It’s hard to ignore the impact of smart mobility, but when the smart mobility is blended with other technology, such as Artificial Intelligence, the force created out of that is just incredible.

People want to experience and try the artificial intelligence not only in large operations but only in day to day task. Smartphone is one such device that brings the AI technology in an easier reach of users. Also, these devices certainly redefine the whole concept of the human-machine interaction. It’s now more responsive, speedy and practically useful.

The same blend of AI and smartphones helps app developers create smarter apps. Such apps live up to the expectations related to load-time, speed, and user experience. Developers are brainstorming how they can deliver an app that matches exactly the needs of users. They see AI as one of the best technologies to do this.

In general, AI simulates the human intelligence, but in a precise manner, it’s largely based on its own ability of learning from surroundings, humans, and then reasoning to respond and self-correcting.

For now, the widely used forms of AI are chat-bots, smart sensors, Alexa, and Siri. These products are currently dominating the AI market. They are fully supported by smartphones that means you can use them through mobile apps.

Mobile app developers are putting their main focus on enhancing the customer experience by adding artificial intelligence capabilities to their apps. The AI technology can act as a mediator for smart watches, security systems, and several other connected appliances and gadgets used in home and offices.

AI technology has evolved to a level where it can automate the learning cycle, help in the data-finding, as well as add intelligence to software, adapt to the progressive learning algorithm, and be tuned to achieve the desired accuracy in operations.

Let’s learn how artificial intelligence can provide great user-experience

Personalization Experience

AI can help in collecting such data from apps that can be used to understand user-behavior and pattern. AI can use data to create the detailed insights of what customers like and what they don’t. When customers see what they like, the approach triggers more purchases to a particular product or service. On the other hand, an AI system doing all this actually learns everything from users themselves.

enhanced predictive reply

AI’s subset machine learning can predict replies for communication between a platform and users. Based on a user’s query, it can find the best suitable information from the database and then prepare answers to users. Chat-bots can interact with users in a natural way and deliver answers to most the relevant questions.

Voice-based search:

People do not like to type on mobile screens. It’s boring and tedious. This is why voice based search is being accelerated by tech giants. Google and Apple have successfully implemented the voice assistant to their operating systems, Android and IoT respectively. Google has even localized its voice search feature with different languages spoken over the world. Most of these voice-search and voice-assistant systems use AI and machine learning capabilities to deliver answers to users’ queries.

Machine learning

Machine learning based apps deal with a vast amount of data and the find actionable insights. The machine learning technology offers efficient, cost-effective, and reliable solutions for a problem and then finally increases decision making process based on the data-driven affairs.

Author Bio: Sofia Coppol is a digital marketing expert in Rapidsoft Technologies which is a leading IT consulting company providing full range it services including, IoT app development, Blockchain development, and big data app development  solutions.