What if your users never opened your app directly again?
They would simply ask their AI assistant: “Order me dinner,” “Find a nearby hotel and book a room,” or “Buy a ticket for tomorrow evening” – and get the result in seconds. No searching through the App Store, no browsing through multiple apps, no navigating through your product’s interface.
Sounds like a scenario from the future? In reality, this shift has already begun. AI assistants on Android and iOS are gradually becoming a new way for users to interact with digital services. They are moving beyond answering questions and are starting to help people complete real-world tasks.
But this raises an important question for businesses: will your mobile product become part of this new experience, or will an AI agent choose your competitor’s app instead?
Today, most mobile applications are still built around a traditional model: users open an app, find the right feature, and complete an action themselves. However, the rise of agentic AI is changing the rules. In the future, the value of an app will depend not only on its user interface but also on how easily AI agents can understand its capabilities and use them to solve user needs.
That is why Apple and Google are introducing new ways for AI assistants to interact with mobile applications. For developers, this represents a new technical challenge. For businesses, it is an opportunity to gain an advantage by preparing before competitors do.
From App-Centric to Intent-Centric: What’s Actually Changing
For the past two decades, mobile applications have been built around one simple idea: the user comes to the app and looks for the feature they need.
Need to order food? Open a delivery app, choose a restaurant, find a dish, and place an order.
Need to buy a ticket? Open an airline app, enter your search criteria, compare options, and complete the purchase.
Need to transfer money? Open a banking app and go through several steps to send the payment.
This model worked because the app was the main point of interaction between the user and the service.
But AI agents are changing the way this interaction works.
Instead of thinking: “Which app should I open?”, users will increasingly think: “What do I need to get done?”
For example: “Find me the most convenient flight to Berlin next Friday and book it.”
The user does not need to know which app to use, where the right button is located, or what steps are required. Their only task is to describe the desired outcome – and the AI should find the best way to make it happen.
This is the shift from an app-centric approach to an intent-centric one.
In the traditional model, an app waits for users to open it. In the new model, an app needs to be ready when an AI agent approaches it on the user’s behalf.
For businesses, this represents a fundamental shift. The value of a mobile app will no longer depend only on its design, navigation, or number of features. It will also depend on how easily AI agents can understand what the app can do and use those capabilities to solve real user needs.
In other words, the future of mobile apps is not just about competing for a place on the smartphone home screen. It is about becoming the service that AI agents choose first when a user expresses an intention.
iOS: App Intents Just Became Mandatory
Developers now have a new standard way to make app capabilities available to Siri, Apple Intelligence, and other system-level experiences.
Previously, users had to open an app themselves and navigate through the interface to complete a task. Now, apps need to provide AI with a clear way to access specific capabilities – whether it is placing an order, finding information, creating a booking, or completing another action on the user’s behalf.
App Intents serve as a bridge between mobile applications and AI-powered assistants. They allow apps to connect their functionality with Siri, Spotlight, Shortcuts, and the Apple Intelligence ecosystem, enabling users to interact with services through natural language commands.
For businesses, this creates a new level of app accessibility. Users may no longer need to search for and open your app manually – they may simply ask Siri to complete a task. If an app is not prepared for this type of interaction, it risks being left out of the next generation of user experiences.
That is why Apple’s app intents are becoming more than just developer terminology. They represent an important part of the future strategy for mobile products.
Android: AppFunctions Is Coming – and Early Movers Will Win
Android is moving in the same direction as iOS: mobile applications are gradually becoming part of the AI agent ecosystem. The new AppFunctions approach is designed to help apps expose their capabilities to AI systems, allowing them to perform actions on behalf of users.
Today, the technology is still in its early stages and available as a private preview for a limited group of trusted testers. This means it is not yet a mature, widely available solution – but rather an early signal of where mobile development is heading.
For businesses, this creates an opportunity to prepare ahead of time. Companies that start evaluating their applications and identifying the most valuable capabilities to expose to AI agents today will be better positioned when the technology becomes widely available.
