How to integrate AI & ML in mobile apps & unleash future tech?

Artificial intelligence and Machine learning are contributing to building futuristic technologies. Smartphones are becoming smarter with the integration of artificial intelligence and machine learning. Mobile app development companies are exploring endless opportunities to integrate a high level of artificial intelligence and machine learning components to offer the best product to their clients. If you are someone who wants to know how to integrate AI and ML in mobile app development, this article is for you. Let’s start by checking out the stats of AI and ML in mobile app development.

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Stats of AI ML & mobile app market

Here are a few key stats explaining the sustainability of AI ML and how it will be the future of everything.

AI contributes highly to global economic growth, and by 2030 the contribution of AI will increase by 12.5% (Source).
65% of smartphone owners across 16 developed markets claimed they had used an app with machine learning integration at one point (Source).
50% of smartphone users take high benefit from predictive texts.

What is Artificial Intelligence?

Artificial intelligence uses logic to make processes efficient. With AI, you can build a system in your app that learns from the patterns of users framing if-then rules, decision trees, and other key elements to mimic human intelligence. For example, Instagram studies users’ patterns to generate content that users highly enjoy. It will show you posts by reading your activities on Instagram.

What is machine learning?

It is a subset of artificial intelligence focusing more on future data. Through ML, apps utilize the stored data from users and predict future patterns to make decisions. For example, when you type cat photos in google, it assembles all the data categorized into cats, verifies it through artificial intelligence, and delivers the right output to you.

What is the need to integrate AI and ML in mobile apps?

There are various benefits that AI and ML pack for the customers, either in mobile apps or a software experience.

Reasoning: Artificial intelligence and machine learning are infusing the power of reasoning into solutions. In simple words, they are teaching software to learn on its own by analyzing user behaviors and serving best to them. For example, Google Maps has learned how to deliver the best route to users by studying users’ data.
Personalized experience: YouTube can be a great example of the same. The company uses artificial intelligence and machine learning to evaluate the interests of users and provide them with the best choices.
Understanding the behavior of users: When it comes to understanding the behavior of users, AI and ML lead the competition. This gives a higher satisfaction rate to the customers when they see personalized shopping or product suggestions throughout the internet. For example, AI & ML is amplifying the E-commerce industry by suggesting the best products to the users.
With advanced search: With machine learning and AI, users get better search results, saving their time.
Better security: Artificial intelligence and machine learning in systems can predict threats in advance, offering users a great security experience. The systems identify possible vulnerabilities and take smart actions on their own.

How do you integrate AI & ML in mobile apps?

Integrating ML and AI in mobile apps requires some level of expertise. There are several android and iOS app development companies that are actively exploring the possible opportunities of AI and ML in their mobile apps. Here is how you can integrate AI and ML into your systems.

Identify the key areas

Every mobile app has its basic form and an intelligent form. You cannot apply intelligence to everything, so you must identify the key areas where you can improvise your mobile apps. You can start by identifying the key issues and concerns that can be improved. For example, customer support can be improved by integrating chat support in your mobile app. Further, security systems can be improved. If the search system is taking more time, you can again explore the AI/ML opportunities to make them better.

Prepare your data

Start by identifying the source of data. Collecting the data does not mean that you must collect all the data from all the sources. Keep only important data sources to collect the data. Plan the data in the best possible manner and frame decision trees in the stored data to generate patterns. Refining and organizing the data plays a key role in preparing the right sets of data.

APIs are not enough

So, do you have to hire iOS developers or hire Android app developers? Most of them might rely only on APIs. But, to integrate AI and ML into your app, you might have to hire developers who are data engineers and do not rely solely on APIs to explore AI/ML opportunities. Further, you might have to build an intelligent API on your own if you want to build a sustainable AI solution for your app.

Measurement metrics

Do not avoid integrating measurement metrics in your AI and ML solutions. You cannot open a wide scope to improve your advanced solutions without knowing how your advanced solutions are performing.

Top mobile apps with Machine learning integration

If you are planning to look at the reference for mobile apps that have already successfully integrated Machine learning, here are some of them.

Netflix: Netflix users discover great shows through a recommendation system processed by ML algorithms.

Tinder: The leading dating app uses Machine learning to show the best matches to the users.
Google maps: This app is magic, and it has started to use advanced ML to even predict parking spaces.

Top AI technologies for mobile apps

For artificial intelligence, there are multiple technologies that you can integrate into your mobile app.

Speech Recognition: Users want to perform minimum efforts to perform their tasks. And the fact that they can call people just using their voice is a great example of AI. You can add speech recognition to your app.
Chatbots: For a great customer experience and rich AI experience in your app, Chatbots are a trending example.
Biometrics: The great example of AI and ML is biometrics which you can use for a great security level.

Wrapping up Integrating AI & ML in mobile app

AI and ML are the future, and if you do ignore its strength, you might end up spending more than necessary resources, time, and effort. Yes, AI and ML require complex processes and advanced algorithms, but it is worth consideration. Because once your mobile app starts performing the most important tasks on its own, you realize how much cost you are saving for the same. It is suggested that you consult with a leading mobile app development company and unleash the power of technology into your mobile app.