6 Practical Applications of AI in Mobile App Development

Raju Ram Khakhal
Jun 03, 2024


What’s common in Siri, Google Assistant, and ChatGPT? It's not just that they're all apps, but rather the underlying technology that powers them - Artificial Intelligence. The technology has emerged as a boon for the mobile app development industry, with varied applications. After the term ‘AI’ was coined in the 1950s, it has finally made its way into people’s lives. Many big sharks like Meta, Google, and IBM have started to embrace this emerging technology and are making efforts to make it widespread. That’s not all! Even a small business should have a good understanding of the practical applications of AI in mobile app development. 

AI technologies, such as deep learning, machine learning, and predictive analysis, have helped mobile app developers take personalization to the next level, both in terms of features and marketing efforts. In fact, the benefits of AI in mobile app development are so prevalent that businesses are now focusing on developing futuristic apps. And it doesn’t end here; there is more to come!

So, today, we will discuss AI's potential in mobile app development and its practical applications in the industry that will improve your solution. After all, as a thriving business, you should have a clear understanding of how AI and other emerging technologies are contributing to your overall growth. So, let’s get started with some exciting statistics on AI mobile app development.  

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Current Trends and Statistics for AI in Mobile App Development

  • 66% of businesses are considering investing in artificial intelligence to enhance the user experience of their mobile apps. (Source: AppDynamics
  • By the end of 2024, 80% of mobile apps will leverage AI for enhanced user experiences and deliver superior services. (Source: Gartner)
  • The global mobile AI market is predicted to reach $826.70bn in 2030. (Source: Statista)
  • According to a survey, 61% of businesses think of AI-powered apps as the means to gain a competitive advantage. (Source: Clutch)
  • According to a recent report, the AI app expects a 300% increase in the mobile app industry’s revenue. (Source: Accenture)


The above statistics underscore the growing prevalence and importance of AI in the mobile app development sector across different industries. 

The Benefits of AI Integration in Mobile App Development

AI integration in mobile app development comes with a plethora of benefits for businesses and end-users alike. It can significantly improve the user experience, which translates into improved operational efficiency and business growth. In this section, we will talk about the potential advantages of AI in mobile app development and how it is making its way already. 


1. Apps that Users Love

Have you ever thought of an app that automatically anticipates your needs and works accordingly? With AI, this is becoming a reality. AI analyzes user behavior to recommend relevant content, suggest helpful actions, and even personalize the app's interface.  This user-centric approach makes apps more engaging and keeps users coming back for more.

2. Streamlined Operations

Mobile apps are getting smarter day by day, and it's all because of AI. The technology transforms how users interact with apps and gives businesses a strategic advantage. 

AI isn't just about users; it's a boon for businesses, too. The technology streamlines processes within apps, identifying areas for resource optimization. Think of AI as a super-efficient assistant, automating tasks and minimizing errors. This translates to significant cost savings for businesses.

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3. Predictive Analysis

AI's ability to analyze massive amounts of data makes it a master of prediction. In mobile apps, AI can anticipate user behavior and market trends. This foresight allows businesses to make data-driven decisions, proactively address challenges, and stay ahead of the curve.

4. Robust Security

Keeping user data safe is paramount. AI steps up as a security guardian, using machine learning to detect and prevent fraud. The technology can also identify potential threats and implement robust authentication measures. With AI on watch, user data enjoys an extra layer of protection.

5. Growing with User’s Needs

The best apps are those that adapt and evolve. AI-powered apps are masters of this art. Machine learning algorithms continuously learn from new data, allowing the app to improve and grow over time.  This ensures the app stays relevant and delivers a consistently positive user experience.

6. Making Apps Accessible to All

Technologies like natural language processing allow users to interact with apps through voice commands or natural language. For those with visual impairments, AI-powered features like image recognition can enhance the app's usability. In short, AI is making mobile apps more accessible to everyone.

Thanks to AI, the future of mobile app development seems bright. With a focus on user experience, operational efficiency, and cutting-edge features, AI is transforming the mobile app landscape. As AI continues to evolve, we can expect even more exciting innovations that will push the boundaries of what's possible.

6 Ways to Use AI in Mobile App Development

AI might be a new buzzword for general people, but it has long been helping the app development sector in creating purposeful apps. So, let’s explore some of the practical applications of AI in mobile app development: 

6-ways to-use

1. Automated Reasoning

AI is a blend of science and art that uses analytical and logical reasoning to solve problems, help machines prove theorems, solve puzzles, and play chess matches. This AI-enabled feature in mobile apps can help healthcare service providers have data on patient check-in in the hospital, and even it has abilities to do stock trading on behalf of users. 

We have many examples of big brands integrating this feature into their mobile app. Let’s take Uber as an example. This ride-sharing app uses logical reasoning to optimize the driver’s routes so that riders can easily reach their destination. The algorithm behind this feature studies trillions of portions of data collected from the same route drivers. This not only saves the time of the driver and rider but also ensures a faster turnaround time for drivers to reach the destination. 

