







When we talk about disruptive technologies, Artificial Intelligence (AI) tops the list. It has brought revolutionary changes in business processes with the help of Machine Learning (ML). Both AI and ML are still in the nascent stage, but they have started exerting a huge impact on a mobile app development domain. Today, many enterprises want to leverage the benefits of AI through business apps. Here we mention the importance of AI in mobile app development.





How to Implement AI and Machine Learning in Your Existing Application





Importance of Integrating Machine Learning in Mobile Apps





Today, industries rely on the automated system to accomplish complex tasks globally. From simplifying the operations to increase productivity, machines can assist entrepreneurs to stay ahead in the growing competition. The machine learning is about learning our behaviors to make our daily activities easier than before. If we consider it from the industrial perspective, the integration of ML and AI in mobile apps can serve this purpose effectively.





As technology evolves, the business apps also get advanced and become more capable to meet the user’s requirements and growing competition. These days, it is of utmost importance for the companies to deliver customized solutions to people’s questions or problems. There, understanding behavior can help enterprises to serve customers in a better way. Machine learning app development makes it possible.





Let’s take a few examples of the usage of ML and AI in Mobile App Development .Gmail offers Smart Replies, Amazon shows Recommendations based on searches, and Facebook provides Proactive Detection through AI and ML. A report suggests that the number of companies, which are ready to invest in ML and AI, is expected to show a twofold increase in the next three years. Here are three fundamental ways of integrating machine learning in mobile apps.



Automated Reasoning

Have you ever wondered how Uber and Google Maps optimize the route to enable the users to reach the destination quickly? Well, automated reasoning has an answer to this question. This AI-based functionality facilitates the computers to apply to the reason for solving problems.



Personalized Recommendation

R etailers and B2C industries remain the biggest beneficiaries of this use case of AI and ML. Amazon, Netflix, and Flipkart use this AI-powered functionality to attract and retain customers on their apps.



Behavior-based Security

The learning of the user’s behavior is at the core of machine learning technology. This understanding of the app user’s behavior can help AI to make the app more secure. Even if someone has stolen the data and try to transact online without the victim’s knowledge, the AI system can identify the uncommon behavior and immediately stop the transaction. In a way, AI secures mobile apps.





Major Benefits of Integrating AI and ML in existing business apps

Your existing app can get the benefits of AI and ML by integrating any of these fundamental ways. Here are the key benefits of machine learning app development services.



- Personalized Experience

AI algorithm is designed to analyze the user’s behavior and give responses accordingly. Now, when AI and ML-based features are integrated into the existing business app, they will provide personalized recommendations and notifications to the app users. Machine Learning application development facilitates you to know everything about your customers and you can run the marketing campaign more effectively by offering a personalized experience to customers.



- Search Functionality

People tend to search on the move these days. The AI-powered app can enhance and optimize search options. AI algorithms learn from the user’s different questions and provide contextual search results. The AI and ML integration also facilitate your existing app to provide functionality in line with the user’s search histories and particular options. You can also add the AI-based features like voice search in the existing app.



- User-focused Services

Machine learning mobile application development is aimed at developing business apps that can enable marketers and companies to offer user-focused services. It is easy to understand the user’s preferences and behavior patterns with AI technology. If you integrate the AI in your existing app, you can readily get and monitor the data regarding age, locations, app usage, and search patterns of your app users. It can enable you to send personalized notifications and real-time alerts to the customers.



- Relevant Ads

Many business apps can act as a powerful and cost-effective marketing tool for companies. As the user’s requirements keep on changing, it is necessary to show them the relevant ads. For example, it is meaningless to show ads of footwear to the users who are in search of utensils or laptops. In other words, integration of AI and ML in mobile apps can assist you to address the customers with the products and services they are looking for.



- Enhanced Security

Both AI and ML can enhance app security by strengthening app authentication. Image recognition, audio recognition, fingertip recognition, and other functionality are based on AI. Users can set up the security authentication using any of their biometric data and make their apps secure. ML also improves your existing app’s security by establishing access rights for your app’s users.



- Competitive Edge

Many companies are yet to avail the advantages of AI and ML in their apps. If you integrate ML and AI-related features in the existing apps, you can get a competitive edge over such peers. Your customers can find your AI-based app more secure and efficient as compared to other similar apps, and as a result, you will have better chances of acquiring a loyal customer base.





Advanced platforms like Azure, Tensorflow, and Amazon AI are highly useful to develop a mobile app with integrated machine learning.





Concluding Remarks

Machine Learning mobile app development domain is full of challenges. But, as AI and ML will be mainstreamed in the corporate sector, we will have many ML and AI-based apps. Right now, the mobile app development companies and AI experts work on data mining, data augmentation, and selective data storage to get an optimum outcome from machine learning applications.



