AI Tools To Improve Your Mobile Application
The capabilities of artificial intelligence (AI) are so extensive and we have barely tapped into the proficiencies of this technology. It is estimated that by 2030, AI will have contributed $15.7 trillion to the global economy, which would make it one of the world’s leading commercial opportunities.
Including AI in both the initial and continuous development of your app is important. Take advantage of the smaller subsets of AI such as expert systems and machine learning. Machine learning provides systems the ability to automatically learn and improve from experience without being explicitly programmed to do so. Expert systems are similar in that they use AI to mimic the judgement and behaviors of a human using expert knowledge in a specific field.
Any application that collects user data requires a robust data security strategy in order to build that initial sense of trust in your user base. They must feel comfortable enough that any shared data will not fall into the hands of cyber criminals or other parties. Cyber security within your application is crucial to the safety of your users’ data. In fact, web-exposed applications are the top cause of data breaches and depending on the popularity of the application, thousands, if not millions, of users could have their data breached if the security is not tight.
It doesn’t matter how popular or secure your app may seem, either. If there is information hackers want, they will try to find the way in. This was shown in May of 2019 when nearly 5 million employee and customer accounts were hacked in popular food-delivery service, DoorDash. Driver’s licenses, addresses, and partial credit card numbers are just a few examples of personal information revealed to hackers before the company cut off access to the breached information.
Applying AI in your previously existing cyber-security method can enhance the capabilities already set in place. Application security covers the security of the web client on mobile applications in all areas of the security development lifecycle. AI techniques, such as machine learning and expert systems, can be used to improve that security to identify and forecast security threats and vulnerabilities. The goal is to resolve or prevent these issues before they take place.
When AI is integrated into the search features of an app it can help optimize the searching process for mobile users. The searching process, suggestion features, spelling corrections and even voice search can be greatly improved with the addition of AI.
Through machine learning, in-app search results can be more contextually relevant to the user through the algorithms the bot undergoes. This means as something is searched more and more by different users, the bot will learn and recommend this search query when others search for it. This can also be utilized to gather user data to further improve the application’s user-friendliness.
In addition to advanced search, you can implement voice search to increase your apps performance. This will allow users to search for a product or ask for a question using voice commands at the click of a button or through a simple voice command. This not only reduces the time it takes to search for something by making the process more efficient, but it also increases accessibility for users with physical limitations.
The introduction to chatbots for most of us probably occurred in the early 2000’s with the use of AOL’s bot, SmarterChild. SmarterChild was a robot that lived in the friends list of your AOL Instant Messenger (AIM) friends list. You could use SmarterChild to ask for stock quotes, movie times, weather, or any other useful information. While this bot was designed for desktop computers, the knowledge learned from early chatbots helped pave the way for what we use today.
Machine learning and natural language processing are the two subsets of AI used in the operation of chatbots. As these two technologies advance, the responses given by chatbots will improve as well. Robots that use machine learning adapt their knowledge based on interactions with users and offer personalized responses. This means your 50th conversation will be drastically improved from your first.
On the business side of things, it is extremely important to be able to engage with customers regularly. If you’re planning to develop an e-commerce mobile application, a chatbot might be the perfect fit for your platform. Chatbots can track customer responses and feedback and allow access to the collected information for your tech team’s analysis.
Customer service can also happen directly in the application for commonly asked questions or issues. Always-on AI customer service lets users get quicker responses outside of normal business hours. By 2021, it is estimated that 85% of customer interaction will be handled without human agents.
AI can be a powerful tool in just about any app you’re developing, whether your goal is user-friendliness or smoother operation, but it’s vital to understand that the best approach is one of trial and error. This will allow the AI to learn based on user interaction and improve as you iterate on your app’s design and function. Some things you try may not stick with your users but that feedback will help you retain only the best, most popular features of your app.
Monitoring technical and behavioral data to make changes is a more scientific method to determine what’s working and what’s not. Then it becomes easier and less subjective when you make development decisions, like implementing AI and other tech options.