• Tokyo : 21:04
  • |
  • Singapore : 20:04
  • |
  • Dubai : 16:04
  • |
  • London : 13:04
  • |
  • New York : 08:04
  • |
  • Sydney : 22:04

Influence Of Artificial Intelligence On Mobile Application User Experience

Oct 22, 2021

The emergence of artificial intelligence is nothing less than a paradox. At one glance, everybody appreciates how helpful it is, while on the other hand, people feel pretty intimidated by its prying eyes. Hence, artificial intelligence has left everybody with mixed feelings. 

In simple words, artificial intelligence is work done by machines that have human brains like simulation. This computer-based system can think, process and generate actions that a human brain can, for example, natural language processing, speech recognition, machine vision. The machine can comprehend data given to it based on the input it has been fed with, then decide to act upon executing the operation. The machine can think and conjure a decision to act upon, which we humans can do instantly. We don’t realize how complicated it is for our brain to do so, but we do, and we are very humble about it. Humble enough to build consciousness into a machine so that it can work at least 1/100th as efficient and independent as us. It makes our work easier, saves time, effort, human resources, and is cost-effective. Hence, it is a whole new level of advancement for human civilization. However, it doesn’t cease there, which is a problem as we will discuss further. 

To build a view on that, we first have to understand the fundamental functioning of AI. The success of an AI mechanism depends entirely on the data fed to it. For example, suppose an AI is built to identify a cat. In that case, the engineers will have to feed the system with thousands and thousands of pictures of both cats and random things which are not cats and demarcate them each manually into two broad categories: cat and not a cat. This is called a data set. The more data set (input) it is fed with, with this distinction, the more accurate and efficient the system becomes in identifying cats. This is how a simple artificial intelligence system is built from scratch, and more actions, formulas, and coding advances it to what we see around us such as, manufacturing robots used in industrial facilities, self-driving cars, intelligent assistants, proactive healthcare management, disease mapping, automated financial investing, social media monitoring. 

Based on the simple principle of inducing the skill of human comprehension and thought processing in a computer system, there are three major branches of AI: 

(1) Artificial General Intelligence (AGI) - can do everything that involves general human prudence and can apply intelligence on multiple tasks at hand. It is also called deep AI and is the most popular and extensively explored dimension of AI. 

(2) Artificial Narrow Intelligence (ANI) - can do a single task in hand only but with extreme intelligence, for example, playing chess or crawling a web page. It is called “weak AI” because of its ability to operate only in a predetermined, pre-defined range. One of its well-understood examples could be Siri. It is narrow because it is not a conscious machine, which responds to our queries. Instead, it processes our language, enters it into a search engine such as Google, and fetches the results to us. That is the reason when we ask abstract questions to Siri or Google assistant like “what does it mean to be alive?” or “is there life beyond death?”, we get absurd answers. Then both the assistants’ surf all the philosophical articles related to such subjects, present them on the internet and then show them to us. 

(3) Artificial Super Intelligence (ASI) - Though this is a hypothesis, the idea is very much there in the minds of AI developers. This is that branch of AI, which has to be tread lightly upon according to engineers, because they believe that there will be a time when AI will surpass the intelligence of the greatest human minds ever, in every domain, be it arts, general aptitude, problem resolving, everything. And it might also bring doom to humankind. Yes, that idea alone is the source of many science fiction movies, including Terminator, Chappie, MCU’s Age of Ultron, and many other series and shows, with which your Google assistant can bombard your screen. 

However, AI is very much vulnerable to critique less far fetched than that in the present time. It has been accused of many declarations such as automating jobs, widening the socio-economic gap, instability in the stock market by algorithmic high-frequency trading and critically alarmingly, threatening privacy and security of data. 

There are 5.27 billion unique mobile phone users in the world today, and it is predicted to grow at a rate of 2.3% every year. With this upsurge in mobile users worldwide and technology becoming more data-driven, AI is bound to heavily influence the mobile application user experience (UX) across the globe, and we will tell you how. 

