Emerging Mobile App Trends in AI

As we look into the future, we see an AI all set to take on the world, and even make decisions for people. Very soon, AI will be making the purchase decisions for people by overloading them with information, and even changing the way they think. AI is going to have too much power into what people buy.

Earlier, just integrating the personal assistants  like SIRI and having Google Assistant was enough to stay competitive in the market, but now that’s not enough anymore. There are some exciting breakthroughs that you must integrate to stay updated with user interests. 

1. Predictive Analytics  

AI is making a significant impact in the field of predictive analysis. This is where AI anticipates and predicts the needs of the customers even before they know what they want. For example, your user might be shopping online for one of your products, and as they browse through it, the AI realizes the color preferences and taste of the users and suggests more products that align with that particular product. 

Suppose you sell swimming costumes, with the help of AI, you can sell other products that complement their swimming costume (earplugs, swim cap, goggles, etc). This is how the intuitiveness of AI takes over, and makes the buyer buy more than what he intended. The predictive analysis progresses, it will improve according to the preferences of the users. They no longer have to type and search what they want – it will be presented right in front of them, and they just have to click on them. Makes one wonder, is it making the users lazy? Or is AI directly responsible for making the users buy more than what they intended? Either way, it would help you get ahead of the trend. 

2. The Wonder of Image recognition

This feature has been around for sometime, but this has been progressing and becoming intuitive at a rapid pace. Image recognition is a feature that you must have observed in software’s like Google Photos. Google Photos uses image recognition features to organize your photos according to faces, people and places. This means AI is used to understand facial recognition, object detection and scene understanding.  

Another thing is the Google Lens App, which is more powerful with each version, and it allows users to search for information based on the objects captured in photos. The app can identify animals, people, plants, actions and landmarks on images and provide information based on what the user needs. 

3. The Rise of Facial Recognition

Along with predictive analysis, you have the facial recognition feature asserting its dominance in the mobile applications. It saw a remarkable surge in 2020, and has been prominent in mobile applications. The feature of facial recognition does have its positive and negative features, but many experts claim that the positives outweigh the negatives. Try integrating this feature on your mobile applications, and see the difference it makes in their functioning and popularity. 

Even most of the mobile phones have in-built facial recognition features integrated into them. This feature would definitely prevent fraud, and most of the financial services companies now rely on this technology to serve their customers better. Other industries have also started experimenting with facial recognition to enhance the functionalities of their apps. You will soon be seeing them going mainstream in almost every app that sees security as one of their primary requisites for app development. 

4. Voice Assistants (VA) Have a Resounding Presence

Along with facial recognition, voice assistants are perhaps the most loved consumer technology. There aren’t many people who have experimented with Siri, Alexa or Google Assistant. These voice assistants are all AI based and have been used in apps on a consistent basis. The apps also allow you to customize the voice based on country and gender. So if you are based in India, you can have the app assistant speaking in an Indian English style. The conversion to AI based voice assistants has been dominant during the lockdown period since the call center’s had to be shut down. Many industries, especially the banking sector, even the e-commerce sector relied on voice assistants for providing customer service. 

5. Emotion Recognition and Sentiment Analysis on Mobile Applications

If Facial recognition and VA were ruling the world of mobile applications, imaging what Emotion Recognition AI and Sentiment Analysis can do. Emotion AI is also known as the Affective Computing system where Artificial Intelligence goes even further and analyses the expressions, voice tones, body language and facial expressions of people. The machines will analyze the emotions and sentiments of the people and then interpret and classify them. This is done in an interesting manner by: 

• Acquiring the image through a camera feed
• Preprocessing the image
• Extracting the features of the image
• Analysis of the image
• Classifying the emotion

Though the steps seem simple and easy, it entails the usage of very intricate technology because the AI will have to distinguish all the facial features of a person, including neutral expression. Emotion detection is a very big challenge to master, but with state of the art technology and a competent software development team, it will only be a matter of time before your mobile applications get completely driven by them.  

6. The Sophistication of Natural Language Processing (NLP)

NLP or Natural Language Processing is a significant feature that enables the apps to understand and interpret human language. NLP when integrated with chatbots and voice assistants makes it more accurate, sophisticated and user-friendly. With this feature, humans and machines can have real-time conversations. Breakthroughs in AI have made it possible for apps to understand what the users need on a deeper level, distinguish between different user behavior’s and preferences and match them with the exact user. 

NLP is constantly evolving and very soon they will become so advanced that they will be able to carry out complex tasks with just basic commands from the user. This would be of great help to people with different kinds of disabilities. Examples of this could be blind navigation or speech to text transcription capabilities with extreme accuracy. 

7. Unbelievable Accuracy in Personalization and Recommendation

The personalization and recommendation engines are going to be powered by Machine Learning and AI. The engines leverage these two powerful technologies to analyze user behavior’s, follow their preferences and learn more about them by collecting data. This enables the app to deliver better user engagement and customer satisfaction. The apps can even offer customized suggestions based on these algorithms with unbelievable accuracy. A software development agency that has teams of highly talented developers wilsy: IndiaNICl be able to come up with excellent solutions that can transform your mobile apps, and above competition. 

8. Enhanced Security and Authentication

With AI, mobile app security and authentication has become more robust and adaptive. The algorithms have become so advanced that they can identify potential security threats, detect suspicious user behavior and prevent unauthorized access to your apps. It provides your users with safe, secure and seamless login experience.