Are you looking to transform your mobile app with AI solutions? You can improve your user experience by integrating AI technologies to your app. We have compiled an introduction to AI-powered mobile apps to help you to understand how you can benefit from AI to improve your mobile apps.
How is AI impacting the mobile experience?
AI enables personalized mobile apps which helps improve user experience. This is the most common use case of AI in mobile apps. These apps can store many information about us such as our age, gender, location, hobbies, photos we like, the products we buy and much more.
From all this information, mobile apps provide us personalized content. An example of personalized content can be ads. Because mobile apps get to know us more, it shows ads that are more related to us. More related ads mean a greater number of clicks/engagement, which improves profitability.
Personalized content also improves user engagement and meets user expectations more. Based on “learning from” previous usages, mobile apps interact with users more. Chatbots or notifications based on user experience are examples of improved user engagement. According to Servion Global Solutions, 95% of user interactions will be powered by AI until 2025.
People can automate their tasks with AI-based mobile apps. As the mobile app understand how processes work, it can automate some procedures and reduce the duration of them. In this way, people can save time and improve their productivity. These tasks can be business-related such as auto replying apps or from our daily life, like using navigation apps for finding the shortest path.
How are mobile OS platforms leveraging AI?
Mobile OS platforms use many AI-powered solutions to improve user experience and satisfaction. For that, developers aim to make use of several AI functions and, they integrate them into mobile OS platforms. These functions enable mobile apps to provide personalized experiences and improve user productivity. Those main functions are as follows:
- User insight derivation: As a part of the Starbucks Rewards loyalty program, the Starbucks app can make personal recommendations from the menu whenever you are close to a Starbucks location.
- User data pattern recognition: SleepScore app uses your microphone and speaker to track your breathing rate and movement during the night. According to your sleeping pattern, it offers you personalized sleep coaching, too.
- Task automation: X.ai provides you an AI assistant to schedule your meetings based on your schedule. As you share the meeting details, it arranges a meeting in your available time and invites others to your preferred meeting platform.
- IoT integration: IFTTT app can change the color of your hue lights when your pizza order is in the oven.
How is AI powering mobile apps?
As AI becomes a giant trend in the business world, mobile apps are one of the usage areas which people can benefit from. Many features of AI can be integrated into mobile apps and improve user experience. The most common ones are listed below:
Personalization: By collecting user’s information, your mobile app can serve each user individually. It can track the user’s tastes or daily routines to offer a personalized experience. Tacobell’s mobile app receives orders and answers questions. From the information gathered, it also recommends menu items to its users based on their tastes.
Personalized user information can help companies to show the right ads to their users. In this way, users can see related and personalized ads while they use mobile apps.
AI can also deliver accurate forecasts by containing user information. Your mobile app can provide proper forecasts for your users. For example, Migraine Buddy is a mobile app that forecasts your possibility of a headache and gives recommendations for you.
Productivity: People use mobile apps to improve their daily productivity. These apps enable users to automate their manual work and allow them to save time for other tasks. For example, G Suite launched Smart Reply which can auto-generate replies for emails that only require a quick response. According to Prabhakar Raghavan, VP of Google Cloud, more than 10% of all email replies are generated via Smart Reply in 2019.
Image Recognition: Image recognition allows users to detect and classify entities within images. In your mobile app, you can successfully adopt this technology for face recognition/verification, emotion detection, object identification or any further purposes.
Speech/Voice Recognition: Speech recognition is another important tenet of AI. You can capture human speech automatically and accurately with this technology. The most common examples of speech recognition on mobile are Siri, Cortana or Google Assistant. You can read more about it from our in-depth guide.
Chatbots: If you plan to have a mobile app that can interact with people online, to contain feedback from the user, chatbots will be an efficient solution. Chatbots most commonly analyze your texts to communicate with you. You can integrate this with your mobile app to answer FAQ or resolve user queries. Feel free to read our related article about chatbots.
What are the alternatives to AI in mobile apps?
AI tends to achieve improvements that are a few percentage points better than best-practice non-AI techniques. Therefore best practice techniques that could be classified as non-AI are alternatives to AI approaches.
For example, collaborative filtering which is a personalization technique may be classified as a non-AI technique if we consider that it is a relatively old technique that does not rely on deep-learning. Compared to leading edge approaches, collaborative filtering tends to have results that are just lower by a few percentage points.
Of course, others may argue that it is an AI algorithm as it creates intelligent results. We don’t want to start a discussion about what is AI and are OK with the fact that once an algorithm becomes widely implemented, it is no longer called AI.
Which companies can help with AI-powered mobile apps?
An ideal company should be able to install AI-powered technologies. However, these solutions need to be feasible for mobile development. As AI presents many solutions to businesses, some of them might not integrate into mobile apps. Companies that specialize in those areas would have a hard time to help you with AI-powered mobile apps. It would be preferable to continue with AI companies that can implement their solutions on the mobile environment.
Experience in mobile development is a must, as well. It won’t be possible to build a mobile app without any mobile development knowledge or experience. Thus, it is essential to choose companies that both develop AI-powered solutions and have experience in mobile development.
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