On the face of it, mobile application UX is all about streamlining services for users on the go. However, it has a lot to do with mobile users’ particular needs and limitations. It is growing important with the booming increase in mobile users, who have an altogether different requirement than desktop users. UX designers and mobile app developers are responsible for catering to all desktop-like features on fingertip size. When the user’s attention span is short, results are demanded real quick, with less effort and no friction; when the fear of losing signal, power and internet is wandering all the time, a mobile app development company has to build the UX such that it can support multitasking, give every information to the user in his surrounding and continually engages them.  

For this very purpose AI, specifically Artificial General Intelligence (AGI), is used in the following ways: 

Analyzing User Behaviour

To boost engagement and a sense of understanding between the brand or mobile application and user, AI analyzes the pattern of the user’s behaviour by observing the user data for a long time and then predicts insights to the company who can provide more user-centric services. For example, the reason why Spotify’s discover playlist is applauded is because of the algorithm behind it, which deciphers your musical inclination for a substantial period, letting you play songs one after another, and then starts suggesting songs that are in the same tempo, genre and by similar artists and thus giving you a good playlist.  

Nevertheless, on the other side, when there is a sudden shift in the user’s preference, it takes time for the AI to identify that change and then change its pool of suggestions for the user. Therefore, the user must continue making similar choices for a certain period until the AI is well fed to note it and provide related services. The best example for this is Instagram, where your feed shows you things you are interested in, but the feed doesn’t change as fast as your interest. 

Chatbots To Address Customer Queries

Today many online shopping platforms use chatbots to update their customers regarding their orders, queries and upcoming offers. Although its communication with the customers is limited to the questions, it has received in its data set. If the customer paraphrases their question differently than the AI can attribute, the chatbot fails to revert accordingly.  

Personalized User Experience 

You must have noticed how Google, Amazon, and Youtube start advertising things that you have been looking up on the internet here and there. Or why each time you surf a website, you have to allow it to catch the cookie. The AI notes your digital imprint to provide a more personalized service to you; it can make your UX across the applications pleasant. 

Unfortunately, however, it also inculcates among users a feeling of being watched. And if psychologically speaking, then yes, no user feels comfortable by the idea of the deep AI keeping tabs of the user’s search, preferences, location, consumption behaviour, social visibility, accessibility and cumulatively, their whole being because if this data falls prey to wrong hands, which it is very vulnerable to, it can be a severe violation of consumers’ privacy. 

And the debate on AI and its hampering privacy and security has been around for a long time now. Tech Giants such as Yahoo, Alibaba, Facebook, Linked In, Adobe and many more have been thrown in the global limelight of criticism and legal repercussions because of the data breach. However, lately, companies continue to account for this data for better UX only after seeking user permits. 


Suppose a particular application wants to know your location. In that case, you very well know by now that it seeks to support you with local information, context-driven services, suggesting you products as per your whereabouts and surroundings. And this precursory action is taken not just by location-driven application services but by applications that do not need your location for any apparent reason known to you. And though the permissibility and the AI’s permeability lies in your hand, users often find themselves in two minds and then to allow or not to allow the AI, that becomes the question. 

That being said, it is inarguable that companies, especially those dealing in the B2C model, that is business to consumer model, may leverage AI to optimize and improve their services to their customer base significantly. 

For example, artificial intelligence can aid mobile app development in the following ways: 


Every application must have a feedback report for the user at the end, which should be easy and quick for the user’s convenience. The more feedback the AI gets, the more it can determine the application’s success and later give suggestions for improvement for the application itself. 

Deciphering User Beyond Numbers 

Since AI highly depends on the data set, it values quantity more than quality. Therefore, it is impossible to understand why a user chooses what he does. That is when such action must be backed up with follow-up questions so that the application can understand user preference adeptly. 

BETA Testing

The virtues of AI can be exceptionally beneficial for the beta testing of applications. In this phase, the AI is open to varied and complicated data sets. Thus it grows more efficient in responding to a specific task. 

Therefore, building a view on artificial intelligence when considering its impact on mobile application user experience often throws an individual in juxtaposition since neither can we agree to the threat it poses to privacy, security and data breach, nor can we disagree that ultimately it is created to serve customers with the best user experience. Hence, AI will continue to thrive and influence every field predominantly as long as the customer values convenience and data remains to be power.

Featured Clients

Our Associations

Sister Companies

Copyright © 2024 - B A Barry. All Rights Reserved.