Shipping AI-Built Apps Through Google Play and App Store Review

The pre-submission checklist we run

Before submitting any app to either store, we verify these eight items. It takes about an hour and catches 90% of what would otherwise bounce in review.

1. Privacy policy is specific and reachable

Both stores require a working URL. We host privacy policies on our own infrastructure (not a shortlink service), include a last-updated date, and make sure every data type the app actually touches is named explicitly.

2. Data Safety / App Privacy match behavior

Google Play's Data Safety form and Apple's App Privacy label must accurately reflect what the app does. If the app uses Firebase Analytics, declare it. If it stores content on-device, say so. Inaccurate declarations get apps removed long after publication.

3. Permissions are minimal

Ask only for permissions the app actually needs. Each permission requires a reasonable, user-facing explanation. "Access location to show nearby X" is fine; "Access location" alone is not.

4. Target API level is current

Google Play enforces minimum target API levels annually. Apple enforces iOS SDK versions on first submission. Both lock out older targets — check the current cutoff before building.

5. Age rating is honest

Content rating questionnaires matter. Lying about content rating to avoid restrictions gets apps removed. Err toward accurate-conservative ratings.

6. Ads and IAP are clearly labeled

If the app shows ads, declare it on the store listing. If it offers in-app purchases, use the platform's purchase API, not third-party payment flows (unless you qualify for the reader-app exception).

7. Test accounts and review notes prepared

If the app requires login to demonstrate functionality, create test credentials and put them in the review notes. Save review time; avoid unnecessary rejections.

8. Screenshots match the live app

Store screenshots must depict the actual current build. Marketing-first "aspirational" screenshots get apps rejected.

AI-specific considerations

If your app exposes generative AI features to users:

• Label AI-generated output clearly when it could be mistaken for human content
• Have a clear moderation/abuse policy if users generate prompts
• Log or flag egregious output to prevent your app becoming a platform for policy violations
• For kids or family apps, AI features face extra scrutiny — plan for it

The meta-lesson

Platform review gets more automated every year. Policy bots catch category violations, permission mismatches, and privacy-policy gaps fast. Human reviewers now focus on harder edge cases. Either way: accurate, honest, complete submissions still sail through. Clever submissions get kicked.