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2. Personalized Recommendations

Recommendation services powered by AI have become a game-changer in the world of mobile apps, particularly in the mCommerce and entertainment industries. These intelligent systems analyze user preferences and behavior to suggest relevant content, products, or services, ultimately enhancing the user experience and driving business growth.

One of the primary reasons mobile apps fail within the first year of launch is the inability to consistently engage users with relevant content. Even with a continuous introduction of new products or content, the lack of personalized recommendations can lead to low app usage and conversion rates.


By leveraging AI algorithms that learn from user data, mobile apps can provide tailored recommendations that users are more likely to find appealing and purchase. This feature has become a significant revenue stream for many mCommerce apps like Amazon and entertainment apps like Prime Video and Netflix.

While mCommerce and entertainment are the most prominent adopters of recommendation services, any business that engages in upselling or cross-selling can benefit from this AI technology. By suggesting complementary products or related content based on user interests, businesses can increase customer satisfaction, loyalty, and overall revenue.

3. Learning User Behaviors

Most platforms can learn about users' shopping habits to make the next session smoother. For example, the half-human, half-bot hotel booking service Snaptravel uses natural language processing (NLP) and machine learning to have conversations with users based on their needs. When bots get stuck interacting with the user, the human team takes over and teaches the bot how to handle the situation next time.

Another popular example of AI user behavior learning is fraud detection in online payments. AI pattern detection mechanisms analyze credit card details and purchase history as they occur and use this learning to check if someone has made a purchase recently that is not consistent with your purchasing habits.

4. Decoding User Sentiments

By tracking what's being said about your app anywhere - on stores, social media, forums or even messaging platforms, the AI ​​sentiment analysis feature gives you insight into how users are interacting with your application, with which competitors they compare you, etc.

Sentiment analysis provides you with direct feedback on which features to add and which to remove from your application suite. In addition to informing you about how users interact with your app, AI will also help you access insights related to your users' behavior across different platforms. You will then know which platform your users frequent the most, at what time, for what purpose, etc.

5. Customization 

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Have you ever wondered how some taxi booking apps send you a discount message right at the time you’re about to book a cab? Or how come your favorite restaurant's app suggests dishes you like to eat? This is thanks to AI.

One of the biggest benefits of having this AI functionality integrated into a mobile app is that it gives brands full access to usage data from the user's device location - the moment where they are active, the type of app they use, the people they talk to the most, the platforms they visit the most, etc.

Using this information, companies offer discounts to some users of the same app while focusing on cashback for others. AI allows brands to take personalization to another level, helping to redefine their customer relationship management (CRM) model.

6. Adding Predictability to Users’ Changing Lives

The much-discussed area of ​​machine learning is helpful when performing predictive analysis on your app's users. Suppose you have an on-demand medicine delivery app. With the help of predictive analytics, you will be able to notify your users that their medicines are about to run out and that they should order them again.

If you're just starting out, you can use these features in two ways—either base the entire app on predictive analytics or use it to push out information about products or discounts to keep users active in your mobile app. 

Or you could also launch an extension in your email app that would use a neural network to send automatic replies like Google does. If you are confused by the numerous options, it's time to talk to the experts at Mtoag Technologies.

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3 Key Considerations for Integrating AI in Mobile App Development

As you have understood the use cases of AI in mobile app development and how it is already making waves in the industry, it's time to discuss the key considerations that you shouldn’t ignore. 

While AI integration in mobile app development rarely stands a chance of something that could go wrong against the company’s growth, you still need to be cautious to ensure everything works well. So, let’s explore some of the key considerations for integrating AI in mobile app development: 

  • Instead of going after your competitors and overwhelming your app with AI integrations, incorporate the technology in small portions. Consider adding the features the users are demanding. For instance, you have a ride-hailing app, no instead of recommending people places to go, use a fare and time calculator so users can get an idea of distance an the money they will have to pay. 
  • Before integrating each feature, consider reviewing it on your own. Use tools to implement AI in mobile apps The most commonly used tools for AI integration in mobile apps include Api.ai, Wit.ai, IBM Watson, Microsoft Azure, and Tensorflow.
  • Invest in AI algorithms that are trained to divide the structured and unstructured data. They should be capable of converting this data into a valuable resource for a business that would add to its growth. 

5 Must-have Tools for Integrating AI Features into Mobile Apps

Developing AI-powered features for mobile apps has become increasingly accessible thanks to the wide array of tools and technologies available to developers. These solutions offer the necessary frameworks, libraries, and resources to streamline the implementation process, making it easier than ever to integrate intelligent capabilities into mobile applications. Let's explore some of the most popular options:


1. TensorFlow

TensorFlow, developed by Google, is an open-source machine learning framework that provides a robust ecosystem for building and deploying AI models. It supports a wide range of AI techniques, including neural networks, deep learning, and natural language processing. TensorFlow offers a user-friendly interface and supports multiple programming languages, making it a versatile choice for developers.

