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Apple Uses AI to Boost App Store Discoverability

Posted about 2 months ago by Anonymous

Apple is revolutionizing app discovery through artificial intelligence, announcing new AI-powered App Store Tags at WWDC 2025. This innovative approach aims to help users find precisely what they’re looking for while giving developers better visibility.

How AI-Powered Tags Work

Apple’s implementation leverages large language models (LLMs) to analyze multiple data points about each app, including:

  • Metadata
  • App Store descriptions
  • Category information
  • Screenshot content

After AI generates these descriptive tags, Apple’s team conducts a human review process before they go live. This hybrid approach ensures both algorithmic efficiency and human oversight.

Developer Control and User Benefits

A key feature of the system is developer control. Through App Store Connect, creators can:

  • View suggested tags
  • Remove unwanted classifications
  • Monitor discovery metrics

For users, tapping a tag directs them to collections of apps sharing similar features—greatly enhancing discoverability beyond basic category browsing.

Enhanced App Store Features

Beyond the AI tagging system, Apple revealed several other upgrades coming to the App Store:

Custom Product Pages

Developers can now create tailored landing pages that activate when users search for specific keywords.

Improved App “Nutrition Labels”

The expanded transparency system now includes:

  • More detailed age ratings (now with five ranges)
  • Clearer data usage information

Extended Offer Codes

Apple now supports promotional codes across more subscription types, including consumable and non-renewing options.

The Future of AI in App Discovery

This marks Apple’s latest application of AI for app discovery, following their implementation of AI-generated review summaries. The tech giant continues to refine how artificial intelligence can bridge the gap between developer offerings and user needs while maintaining its commitment to privacy and quality control.