5 Best Ways of Applying AI in Mobile Apps

Artificial Intelligence (AI) witnessed a warm welcome in 2017 and earned a slot among the trendsetters. AI is predicted to culminate in a hallmark of tech development in the present year too.

A study by Mckinsey Global Institute points out that tech giants like Google and Baidu invested $20-$30 billion on AI in the past year. Of this, the lion’s share (90%) was dedicated to R&D. Only 10% of the expenditure went to AI acquisition. Google’s attainment of DeepMind is an example that shows how AI application is becoming mainstream.

The rapid penetration of AI in our daily tech can also be seen in Apple’s iPhone X. The smartphone boasts an A11 Bionic chip that Apple terms as “neural engine,” which is powered by AI. Some of the common AI features of this include augmented reality and face ID recognition.

Furthermore, the latest Gartner report indicates that the world’s largest 200 companies will implement artificial intelligence to revamp personalized user experience this year. All this confirms that the horizon for AI application and development is bright.

Why should you use AI in mobile apps?

At present, the AI development landscape is dotted by intelligent applications like personal assistants, chatbots, and more. However, there is a wide array of anticipated developments that will showcase the cross between mobile apps and AI in 2018.

Here are two chief factors that encourage the use of AI in your mobile app:

• About 90% of the users’ time spent on their mobile goes to apps with 70% of people losing interest in downloaded apps within seven days
• Customers expect personalized app use that is not hindered by high load speed and bugs

A good solution that maintains customer interest, as well as, satisfies user experience is a smart app. In this regard, the co-Founder and CTO of Clearbridge Mobile, Sanjay Malhotra, says, “The next set of applications will be a lot more intuitive and more interactive. A mobile experience has to be personalized and customized and what I see today is that it’s getting easier and easier to create those truly personalized experiences by leveraging AI and big data.”

An AirG Review confirms that AI-infused apps are an excellent means to deliver predictive smartphone app performance that users’ are currently demanding.

Best ways of applying AI in mobile apps

Now that the need for planting AI in your app is clear, here is a look at five ways of applying the artificial intelligence to your app:

1. Use it for automated reasoning

Logical reasoning is the key trick that machines use to beat humans at chess. The wheels of automated reasoning shift in the same way as a decision tree. A representative tree with branches that weigh benefits, risks, and costs is used to make a decision.

This use of AI in your mobile app can help your customers make quick decisions. A case in point is the Uber app. The automated reasoning-powered engine facilitates the user with timely decision-making regarding the fastest route to the destination.

You can create a utility smart app based on augmented reasoning that allows users to complete their work efficiently. Such an app will lessen the cognitive burden of the user too.

2. Learn behavior patterns

One of the best ways for planting AI in your smartphone app is for tracing patterns of user behavior. It will assist in providing content to the user that aligns with his interests and needs. For instance, Apple’s music app memorizes user preference to make suggestions to the user that are based on his taste.

Such an AI application can also help extract systematized feedback from customers. It will help you comprehend the popularity of content and allow you to make decisions as per users’ likes and dislikes.

3. Purchase prediction

Another excellent way to use AI in mobile apps is by programming the intelligence for determining predictive purchase behavior. Online retailers can drive substantial benefits by using this form of AI.

A leaf from PetCareRx’s book shows the importance of predictive analysis. It is an e-pet pharmacy that has been catering to the needs of its customers for plus 15 years now. When this online store tapped into the potential of purchase prediction, it was able to see its profit rise by 24%. Simultaneously, customer retention soared by 14%.

Such an AI analytics offers excellent customer experience. It is best for apps that provide in-app purchases or other e-commerce functions.

4. Recommendation services

Using AI in mobile apps for recommendation is perhaps the simplest and most effective way. It has a broad scope of implementation. A common reason for failing to hold the customer’s interest in your app is the failure to provide relevant content.

Nearly 91% of the users consider content as significant. It arrests attention and enhances user engagement. An antidote to this serious issue is AI that monitors choices that users make, remembers it, and makes recommendations accordingly.

An app for a business that sells products can make the best use of such an AI application. Such smart recommendations are an extensive source of revenue for the entertainment king, Netflix.

5.Voice recognition

A report says that voice recognition industry is estimated to reach a value of $601 million by 2019. Moreover, 50% of the searches will be done using voice by 2020. It outlines the bright future of voice recognition and its application.

Voice recognition in mobile apps is a good way of AI implementation. It facilitates people with increased connectivity, as only a few voice commands can help further connectivity. It also affords seamless navigation and provides greater accessibility and engagement with your app.

Polish your app’s voice recognition with automatic speech recognition (ASR) and natural language understanding (NLU). The latter uses AI the most as it processes users’ requests, understands them, and then uses machine learning to memorize all similar requests.

Final word

Conclusively, you can use AI for recommending services to customers, provide content based on their interests or offer purchase predictions with it. AI can also be used in apps for smart voice recognition and for learning user behavior patterns.