Conceptually, Android AppFunctions is similar to how many developers already understand MCP (Model Context Protocol) in the AI agent ecosystem: it provides a structured way for intelligent systems to access and use external services. In the mobile world, AppFunctions could become a bridge between applications and AI assistants, enabling new interaction scenarios with technologies such as Gemini on Android.
That is why Google AppFunctions Gemini Android represents more than just a new developer feature. It is an early sign of a broader shift: mobile applications are moving from standalone interfaces toward becoming active participants in the AI ecosystem.
Why This Isn’t Just a Developer Problem
When it comes to integrating applications with AI agents, it is easy to view it as another technical task for the development team: add new capabilities, update the codebase, and learn new APIs. But the reality is much broader. This is not only about technology – it is about how users will discover and interact with digital products in the future.
Imagine this scenario: a user wants to book a hotel. Instead of opening a familiar app and searching through available options, they simply ask their AI assistant: “Find me a hotel near the city center and book the best option within my budget.”
At that moment, a new type of competition begins. The user may never see a list of available apps – the AI will choose the service that is best suited to complete the task.
This creates the main business risk: your app could become functionally invisible to the growing number of AI-first users. Even if your company has a great product, a large user base, and a strong mobile experience, failing to integrate with AI agents may mean your app will no longer be part of the new way users interact with digital services.
But this shift also creates significant opportunities.
Companies that start preparing early can gain a new type of advantage – distribution advantage within the AI ecosystem. When users express an intent, AI assistants will look for services that can complete the requested action.
In the future, success will not only depend on having your app installed on a user’s smartphone. It will depend on becoming the app that AI chooses first when a user expresses a need.
That is why preparing for AI agents is not simply about updating a mobile application. It is a strategic decision about whether your product will remain part of the next generation of user experiences – or whether competitors who prepare earlier will take that position.
What It Actually Takes to Implement This
Making an app ready for AI agents is not simply about adding a new feature or connecting another API. The first step is understanding which app capabilities actually make sense to expose to AI. Not every user action needs to be available through an assistant – the focus should be on the scenarios that solve real user needs and create additional value.
Once those capabilities are identified, the technical work begins. Developers need to define available functions, prepare the required schemas and integrations, and test how reliably AI agents can interact with the application.
The scope of work largely depends on the current state of the product. Modern applications with a well-structured architecture may adapt faster, while projects with outdated codebases and significant technical debt may require preliminary modernization.
That is why preparing for AI agents is not only about adopting new technologies. It starts with understanding whether the foundation of your application is ready for the next stage of digital experiences.
How to Prepare Your App – A Practical Starting Point
Preparing your app for AI agents starts not with technology, but with the right strategy. Companies can approach this transition through several practical steps:
- Audit your app capabilities
Identify which user actions actually make sense to expose to AI assistants. Focus on the features that are used most frequently and provide the greatest value.
- Assess your codebase readiness
Evaluate whether your current architecture can support new AI integrations. If the app relies on
- Implement and test the integration
The approach will differ between Android and iOS, as both platforms are at different stages of AI integration development. It is important to test not only technical functionality but also how effectively AI agents interact with the app.
- Keep track of technology updates
AI tools and APIs are evolving rapidly. Regularly monitoring platform updates will help you adapt your app to new capabilities and maintain a competitive advantage.
Why Partner With SCAND for This
Preparing an app for the AI agent era requires more than adding new integrations. In many cases, the first step is understanding the current state of the product, identifying architectural limitations, and creating a reliable foundation for future improvements.
SCAND helps companies navigate this transition by combining expertise in mobile development, AI solutions, and legacy modernization. For businesses with older applications, the journey often starts with improving existing codebases, reducing technical debt, and making the product ready for new capabilities.
With experience building and maintaining mobile solutions across both Android and iOS, SCAND understands the differences between platform ecosystems and can help companies choose the right approach for each one.
As AI-driven app experiences are still emerging, working with technologies such as App Intents and AppFunctions requires the ability to explore new approaches and adapt quickly. SCAND helps businesses prepare their applications for this next stage of mobile evolution, providing expertise in areas such as app intents development services and becoming an app functions development company for organizations looking to make their products AI-agent-ready.
The companies that prepare early will be better positioned to take advantage of new AI-powered user experiences – and SCAND can help them build that foundation.
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