Artificial intelligence (AI) is changing the world of app development in ways that are not always visible. From Siri to Alexa, chatbots to voice recognition, it’s becoming more difficult for us humans to keep ahead of the machines. As we enter 2022, we can certainly expect more and more innovation in this space.
AI is used in app development (by companies like Elegant Media) and is currently used in a variety of ways. For example, AI is being used to enhance human abilities when coding. It is also being applied to prevent coding errors when creating apps. Additionally, AI is also being used to fix the flaws that are present in today’s apps. We will discuss how these examples fit into the larger scope of AI in app development below.
5 Ways Artificial Intelligence (AI) Is Used In App Development
1. Using AI To Enhance Human Abilities When Coding
AI is used to make developers more efficient when coding. At present, the main way that it accomplishes this is through natural language processing (NLP). This harnesses the power of AI to enable developers to complete their coding tasks more quickly and efficiently. Although it’s not entirely clear how NLP works, it is similar to how you or I might look up a word in the dictionary. Sometimes, we will struggle to find a word and we may use multiple parts of speech in an attempt to express what we want to say.
2. Using AI To Prevent Coding Errors When Creating Apps
AI is also used to prevent coding errors when creating apps. Although this isn’t as exciting as the first use case, it’s actually far more valuable. You see, some of today’s most popular apps are facing serious issues because of coding errors. This negatively impacts customer experience and directly impacts developer reputation. AI is being used to flag these coding errors during the development process so that they can be fixed before they cause problems for users or harm developer reputation.
3. Using Machine Learning To Fix Flaws In Apps
Machine learning is also being used to correct flaws in apps. This is how it works: you can create an algorithm so that it can predict what a person may want from an app based on their behaviour, age, and demographic. These types of algorithms are called predictive models. This allows developers to predict what type of functionality a user will need from their app before they actually require it. The best part about predictive coding is that it is designed to filter out false positives. This means that it only identifies the functionality that has been requested by users and not clutter unrelated features.
4. Using Machine Learning To Improve Apps Through Recommendations and Predictions
AI is also being used to improve apps through recommendations and predictions. This is how machine learning works: AI is used to predict what customers will want based on their behaviour, age, and demographic. Then, the app must be designed in such a way that it can accommodate those needs without forcing customers to seek out new functionality on their own. The most successful apps use machine learning to predict the actions of their users with good accuracy. They then use these predictions to create personalised experiences for each user who downloads their app.
5. Using Machine Learning To Save Time and Defer Decisions
Put simply, AI is also being used to save time and defer decisions that humans would otherwise need to make. For example, in order to optimise the performance of your app, you may want to know how many users you’ve lost during peak hours. However, this requires a lot of manual work if you choose not to use machine learning. Instead, using machine learning which requires less work than alternative methods and often produces better results. This allows you to save time for projects that are more productive or more enjoyable.
The Use Of AI In Future
It’s clear that AI is already being used in the app development industry, and will be to a greater extent in the future. AI will be used greatly in the coming years, and the ways in which it will will only be certain as time goes on. Predictive coding is going to be expanded with the use of personalised user data. This will constantly enhance app performance and offer a better experience for all users. AI will also make it possible to understand the needs of your target audience as well as their previous behaviour. That being said, you can then adjust your app by updating or modifying those features that have been flagged as necessary by predictive coding.