AI vs. Human Translation: What's Best for App Store Metadata?

The Translation Landscape Has Changed

Five years ago, this wasn't even a question. Machine translation was obviously inferior for anything customer-facing. Today? The gap has narrowed dramatically—and in some cases, AI has distinct advantages.

Let's break down when each approach makes sense for App Store metadata.

Understanding Modern AI Translation

Today's AI translation isn't the word-replacement systems of the past. Large language models understand context, tone, and intent. They can:

• Maintain brand voice across languages
• Adapt idioms rather than translate them literally
• Optimize for character limits proactively
• Understand app-specific terminology

This is fundamentally different from "translate this text." It's "localize this app marketing content for the Japanese market."

Where AI Excels

Speed and Consistency

AI can localize your metadata to 40 languages in minutes. A human translator might take days or weeks for the same scope. For indie developers iterating quickly, this matters.

Consistency is another strength. AI applies the same style and terminology across all content. No variation between translators working on different fields.

Cost Efficiency

Professional translation costs $0.10-0.25 per word. A full App Store description (let's say 500 words) across 40 languages: $2,000-5,000 minimum.

AI localization costs a fraction of this. For indie developers, this makes comprehensive localization financially viable.

ASO Optimization

Here's where it gets interesting. AI can be specifically trained on App Store optimization principles. It's not just translating—it's creating market-appropriate content optimized for discoverability.

Human translators are experts in language, but not necessarily in ASO. AI can do both simultaneously.

Where Human Translation Wins

Cultural Nuance

Despite advances, AI can miss cultural subtleties. A phrase that's perfectly fine in one culture might be awkward or inappropriate in another.

For markets critical to your business, having native speakers review AI output adds confidence.

Brand Voice Perfection

If you have a very specific, nuanced brand voice, humans can capture it better. AI is good at "professional" or "casual" but might struggle with your exact tone.

Legal and Regulated Content

Privacy policies, terms of service, and any legally-binding text should involve human review. The stakes are too high for potential AI errors.

The Hybrid Approach

The most practical approach for most indie developers:

• **Use AI for initial localization** - Get all 40 languages done quickly
• **Human review for top markets** - Have native speakers check your 3-5 most important markets
• **Iterate based on data** - Let performance guide where to invest in refinement

This gives you broad coverage immediately while ensuring quality where it matters most.

Quality Indicators to Watch

How do you know if your AI translations are working?

• **Conversion rates by locale** - Are localized markets converting?
• **Negative reviews mentioning translation** - Users will complain if text is awkward
• **Keyword ranking in target markets** - Is your ASO actually working?

If you're seeing good metrics, the translations are probably fine. If a specific market underperforms, that's where human review adds value.

The Practical Reality

For most indie developers, here's the truth:

• You probably can't afford professional translation for 40 languages
• English-only means you're invisible in most markets
• AI localization gets you 90% of the way there
• That 90% is infinitely better than 0%

Perfect is the enemy of good. AI-localized metadata in 40 languages will outperform perfect English-only metadata every time.

Making the Decision

Use AI when:

• Budget is limited
• Speed matters
• You're localizing many languages
• You can iterate based on performance

Add human review when:

• A market is strategically critical
• Your brand voice is highly specific
• You're seeing issues in performance data
• Content has legal implications

The future isn't AI vs. human—it's AI augmented by human expertise where it matters most.