Integration of AI in mobile apps

Mobile apps have become an integral part of our daily lives, providing convenience and connectivity at our fingertips. On average, a user spends 4.8 hours per day on mobile apps. However, many apps still struggle to increase user engagement, whether it’s the time users spend in the app or the volume of app-based transactions. For a long time, app developers have explored avenues to boost Daily Active Users (DAU) or Monthly Active Users (MAU) metrics through various interventions like personalised notifications, gamification, and personalisation, with a vision to provide users with quick wins and ensure their continuous usage.

Artificial intelligence (AI) is transforming this landscape, offering innovative solutions to enhance user experience and engagement. By leveraging AI, apps can analyse sensor data, location information, and past user behaviour to understand the context and predict user needs. This contextual awareness allows apps to deliver personalised content, enhancing user satisfaction and loyalty.

Popular apps across various categories have already leveraged AI to personalise the user experience and boost DAU. Social media platforms like Instagram and X (formerly Twitter) curate personalised feeds, streaming services like Netflix and Prime recommend films users would love, shopping apps like Amazon suggest products users might want and even to-do list apps prioritise tasks based on user data – all with the goal of keeping users engaged and coming back for more.

With the advent of Generative AI and overall advancements in AI, we can now leverage the same to personalise and shape the “moment” and the “micro journey” of the user. This is different from the current personalisation paradigm where historical data is crunched to predict what the user would like. With moment personalisation, the app can analyse the “current” context and generate content on the fly for the user to engage with immediately.

For example, a fitness app can read multiple data points like the user’s health, day-specific calorie budget, and current heart rate to quickly create a workout routine that the user can do immediately to meet their health goals. If the app detects that the user is idle and hasn’t met their calorie burn budget, instead of a generic reminder to move, the app can create a 10-minute routine that can be performed at the user's convenience. Similarly, if the app knows the user is staying in a hotel with a gym, it can recommend an alternative gym routine. AI can also generate customised workout videos, offering a step-by-step guide that is far more personalised than generic stock videos. This ability to create bespoke content in real-time opens up endless possibilities for personalised user experiences, making interactions more meaningful and engaging.

We can now safely imagine a shopping app that designs clothes based on our style, or a newsfeed that generates articles tailored to our reading history and preferences, all in real-time. This technology allows apps to personalise everything from content and recommendations to the user interface itself, creating a truly unique and engaging experience for each user.

AI-powered chatbots and virtual assistants represent another significant advancement in mobile apps. These assistants can simulate the personalised service found in upscale retail environments, providing users with tailored recommendations and assistance. Unlike traditional chatbots that answer simple FAQs, these AI-driven bots can understand individual tastes, preferences, and social contexts to offer critical feedback and help users make informed decisions. For example, when shopping for a laptop, a user could ask, “Which laptop would you recommend for me?” The virtual assistant would analyse the user’s profession, requirements, and budget to suggest suitable options, performing an intelligent search that goes beyond basic keyword matching. With voice-first devices like Alexa and Google Home, app developers can leverage these highly connected and influential voice bots for an omni-channel experience.

This naturally leads to another important area where AI is making a significant impact--accessibility. Traditional accessibility features, like screen readers, offer basic support by reading out alternative text. However, multimodal AI models can enhance this experience by providing a more natural and interactive form of communication. AI can generate audio descriptions of the content on the screen. Voice bots can engage users in dynamic conversations, making the app experience feel more integrated and less like a series of workaround solutions. For vision-impaired users, this means a more engaging and natural way to interact with mobile apps, significantly improving their user experience.

Using AI in mobile apps is no longer a choice; it is becoming essential. Over time, users will begin to “expect” these personalised experiences, and this is the new normal. In a way, AI is truly redrawing the lines of how users interact with apps. As AI continues to evolve, its role in enhancing mobile app experiences will only grow, setting new standards for convenience, personalisation, and user interaction.

This article is authored by Shouvik Mazumdar, senior director, front-end engineering, Ascendion.