The increasing adoption of biometrics, voice-driven technology, and gesture-driven navigation systems are the prominent factors driving the growth of this billion-dollar AI trend.

Let’s delve deeper to understand the various use cases and examples of emotion AI in different sectors:

How Does Emotion AI Work?

Emotion AI harnesses the capabilities of computer vision, machine learning, deep learning, and other AI trends to analyze users’ sentiments based on object and motion detection. In this tech trend, AI devices treat humans’ voices, text, and facial expressions as an object and generate predictions. The AI devices observe human features like smile lines, wrinkles, eyeballs, eyebrows, etc., and notice their movement over time. Then, it compares the collected data with the already-learned emotions.

For instance, you can observe eye movement to accurately track the users’ gaze points and check where the customers’ attention is going. If they start rolling their eyeballs, it’s not a good sign. Also, if the machine observes an ‘upside-down smile’ and a ‘wrinkled forehead,’ it concludes that the user is upset. By analyzing these basic classifications, emotion AI can identify more complex feelings, thus improving customers’ experience.

Now that we know how emotional AI devices help recognize and detect customers’ sentiments, let’s discover its varied use cases and examples across industries.

The Use Cases of Emotion AI in Different Industries

In the last few years, enterprises have discovered many use cases of Emotion AI to unlock real cost savings and create a better customer experience. These use cases include

Medical Diagnosis

An AI development company builds custom emotion AI solutions to help medical professionals accurately diagnose sentiments-based ailments like anxiety and dementia.

For example, Cognovi Labs, an emotion AI solution developer, built a Coronavirus Panic Index to analyze users’ sentiments and trends about the pandemic. Cognovi’s solution collects emotional data from social media, blogs, and forums to predict how the users in a particular area respond to certain events.

BP Detection

The American Heart Association used NuraLogix emotion AI to build an app that helps detect blood pressure levels based on 2-minute videos. The app collects blood pressure features from the video based on two considerable factors: first is physical characteristics such as weight, age, and skin tone, and the second is facial blood-flow signals such as light near the skin surface, which reflects hemoglobin concentration. The algorithm detects blood pressure with ~95% accuracy.


Emotion AI performs a powerful role in the education sector, helping understand children’s emotions and adapt their teaching style as per their emotions. For example, if a child gets frustrated due to the complexity of the project, AI in emotion recognition adapts the project to make it less challenging. Furthermore, emotion AI helps autistic children understand other people’s emotions.

For instance, Vedantu, a leading online tutoring platform, leverages Entropic Tech emotion AI to optimize its content and strategy. Entropic claims that this tech trend finds areas of improvement in content and presentation, which helps increase students’ attention span.

Employee Health

For many organizations, their staff’s physical and mental well-being is paramount, particularly for those who have very demanding jobs or work as first responders. Emotion AI helps analyze the anxiety levels of such employees and enables leaders to take proactive measures.

Automotive Safety

Emotion AI is of great use in the automotive industry. Since the world is progressively leading to realize the vision of autonomous cars, emotional AI can help improve road safety. By integrating various sensors like cameras and microphones, etc., into the car, the industry leaders can monitor what is happening and how passengers view the driving experience. Automotive vendors can use the diverse branches of emotion AI to observe the driver’s emotional state or drowsiness and trigger an alert to prevent any possible road accidents.

For instance, automotive giant, Ford, and Affectiva’s Automotive AI have partnered with an AI development company to develop an AI emotion recognition vehicle solution to identify human emotions such as frustration, anger, or drowsiness. If the AI solution detects any of these emotions, it stops the vehicle, thus, preventing potential road incidents.

Retail Industry

Retailers now consider installing computer vision in their stores to capture visitors’ moods, reactions, and demographic information and enhance their experience.

For instance, emotion AI in the retail industry can help marketing managers not to ask customers repetitive questions like, “Which card would you like to pay with?” and so on. Customers might get frustrated by answering the same questions over and over again.

Fraud Detection

In the insurance sector, fraud detection is an intimidating task, but emotion AI can make it possible by unveiling the extra hidden information that the customers unwillingly execute when they make a claim.

For example, if a customer uses a phone to make a claim, you can use the accelerometer and the gyroscope to check for fidgeting. It will give a good indication if the customers feel uneasy. Also, wearable devices such as smartwatches provide information, such as skin conductance and heart rate, to detect fraud incidents. According to a survey, around 30% of users have confessed that they are to their car insurance company to gain coverage.

Final Thoughts

AI in emotion recognition has various use cases, benefiting businesses across industries to improve their customer experience and enhance productivity. So, if you want to harness the full potential of this emerging tech trend, partner with a reputed AI development company now and take your business to greater heights.