Does Language Matter in GEO? How English, German, and Niche Languages Affect AI Visibility
In Generative Engine Optimization (GEO), our aim is to be cited or summarized by AI systems like ChatGPT, Perplexity, Gemini, or Claude. But one key factor often flies under the radar:
👉 The language in which you write.
This article breaks down:
📘 Why English is dominant in GEO
🇩🇪 How other mainstream languages (e.g. German) fare
🌍 The challenges for niche or regional languages
🛠️ Practical multilingual strategies for GEO
🔮 What the future holds for language diversity in AI
Why Language Choice Matters in GEO
Most generative AI models are trained on multilingual corpora — but the distribution is not equal.
According to OpenAI and other research groups:
English makes up more than 50% of the training data for GPT-4 and Claude.
Even “multilingual” models are English-first by design.
Most user prompts and responses happen in English.
This means content written in English is more likely to be read, parsed, and cited by AI systems.
What About German and Other Major Languages?
German is one of the top 10 languages online, and LLMs like Gemini, Claude, and ChatGPT can handle German queries quite well. But when it comes to citation and visibility, German content is still at a disadvantage:
LLMs default to English for both queries and responses unless the user specifies otherwise.
Even when German content is available, English sources may be cited preferentially.
Perplexity, for example, often summarizes German sources in English, unless set to a German-language interface.
What Happens with Niche or Smaller Languages?
Languages like Dutch, Vietnamese, Czech, or Greek face a steeper challenge:
They represent a tiny fraction of LLM training data (less than 1–2%).
AI systems often skip over them or translate them into English before surfacing content.
Your article in Estonian might be brilliant — but a similar English piece will likely be cited instead.
Unless your content is translated or summarized in English, it may never appear in generative answers.
When and Why to Use English — Even If It’s Not Your Native Language
Here’s the hard truth:
If you want to be cited by ChatGPT, Perplexity, or Claude — you need some content in English.
That doesn’t mean abandoning your native language entirely, but it does mean adapting your strategy:
✅ Write your best content in English
✅ Translate key insights, summaries, or conclusions into English
✅ Use clear titles and structured layouts that LLMs can parse
Even a 500-word English version or summary can make a difference.
GEO Strategy for Multilingual Creators
| Tactic | Purpose |
|---|---|
| Write blog posts in English | Maximize citation and AI visibility |
| Include English summaries on local-language pages | Help LLMs parse and quote your work |
| Use metadata and titles in English | Improves LLM detection of key points |
| Keep native-language content for cultural/SEO relevance | Serves local readers and boosts SEO |
In other words:
👉 Use English for GEO.
👉 Use your native language for SEO and authenticity.
Will GEO Become More Multilingual in the Future?
LLMs are improving fast, and tools like Gemini 1.5 and GPT-5 are expected to handle dozens of languages fluently.
But fluency is not the same as visibility.
Models will likely continue to prefer citing English sources for two reasons:
Training bias — more English = more confidence in citing
User behavior — most prompts are still written in English
So while you may eventually see better multilingual coverage, the power law of English dominance will persist.
Key Takeaway
If you want generative AI to cite your work, write in English — or at least include an English summary.
Smaller languages aren’t ignored, but they’re far less likely to be surfaced.
GEO is about clarity, structure, authority — and yes, language hierarchy.
📚 Further Reading
GPT‑4 Technical Report (by OpenAI, 2024), direct link to the pdf
The State of Multilingual AI (by Sebastian Ruder, 2022)
Pre-translation vs. direct inference in multilingual LLM applications (Google Research, 2024)
