Knowing the steps is only one part of the AI equation.
AI is the wave of the future. As the world becomes more interconnected, computers grow in processing power, and data becomes more important to our day-to-day lives, Artificial Intelligence is sure to become a more common part of how we interact with computers, and each other.
This is especially true of smartphones and mobile apps. Because our phones keep us connected at all times, and include powerful processors, this is the ideal time to begin building AI support into mobile applications. In this article, we’ll give you a few tips on doing so during the custom application development process.
1. Integrate AI Naturally
AI can be powerful and useful, but that doesn’t mean that an AI-based solution is always the right one. Many AI applications are still in their early stages, which means that there should always be other methods by which users can interact with your application.
In other words, AI should be integrated naturally into mobile applications as a feature – there should always be other input methods, to ensure that users can interact with their phone in whichever way they choose.
In addition, AI should never be integrated into an app just “because”. AI should be used to solve an actual problem that you have – one that can’t be addressed by other technologies.
2. Be Mindful Of Your Limitations
An AI which runs on a cluster of 200 GPUs in a cloud-based server farm can do much more complex calculations and provide much faster response times, compared to an AI which is running on the (relatively) limited computing resources of a smartphone.
You should take this into consideration when building AI into mobile apps. One approach taken by many developers is to combine both cloud AI and local AI. A smartphone-based AI can help provide basic, immediate responses, while a cloud-based AI can be used to handle more complex calculations without overloading the local system.
3. Start Small (And Know What You’re Doing)
Before trying to integrate AI, machine learning (ML), and other such advanced technologies into your mobile applications, it’s important that you understand the benefits, limitations, and applications of AI and ML.
If you don’t understand these things, it’s possible that you may be trying to use AI and ML in the wrong way, or for the wrong application. It’s a good idea to start with a small AI project, and get some experience with this technology – before you try to deploy it in an enterprise environment.
4. Find The Right API – Don’t Do All The Work Yourself!
There are literally hundreds of APIs which can be used to build AI and machine-learning features into your application. You don’t always have to start from square one – often, there may be an API that you can use in the development process. This can help you establish a baseline AI capability which you can expand throughout the custom application development process.
Follow These Tips For More Effective Custom Application Development With AI
AI is a powerful tool, but it should only be used when it makes sense – and when it’s necessary. Following the above tips will help ensure that you make use of AI only when it’s needed, and will help you avoid common mistakes that are made during the custom application development process. Finding the right partner to assist you with your AI strategy is one way to ensure your success.