How AI and Machine Learning Reshape Mobile App Development?

How AI and Machine Learning Reshape Mobile App Development?

20 April 2022

How AI and Machine Learning Reshape Mobile App Development?

How AI and Machine Learning Reshape Mobile App Development?

As the web has largely been substituted by the mobile apps as the most popular digital frontier, apps now accommodate the latest technologies, tools and experiments than other digital platforms. The Artificial Intelligence (AI) and Machine Learning (ML) technologies have already made their inroads into app development in a big way.

Thanks to AI and ML technologies, mobile apps are now at the forefront of business process automation, delivering personalised user experience, ensuring smooth business conversion and streamlining security measures. Any leading mobile app development company will agree that in more than one way, apps have reshaped the way apps are built and conceptualised. Here we are going to explain some of these ways.

Biometric & Facial Recognition

Mobile apps increasingly use biometric technologies such as facial recognition for secure authentication and providing users a smooth experience in regard to safeguarding their mobile data and interactions. Facial recognition is a technology that relies on Machine Learning. The mobile device learns from the facial expressions of the user and accordingly can detect other unauthorised attempts to force login or get access to device data.

Facial recognition powered by AI and ML technologies has particularly played a major role in preventing fraudulent activities in apps relying on financial transactions and data transfer. Thanks to facial recognition, attempts of data theft and security breaches could be reduced to a minimum. No wonder, most of flagship devices across platforms now use facial recognition for their apps.

Voice Based Digital Assistants 

Voice based digital assistants probably offer the most popular AI-best mobile technology already in use across both iOS and Android operating systems. From Apple Siri to Amazon Alexa to Google Assistant, there are several leading voice assistants presently in the market.

Intelligent voice interactions powered by AI and ML technologies are extensively being used for search functions across mobile apps. From speaking a search term or keyword for Google Search to searching YouTube for the relevant contents, voice based digital assistants continues to influence digital interactions and search experience.

Intelligent chatbots 

The intelligent mobile chatbots powered by AI and ML technologies represent another crucial leap. Mobile chatbots that earlier could only provide optional or rule-based responses to audience queries, are now more equipped to adjust to user questions and user contexts by learning from the previous interactions.

Moreover, app developers now can incorporate voice interactions into chatbot conversation to help users find the responses and results for their queries faster. This is why intelligent mobile chatbots have now emerged as an important tool for customer support and service and many big-brand organisations are relying on them to provide prompt and satisfactory customer support.

Personalised user experience 

By incorporating AI into the mobile apps, app developers can also open the scope of personalized user experience for their users more than ever before. This personalised app user experience begins by targeting users based upon locations to provide search results based upon their previous choices and searches.

Thanks to AI, apps can easily access a lot of customer information specific to their demographics, background, financial condition, buying habits and purchasing constraints. Based upon this customer data and data-driven insights, app users can be offered content and contextual solutions they need.

Enhanced Security

Both AI and ML technologies will help solving the major concerns corresponding to mobile app security. The AI and it’s subset technologies such as Predictive Analysis and Machine learning can provide insights on emerging security issues and glitches just in the right time and prevent major security outbreaks.

Particularly, ML technology by learning about the user behaviour patterns can easily detect anomalies and irregularities when they erupt and can send alerts to take preventive measures well in advance. On the other hand, by understanding the security loopholes and issues over time, AI and ML technologies can suggest comprehensive mechanisms and measures to make app security better.

Advanced search function 

Thanks to Machine Learning technology the users can easily optimize the search function in their apps. As the app continues to learn about the user intent and user focus through the search terms and keyword inputs, it can adjust the search results for better and more audience-specific search results.

The AI and ML based apps allows getting access to different user data layers including the location, previous search functions, frequency of interactions with mobile notifications, etc. Based upon this data and data-driven insights regarding the customer intent and preferences, the search function can deliver more appropriate results.

More relevant mobile ads

Most apps these days heavily rely on in-app ads for monetisation and revenue generation. But ads are also the most detested and disgusted digital content that prevent user engagement and user satisfaction in many cases. But not all ads and not at all times can give birth to such repulsions. Which ads are more relevant for which user and when the particular user is more likely to engage with the ads, is something of extreme importance for business conversion through in-app ads.

This is where artificial intelligence and machine learning technologies can play a handy role in catering t9 the customers the most relevant ads and in the right context when the chances of gaining traction is considerably higher. Thanks to machine learning inputs users can be grouped into different categories and accordingly ads content and tim8ng can be decided for enhanced engagement and conversion.

Wrapping Up 

Both AI and ML technologies made major inroads into the app development world with huge promise to cater to the user needs and preferences. Since mobile devices are highly personal in nature, the users always expect more personalised and context-driven user experience and this is the key area where AI and ML technologies have brought major transformation.

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