At the vanguard of technology, artificial intelligence (AI) is underpinning a myriad of state-of-the-art developments that are changing the manner through which modern businesses operate. 

In fact, the advent of AI technology is constantly pushing the mobile internet domain towards innovation. 

In today’s article, we aim to explore the existing AI landscape with regard to mobile application use cases. We will also delve into the prospective future of this technological paradigm in the advancement of mobile apps. 

How is AI used in mobile applications?

To kick things off, it is prudent first to define Artificial Intelligence. 

AI is simply a multifaceted computing discipline that revolves around programmatically achieving a simulated manifestation of human intelligence and action through machine replication. 

As a computer science discipline, AI encompasses the systematic development of algorithms and models that are capable of problem-solving, learning, and decision-making. It works by mirroring the cognitive abilities that are inherent in human beings ultimately reshaping the way technology interacts with humans.

Within the mobile application landscape, AI capabilities are being deployed in several ways. For example,  

  1. Predictive analytics: AI is being leveraged to programmatically analyse user behaviour and interactions, in order to anticipate user needs and preferences ultimately augmenting the overall user experience.
  2. Personalised user experiences:  AI is being deployed to collect actionable data from mobile phones, like location, contacts, and GPS, in order to power personalised recommendations and experiences for users.
  3. Natural Language Processing (NLP): To enable real-time translation via NLP mechanisms (like Google Translate) and break down language barriers, enhancing global accessibility and inclusivity.
  4. AI-chatbot integration: AI is being exploited to provide instant and personalised user support, thereby reducing churn rate whilst augmenting user engagement and client satisfaction.
  5. Advancing security: To enhance the security capabilities within mobile apps by implementing AI-driven fraud detection and authentication methods, to protect user data and privacy.
  6. Augmented and Virtual Reality: Object detection and pattern recognition algorithms are being deployed to enable advanced functionalities like augmented reality, image recognition, and virtual reality expanding the utility of mobile apps. 

In practice, the fundamental premise of AI deployment within mobile applications is to make the interaction with mobile technology more practical, intuitive, streamlined and user-centric. 

This is consequently contributing to a more intelligent and adaptive digital ecosystem, enhancing overall convenience. 

For example, by leveraging location data, AI is being used to optimise navigation apps to better predict traffic conditions and suggest alternate routes for a smoother commute. 

Key areas of AI application in mobile apps

Despite the aforementioned ways AI is deployed in mobile apps, there are three key standout areas that are leveraging the technology, namely:

Personalisation and User Experience

AI algorithms are being deployed to continuously analyse user behaviour in mobile apps to programmatically identify their unique preferences. 

This advanced capability is especially prevalent in eCommerce applications to provide users with relevant recommendations and increase the likelihood of purchase completion.

By the same token, AI is being used to make mobile app navigation and transactions more intuitive, revolutionising the way users interact with mobile applications. 

For instance, in mobile banking apps, AI is being leveraged to assist customers with their financial planning, offering personalised suggestions pertaining to the optimal usage of their money. 

Voice recognition and assistants

Virtual assistants can leverage AI-powered voice recognition techniques to perform commands, allowing mobile users to communicate with an app hands-free. It helps in making mobile apps more responsive, intelligent, inclusive, and user-friendly. Such advanced speech recognition capabilities are indeed indispensable to those with disabilities.

voice recognition
Photo by Andrea Piacquadio

AI is also enabling mobile apps to provide real-time NLP translation capabilities whilst providing instant and personalised customer support, transforming the way users interact with mobile apps. 

Relatedly, AI is also being deployed to process dynamic call scripts and iteratively adjust dialogue suggestions for sales teams in real-time. It, therefore, helps sales teams to flexibly adapt to every call whilst catering to each customer optimally.

Image and speech recognition

AI is appreciably advancing image and speech recognition competencies in mobile apps, underpinning functionalities like augmented reality, and visual search capabilities. 

This interactive integration of AI in mobile apps is driving the evolution of customer experience whilst transforming the way users engage with mobile applications. 

For example, AI-powered image recognition technology can programmatically identify objects, people, and places in images. this helps to make it possible to create more intelligent mobile apps that are capable of recognising and responding to visual cues. 

For instance, LookTel offers unique mobile apps for individuals with vision impairments, enabling the recognition and spoken identification of various items, like currency, food packages, and videos.

Benefits of AI in mobile apps

AI technology presents several tangible benefits for the mobile application industry, such as:

Enhanced user engagement

AI augments user interactions in mobile apps, elevating them to be more intuitive and personalised. This consequently leads to more engaging and interactive app experiences. 

In fact, by aggregating and analysing vital data from mobile phones, AI facilitates mobile apps to provide highly tailored and intuitive experiences. It, therefore, helps deliver tailored interactions that resonate with individual needs. 

