We recently took part in a webinar with AppTweak and Reddit exploring the future of app discovery and the evolving age of AI.
The session brought together perspectives from across the ecosystem, with Igor Blinov, AI Innovation & ASO Director, Yodel Mobile, joining Ryan Angerami, Global Head of App Developer, Reddit and Simon Thillay, Head of ASO Strategy & Market Insights, AppTweak, to unpack how platforms like ChatGPT and LLM-powered search are reshaping how users find and choose apps.
What followed was a practical, candid discussion on what’s actually changing, what remains true, and how app marketers can start adapting today.
The future of app discovery is moving up stream
The most important shift is where intent is formed.
Historically, intent started inside the App Store. Now, it increasingly begins outside of it.
Users are turning to AI assistants to articulate what they need:
- “What’s the best budgeting app for students?”
- “What running app should I use as a beginner?”
- “What’s the best dating app for serious relationships?”
Instead of browsing categories or scrolling search results, users are asking for recommendations based on their specific context.
This changes everything.
AI models are not thinking in keywords. They are matching problems to solutions.
That means visibility is no longer just about ranking for “budgeting app”, it’s about being relevant to the use case behind that search.
AI discovery is not replacing ASO, it’s expanding it
It’s important to be clear, the App Store still matters.
Users are still landing on your product page. Conversion still happens there. ASO is still a critical lever.
But AI has introduced a new discovery layer.
Instead of:
Search > App Store > Download
We are now seeing:
Intent > AI > Recommendation > App Store > Download
This has two key implications:
- ASO metrics are no longer the only signals of discovery
- Positioning and context now influence visibility upstream
AI does not simply replicate App Store rankings. It builds what was described in the session as a “defensible answer”, based on multiple sources and perspectives, not just popularity.
Reddit and community signals are shaping recommendations
One of the most important sources influencing AI outputs today is community discussion.
Reddit, in particular, is heavily cited by AI models when generating recommendations.
Why?
Because it reflects:
- Real user experiences
- Nuanced use cases
- Differing opinions and debates
For example, a search for “best running app” might return well-known platforms like Strava.
But when context is added, “best app for beginner runners”, community discussions surface entirely different recommendations.
Smaller apps can win here.
Not because they have the biggest budgets, but because they are the best fit for a specific problem.
This is a critical shift away from pure popularity.
Visibility is now probabilistic, not positional
Another key takeaway is how AI presents results.
In traditional search and ASO, ranking is everything. Position 1 vs position 5 has a clear impact.
With AI, the dynamic is different.
You either appear in the recommendation set, or you don’t.
There is less emphasis on strict ranking, and more on:
- Relevance to the user’s intent
- Consistency of your positioning
- Breadth of your contextual coverage
This creates a new competitive dynamic.
You are not just competing for keywords, you are competing for problem ownership.
What actually influences AI recommendations?
While the space is still evolving, several signals are already emerging as important:
1. Intent coverage
AI models map problems to solutions, not keywords.
Apps that clearly articulate:
- What problem they solve
- Who they solve it for
- In what context
…are more likely to be surfaced.
2. Semantic depth
It’s not enough to say “budgeting app”.
You need to cover:
- Student budgeting
- Monthly planning
- Expense tracking
- Financial goals
This broader semantic coverage helps AI understand where your app fits.
3. Cross-channel consistency
AI models are trained across multiple sources.
That means your positioning needs to be aligned across:
- App Store listings
- Website content
- Social channels
- Community discussions
Consistency builds credibility.
4. Real conversation and credibility
AI prioritises sources that demonstrate:
- Authentic discussion
- Multiple viewpoints
- Evidence and reasoning
This is why community platforms like Reddit are so influential.
5. Brand signals (indirectly)
Traditional metrics still matter, but indirectly.
Downloads, reviews, and brand awareness contribute to:
- Visibility across the web
- Volume of discussion
- Overall credibility
But they are no longer the sole drivers.
The App Store still plays a critical role
Despite all of this, the App Store remains the point of conversion.
Users still validate recommendations there.
That means:
- Your messaging must align with AI-driven expectations
- Your listing must reinforce the problem-solution fit
- Your conversion experience must deliver on the promise
There is also early evidence that App Store metadata can influence AI visibility.
In one example shared during the webinar, updating long-form descriptions to better reflect user intent and semantic coverage led to increased traffic from AI-driven sources.
This suggests ASO is evolving, not diminishing.
What should app marketers do now?
While the space is still developing, there are clear actions brands can take today.
1. Understand how your category is surfaced
Test prompts across different AI platforms.
Look at:
- Which apps are recommended
- Which sources are cited
- How answers are structured
You cannot optimise what you don’t understand.
2. Reframe your positioning around problems
Move beyond feature-led messaging.
Focus on:
- The user problem
- The context of use
- The outcome delivered
3. Align your ecosystem
Ensure consistency across:
- Website
- App Store
- Content
- Social
AI is connecting these dots.
4. Engage with communities
Understand where your audience is talking.
Listen first, then contribute:
- Address feedback
- Provide value
- Be authentic
This is not about promotion, it’s about participation.
5. Start testing and learning
There is no fixed playbook yet.
Early movers will benefit from:
- Building internal knowledge
- Testing frameworks
- Identifying patterns
The opportunity ahead
AI-driven discovery is still evolving, but the direction is clear. As discussed by Igor, Ryan and Simon, success in this new landscape will come from understanding intent more deeply, building credibility across channels, and aligning your entire digital presence around the problems your app solves. For app marketers, this is not a future consideration, it’s already happening, and the opportunity now is to get ahead of it.
If you’re looking to understand how your app is showing up across AI platforms and where the opportunities lie, get in touch with our team.