2. PyTorch

PyTorch, another open-source machine learning framework, emphasizes flexibility and ease of use. Its dynamic computational graph allows for rapid prototyping and experimentation, making it a popular choice for deep-learning applications. PyTorch offers extensive libraries and tools, ensuring developers have the resources they need to create cutting-edge AI-powered mobile apps.

3. Keras

Keras is a high-level neural network API written in Python that provides a user-friendly interface for building and training neural networks. Known for its simplicity and ease of use, Keras is an excellent choice for beginners in AI development. It supports multiple backends, including TensorFlow and PyTorch, allowing developers to choose the framework that best suits their needs.

4. Amazon Web Services (AWS)

AWS offers a range of AI services and tools specifically designed for mobile app development. These include Amazon Lex for building chatbots, Amazon Rekognition for image and video analysis, and Amazon Polly for text-to-speech conversion. AWS provides scalable and cost-effective solutions, making it an attractive option for developers looking to incorporate AI capabilities into their mobile apps.

5. Microsoft Azure

Microsoft Azure offers a complete suite of AI services and tools, covering areas such as natural language processing, computer vision, and speech recognition. Azure provides pre-trained models, APIs, and SDKs that simplify the integration of AI into mobile apps. Additionally, Azure offers a cloud-based infrastructure for scalable AI deployments, ensuring that developers can handle increasing demands as their apps grow in popularity.

These tools and technologies empower developers to create innovative and intelligent mobile applications. By leveraging the power of AI, developers can enhance user experiences, automate tasks, and provide personalized services to their users. 

As the demand for AI-powered mobile apps continues to grow, these tools will play a crucial role in enabling developers to stay ahead of the curve and deliver cutting-edge solutions.

How Much Does It Cost to Develop an AI-based Mobile App?

Developing AI mobile apps is quite expensive compared to traditional mobile apps. As AI is an advanced technology, and its full potential has yet to be uncovered, developers may face challenges while developing such an advanced mobile app. Therefore, individual developers and mobile app development companies tend to charge according to the project's complexity and scope. 

However, the average cost of developing an AI app ranges between $50,000 and $150,000. This is just an estimation; the exact cost depends on three crucial factors: 

  • Data cost
  • Research cost
  • Resource cost

Apart from these, there are many other cost factors that influence the budget for developing an AI app. These include: 

  • Number of the features in the app
  • Types of AI: process automation, voice recognition, machine learning, or chatbot
  • Software requirement specifications
  • App development complexities
  • Development platform, iOS or Android
  • Usage of the third-party APIs
  • Location of the mobile app developers

Apart from these factors, the app development cost also depends on the type, the category, and the working hours of your development team. Here’s an hourly breakdown of AI app development: 

  • Market Research: 40 – 80+ hours
  • Wireframing & Prototyping: 40 – 90+ hours
  • UX/UI Design: 40 – 300+ hours
  • Front-end App Development: 50 – 250+ hours
  • Back-end App Development: 100 – 400+ hours
  • QA Testing: 50 – 100+ hours
  • App Launch: 48+ hours
  • Total AI App Development Hours: 1300+ hours

To find the exact cost of your AI mobile app development, here’s a formula: 

Development Cost = Number of hours x developer’s cost per hour

For instance, you have hired a mobile developer from India, where an average hourly rate is $35, and they have spent 1600 hours on your project. Then, your AI app development cost would be:

1600 hours X $35/hour = $56,000



After reading this blog, you might have understood the potential of AI and its practical applications in mobile app development. By integrating AI-features, businesses can ensure better user experiences and intelligent interactions with the users. 

From personalization to offering virtual assistance, AI has come a long way to become a technology that we can’t live without today. Technology has been a boon for the healthcare, finance, and education sectors by offering improved efficiency. 

In case we miss out on something or you want to know more about the potential of AI in mobile app development, just contact Mtaoag Technologies anytime. We will be ready to assist you with our expertise and excellence in the industry. 


What is the Application of AI in App Development?

AI can supercharge app development by automating tasks, personalizing user experiences, and improving app functionality. It can help write codes, analyze user data for recommendations, or even help design user interfaces.

How to Use AI to Build a Mobile App?

There are several ways to leverage AI in your mobile app. You can use AI tools to automate code generation, integrate chatbots for customer service, or utilize machine learning to create personalized recommendations – all to enhance your app's features and user experience.

What is the Future of AI in Mobile App Development?

We expect AI will play an even more prominent role in the future. AI could assist with more complex tasks like designing entire app layouts or writing bug-free code. We might also see AI helping developers create even more intelligent and interactive mobile apps.

Can AI Replace Mobile App Developers?

While AI can automate many tasks, it won't replace developers entirely. Developers will still be needed for creative thinking, strategic planning, and overseeing the overall app development process. AI will likely become a valuable tool that frees up developers' time to focus on these core aspects.

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