Read: How to Craft an App UI Design That Amplifies User Experience

Improved efficiency and functionality

AI-powered mobile apps are capable of efficiently performing repetitive tasks faster than a human. For example, data processing data, automatically responding to customers’ queries or even managing workflows.

This same efficiency can be trickled down to mobile apps, rendering them more useful in situations where users are required to perform repetitive tasks that are time-consuming and error-prone. For example, data entry, and scheduling. 

This exploitation of AI in apps can consequently help increase productivity and free up users’ time to focus on more critical tasks. 

Innovative features and capabilities

AI has enabled numerous innovative capabilities in mobile apps, like natural language processing, predictive analytics, and object detection. 

For context, object detection algorithms are enabling the integration of unique augmented reality and image recognition capabilities into eCommerce apps. 

For example, the IKEA Place App is appreciably augmenting and transforming the way IKEA users test furniture products in real-time via Apple iOS 11’s ARKit technology, before making a purchase decision.

Challenges and considerations when using AI in mobile app development

Despite its exciting potential to revolutionise how ordinary mobile users interface with mobile apps, there are still some challenges and questions that AI raises.

Let’s discuss some, shall we?

Privacy and security concerns

AI-powered mobile apps that leverage user-generated content that may be susceptible to misuse, like the spread of misinformation or inappropriate content. 

Additionally, the collection and management of data for AI applications raise privacy concerns, as sensitive user information must be handled with care to ensure compliance with regulations like GDPR.

Suffice it to say, ensuring AI-powered mobile apps must be carefully designed to protect user data and privacy, with robust measures to prevent unauthorised access and data breaches.

Ethical considerations

AI algorithms may sometimes inherit biases from the data they are trained on, resulting to unfair or discriminatory outcomes. For instance, an AI facial recognition system trained on biased data may have disastrous consequences when identifying people, amplifying already existing social inequalities. 

Relatedly, AI-driven apps must be built with ethical considerations into how AI algorithms make decisions and handle user data. This may help to build trust with users and ensure that AI-powered mobile apps are used in a responsible and ethical manner.

AI tools for app development

A few commonly used AI tools for mobile app development and their important features are:

  • TensorFlow is an open-source machine learning framework that provides a comprehensive ecosystem of tools, libraries, and community resources for AI development. It is widely used for building and deploying machine learning models in mobile apps, enabling developers to create innovative and intelligent applications based on AI-powered accessible solutions.
  • IBM Watson Studio assists in data analysis, modelling, and application deployment. It provides mobile developers with a diverse range of features for data analysis and machine learning model development, making it a versatile tool for AI-powered app development. 
  • Google’s ML Kit enables programmers to create intelligent iOS and Android applications. ML Kit offers production-ready ML models optimised for mobile, with features such as barcode scanning, text recognition, and face recognition, enhancing the functionality and user experience of mobile apps.

The future of AI in mobile apps

The prospective impact of AI on different industries through mobile app innovations is endless. For instance, in the healthcare industry, AI-powered mobile apps may be exploited to provide personalised health recommendations and detect early signs of disease. 

Relatedly, in the finance industry, AI may be deployed in apps to detect fraud and automate financial transactions. 

Some of the more recent emerging trends in AI and their potential impact on mobile apps include:

  1. AI-generated content: Many AI-powered mobile apps powered by generative pre-trained transformers (GPTs) possess the ability to automatically generate content like articles, videos, and images. This is transforming the information landscape, reducing the time and effort required for content creation whilst enhancing the functionality and user experience of mobile apps.
  2. AR and VR: In gaming, AI-driven elements are being used to adapt to mobile user behaviour, creating more dynamic and personalised gaming experiences. In fact, sectors like healthcare and education are exploring AI-powered AR and VR apps for training simulations and medical diagnosticsoffering a new dimension of personalised and context-aware experiences whilst catering to diverse industry needs.

    AR and VR: In gaming
    Photo by Michelangelo Buonarroti


It is predicted that the market for AI will demonstrate strong growth in the coming decade, growing twentyfold by 2030 to nearly two trillion U.S. dollars. 

Similarly, the international mobile application sector is predicted to generate more than $755 billion in revenues by 2027. 

These promising predictions show that AI and mobile applications are intertwined in their efforts to profoundly shape the future technology landscape, unlocking innovative possibilities across various disparate industries. 

From NLP-driven conversational interfaces to increasingly sophisticated virtual assistants and chatbots, we expect to see more dynamic and user-centric mobile app experiences powered by AI. And these will definitely span major global sectors like healthcare customer service, e-commerce, and finance!

Expect an exciting future where AI seamlessly integrates into the fabric of mobile app development, fostering a more intelligent, dynamic and user-centric digital landscape.

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