Common App Store Rejections for AI-Built Apps and How to Fix Them
By the apprat.io AI Code Engineering Team 9 min read
In short: AI-built apps are most often rejected for thin functionality, crashes, missing demo access, privacy mismatches, account deletion gaps, payment rule violations and incomplete content. Each has a concrete fix, usually a mix of code changes, clearer review notes and accurate metadata.
A rejection message from Apple is rarely a surprise in hindsight. The same handful of causes appear again and again, and AI-built apps have a few typical weak spots on top. This list is organized by what the reviewer sees, so you can compare it with your own rejection text. Guideline numbers and wording change over time, so confirm them on Apple's developer site before you act.
Rejections about the app itself
Minimum functionality (Guideline 4.2)
The app looks like a website in a frame or has very little to do. Fix: add real native value, polish the experience and explain it in the review notes. We cover this in a dedicated guide.
Crashes and bugs (Guideline 2.1, app completeness)
Blank screens, broken buttons, endless spinners, placeholder text, "coming soon" sections. Fix: test the release build on real devices and on a fresh install; remove unfinished features instead of hiding them behind a disabled button; make sure every backend the app needs is live during review.
Demo account missing or not working
The reviewer cannot log in. Fix: provide credentials in App Store Connect, preloaded with realistic data, and ensure two-factor or email verification does not block them. If the app needs hardware or a special environment, explain how to test it.
Rejections about data and privacy
- Privacy labels do not match behavior. A generated project may include analytics, crash reporting or advertising SDKs you did not choose consciously. Fix: inventory every SDK and network call, then answer the questions accordingly.
- Missing privacy policy or unreachable URL. Fix: host a clear, current policy and link it in the app and the listing.
- Unexplained permissions. A camera or location request with a vague purpose string is a common flag. Fix: request only what you need, and write a specific, honest usage description.
- No account deletion. If users can create an account in the app, Apple expects a way to delete it in the app. Fix: build a deletion flow that really removes or anonymizes data.
For European audiences, a broader view is in building a GDPR-compliant mobile app.
Rejections about money and content
- Payments: digital goods or subscriptions sold outside Apple's in-app purchase system, or confusing purchase flows. Fix: review in-app purchase options and align the app with the rules that apply to your product.
- User-generated content: apps with chat, posts or comments are expected to offer reporting, blocking and moderation. Fix: add these tools and describe them in the notes.
- Sign-in options: if the app offers certain third-party logins, Apple may require an equivalent privacy-focused option such as Sign in with Apple. Fix: check the current rule for your case.
- Metadata: screenshots that do not show the real app, misleading descriptions or mentions of other platforms. Fix: use real screens and plain claims. Our assets checklist helps.
A repeatable response process
- Read the whole rejection message and note every guideline cited.
- Reproduce the issue on a real device with a fresh install.
- Fix root causes, not just the symptom the reviewer mentioned; related issues often sit beside it.
- Update review notes with what changed and where to find it.
- Resubmit and, where the message is unclear, ask for clarification through the Resolution Center.
How apprat.io deals with rejections
Our AI coding agents help us implement fixes quickly, such as an account deletion flow or a permission rework, but an AI Code Engineer reads the reviewer's message, decides what the underlying problem is, reviews every change, tests on a real iPhone and writes the response. That human accountability is the difference between guessing and fixing. If your app is stuck in a rejection loop, we offer code audits and rescue for AI-generated apps; book a call for free and bring the message you received.
Prevent it next time
Run a pre-submission review against this list, keep a simple log of past rejections and their fixes, and treat every release as if the reviewer knows nothing about your product. Preparation costs hours; a rejection can cost days. For platform-specific walkthroughs, see publishing a Lovable app to the App Store.
Frequently asked questions
How long does it take to fix a rejection?
It depends on the cause. Metadata and notes can be fixed in a day, while missing features such as account deletion take engineering time, plus the next review cycle.
Should I argue with the reviewer?
Start by fixing the issue and clarifying your notes. If you believe the rejection is a misunderstanding, you can reply in the Resolution Center or use the appeal process, politely and with specifics.
Why do AI-built apps get rejected so often?
Not because of AI itself, but because generated apps often skip store-specific work: native value, privacy accuracy, account deletion, demo access and real-device testing.
Can apprat.io help with an existing rejection?
Yes. Our AI Code Engineers can analyze the message, fix the cause, retest on devices and resubmit.