How AI Is Going to Influence Mobile App Development and UX

AI. Or expansive artificial intelligence. Unless you are hiding under a rock (or you are an infant), you have come across this term one place or another.

To give you an idea about exactly how useful AI is in making our lives easier, here are two examples.

When using Uber, it provides you with the best route to your destination. It’s not magic but AI that makes it possible.

You get suggestions on Netflix, which saves you time to search for ones you would enjoy. Another blessing of AI.

Just like Uber and Netflix, AI is going to influence mobile app development and user experience (UX) design as well!

You are probably curious as to how exactly AI is going to do that. Stay with me. You would find out for yourself! Before this journey into the influence of AI gets bumpy (read technical), it is better if we get one thing clear. That is: what exactly is AI.

So what exactly is AI?

AI is a technology that helps machines or software make smart decisions or provide useful suggestions to its users. Furthermore, it enables a machine to learn from previous decisions without being explicitly coded to do so. It does so by statistically analyzing available data regarding any issue of interest using multi-layered neural networks.

OK. Understood. Now please explain how AI is going to influence mobile app development.

There are several stages of mobile app development. In this discussion of ours, we would focus on two of those stages which are impacted by AI.
The first step in mobile app development that AI influences is -

Developing a prototype for the mobile app

Developing a prototype for a mobile app entails transforming service requirements into a technology product that is ready for inspection.

This process, when done conventionally, takes months. These “months” may stretch into years if the app in question is intended to deliver extensive and multi-faceted service (like WeChat).

Enter artificial intelligence

Via natural language processing algorithms, an AI model would be able to convert the requirements for the app into codes that would form the basis for the digital skeleton of the app. On this skeleton, flesh and skin, i.e. graphical user interface and any other interactive element would put on. Your prototype is ready!

The second step in app development we are going to discuss is -

Deriving insights from analytics and handling errors

Mobile app development requires a myriad type of activities to be performed by the team responsible.
Thus, there would be numerous scope for process optimization. This optimization process often entails deriving insights from performance analytics of the team as well as similar products developed in the past.

Thanks to multi-layered neural networks of AI models, these data can be processed fast leading to the extraction of crucial insights and quick detection of errors in the performance of tech products. Such insights would help the be more efficient. Furthermore, the developed product would potentially provide a smoother and well-rounded service!

The scope of this article doesn’t allow me to discuss other ways AI is influencing the mobile app development process. If you are interested in greater details, do have a look at this from Forbes.

With mobile app development covered, let us move on to the influence of AI on UX design.

UX design involves in-depth analysis-both quantitative and qualitative-of the software or physical prototypes involved. Additionally, it also included empathy testing to get an educated estimate of how a potential user would feel when using a product.

So where does AI fit in when it comes to UX?

Well, the first step in UX design that AI influences is -

Analyzing user data to detect room for optimization

Data collected from users when testing a product can amount to the behemoth database.

Deriving useful patterns from such a massive dataset by using conventional pattern-recognition algorithms would significantly enlengthen the overall design process. Besides, such algorithms may not be able to take care of all the relevant factors.
An AI-based model is free from such shortcomings.

Because of its extensive neural network, it can factor in a wide number of factors and extract insights in a much shorter time.
As a result, an increasing number of user issues can be addressed, leading to a smoother experience!
The second step in UX design that goes under the whetting stone of AI is -

Competitor analysis

An integral part of UX design for any product involves a critical analysis of similar products in the market.
Just like the database consisting of user test data, rival product UX analysis is highly likely to be a heap of data.
Now, without analysis, this data is worth nothing.
And, as you have probably guessed, this is where natural language processing and deep learning capabilities of AI modes come in!

The natural language processing (NLP) allows the extraction of meaningful and usable patterns from the qualitative data on rival products.
And, as you have probably guessed, this is where natural language processing and deep learning capabilities of AI modes come in! When you are aware of such issues, you can make sure your product addresses those thus placing you in the front-runner’s position in the industry.
Via the deep-learning feature, an AI model can find the magnitude of error between the UX of existing products in the market relative to your one. Furthermore, it can also offer valuable suggestions via iterative deduction. These iterations are usually capable of factoring in factors not limited to the end-users themselves.

AI models can provide you with data on rival from various platforms (social media, website). It can also help you zero in on any micro-area of improvement. When you receive these data over a short period, the entire development process of your product will get optimized.
The result of such optimization has no choice but to be positive! And profitable!

Get ready for the AI tsunami!

As more and more data are generated, AI models would keep getting smarter. Thus as a business owner, it is imperative that you prep your team on the potential benefits that AI can render. At the same time, it would be crucial to handle any potential adverse effects it might have on your business.
With such a balanced approach, your pathway to the position of a leader in an AI-driven industry would be a lot less stressful! Good luck with your journey!

Author Bio:

Ryan Aslatt is a web strategist, freelance writer, and an independent blogger. He currently works at the mobile app development company WebAlive. He is used to writing well-researched articles that readers will find insightful, engaging and highly informative.