Artificial Intelligence is one of those sci-fi conceived technologies that was introduced with the fear of replacing a multitude of human-centric jobs. However, over time, the technology has cleared its stand that it is intended to make processes efficient and advance the skill set of teams that employ it. Teams that go beyond manufacturing and automation sectors.
In this article, we are going to deep dive into how AI is being put into use by the mobile app development industry – how to use AI for better user interface design and a robust, scalable experience.
Now as a prelude to the article, instead of taking you through the definition of artificial intelligence and how it is becoming a key source of innovation for industries, let us take a look at some statistics that showcases the technology’s unprecedented growth.
- A PWC report highlighted that AI will hold a share of $15.7 Trillion in the global economy by 2030.
- Some researchers believe that AI would become 1/10 as smart as humans by 2035.
- According to a Gartner report, by 2021, 80% of the emerging technologies would be based on AI foundations.
These statistics are only a peek into how big the technology is poised to be in the future. But how do these get incorporated into a sector that is on a growth trajectory of its own?
There are multiple ways through which application developers can integrate AI into their solutions. Let us look into some of the top ones:
1. Optimization of the Search Process
When AI is incorporated in the search process, several things become easier for the app users: it becomes less troublesome and a lot more intuitive to engage in the search process by performing suggestions, correcting the spellings, and finding what they are looking for through voice suggestion.
The crux of it is that adding AI in an iOS or Android app can help with optimizing the search process to an extent that it becomes a limited movement task. After all, delivering an immersive experience is a priority task for mobile app development agencies across the globe.
2. Incorporate Video or Audio Recognition
Nowadays, it is becoming extremely popular to have mobile apps with a chatbot functionality integrated into them. Apple Siri, Google Assistant, and Amazon Alexa are just a few of those voice and text-based assistant examples.
For some of the mobile application development companies and businesses, the use case of AI in video and audio recognition revolves around simplifying the authentication process via face or fingerprint recognition. While for some, it can also be used for enabling entertainment use cases like in the case of Snapchat or Instagram Reels.
3. Gain Insights Into Behavior Patterns
One of the most popular ways of adding AI in the mobile app development process stages is through the integration of algorithms that are capable of dissecting the users’ behavior patterns and making recommendations to them according to their behavior in the application. By providing personalized services and product suggestions, customer experiences are being increased to an extent that it contributes significantly to an efficient, ROI-friendly sales effort. Showcasing personalized suggestions is only one of the ways how behavior patterns are being used to better the customer experience. You will find several examples of the process across industries.
4. Develop a Smart Digital Assistant
In the current times, customers have moved on from the stage where they used to make calls and write long letters for accessing customer support from a company. And with almost every business under the sun having being moved online, customers have also let go of the “opening hours” funda when conducting their search for the eBay business. This means that it has become important for a business to be available to the users in real-time round the clock.
As an effect, a number of app development agencies have started integrating AI as a necessary means to help their customers get the needed information. One way they are achieving this is through the incorporation of a chatbot to align customers with the best customer service team and the assistance which they require. Companies such as e-bot7 have started offering high-level hybrid AI solutions for the customer service to better the service offering by a manifold amount.
5. Guarantee App Security
The rate of cyber and through mobile apps crime is ever-increasing. Any app development agency would swear upon the incorporation of AI for strengthening application security. The reason behind it is the secure and fast authentication process that AI technology promises. In fact, AI can be incorporated in line with a number of recognition types for passing authentication and user identification.
6. Onboard Experience and Gamification
Near-about 25% of the application users do not return to the application after the first experience. To lower these events, mobile app developers are getting inclined towards AI. The technicality of AI helps understand human psychology and enable UI/UX designers to create designs aligned with them. It, in turn, prevents the users from memorizing their login details, helps them view personalized content, etc. – examples of the fact that AI is in plan and would enhance the app usability. Moreover, it lets the app users have an access to in-app gestures that makes application experience a lot more enticing.
7. App Personalization
Through the integration of AI in mobile applications, brands and developers are able to offer a personalized experience to the users.
Applications would trace the user’s whereabouts and offer them location-centric results in real-time; meaning, the users would not have to enter their location every time – like in the case of Uber and other booking apps.
Secondly, AI technology also lets brands gather in-depth information about their customers through multiple modes like traffic, type of devices, and PoS machines, amongst others. The gathered data in addition to the gathered user behavior helps, in turn, with bettering the personalized results. This also plays a huge role in bettering the retention rate of users. A working example of this can be Starbucks’s AI-powered app – My Starbucks Barista. It enables the customers to place orders while they are in line to place orders.
Up until a point, you must have gathered how AI can make businesses better while giving insights into how businesses are using it in their real-life use cases. The information, however, cannot help until we look into how to implement them into applications. Let us look into that as the last section of the article.
How to Start with Implementation of AI into Apps?
The implementation of Machine Learning or its superset Artificial Intelligence calls for a substantial shift in the operation of an app that operates without any intelligence factor.
Here are some of the things which you should note when managing an AI project:
1. Identify the Issue You Would Like To Solve Through AI
What works best in the case of businesses who are applying AI in their application for the first time is its integration in one part of the app compared to the entire application or its multiple parts. Operative in a single part, it becomes a lot easier to not only manage but even use it to the best extent.
So, start with identifying the part of application that would best benefit from the AI incorporation – would the recommendation section benefit from it or can it be of help in giving a better ETA to the riders? Once you have that section known, start collecting data specific to it.
2. Know the Data
Before integrating AI inside an app, the best thing would be to understand where tha data comes from. At the data gathering and refinement stage, it helps in identifying the platforms where information would be inputted first. Then, move on to the data refinement stage – ensure that the information you have planned to feed inside the AI algorithm and formula is clean, non-duplicate, and an explanation of what the users like.
3. Don’t Get Dependent on the APIs
The next crucial thing to note is that the more extensively you use the app, the more un-useful an Application Programming Interface would prove to be. Although they would be enough to convert a traditional app into an AI-powered application, they won’t be enough for supporting a full-fledged AI product. Point is, the more you wish for a model to become intelligent, the greater you will have to work in line with data modeling: something which the incorporation of API can not solve single-handedly.
4. Define Metrics to Measure the Effectiveness of AI
There is no point in having an AI-based application designed with the expectation to better the business processes and outcomes if you are unable to draw out a mechanism that measures its effectiveness – an event which is possible only when you have an in-depth understanding of what you need to achieve and how.
5. Hire a Team of Data Scientists
The last consideration point in our list is hiring data scientists either full-time or partnering with a mobile app development company that has data scientists employed in their teams.
These data scientists can help with every data refinement and management tasks and everything needed at a must-have level for standing on top of the Data scientists will help you with all your data refining and management needs, basically, everything that is needed on a must-have level to stand and excel your Artificial Intelligence game.
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