Why do answers differ between languages?
AI engines answer from the sources available in each language. The English web documents your market densely: directories, review platforms, industry articles. The Arabic web covers the same market far more thinly, so the engine works from fewer, weaker sources when the question arrives in Arabic. It may translate its English knowledge, lean on whatever Arabic pages exist, or default to whichever businesses already have Arabic content.
The result is two different shortlists for the same market. A clinic dominating English answers can be absent in Arabic while a smaller competitor with an Arabic-first website owns that side entirely.
What does this mean for a GCC business?
Your buyers ask in both languages, and they do not split evenly by value. In Saudi Arabia especially, high-intent commercial questions are asked in Arabic every day. If your AI visibility has only ever been checked in English, the checked half may be the smaller half of your market.
Consider a hypothetical example: a dental clinic in Jeddah. Its English answers may surface internationally listed competitors pulled from directory-heavy sources, while its Arabic answers name local players drawn from Arabic media and community discussion. Same city, same service, two different shortlists, and usually only one of them has ever been reviewed by the clinic's team.
Because so few businesses work on their Arabic presence, the Arabic side of AI answers is the least defended ground in most GCC categories. The gap favors whoever moves first, since a competitor's AI mentions get harder to displace once they're established.
Which language should you fix first?
Fix where the gap between opportunity and presence is widest, which for most businesses is Arabic. The work mirrors the English playbook: consistent facts in Arabic across the directories that matter, Arabic reviews that mention specific services, and Arabic pages that answer real buyer questions rather than translated brochure copy. Machine translation of your English site does not close the gap, because the engines already had that option.
Treat the first Arabic sprint like a launch rather than a translation task: pick the ten questions with the most buying intent, publish one strong Arabic answer page for each, and let the directories confirm the same facts.
How do you test both languages properly?
Run the same fixed question set twice, once per language, across ChatGPT, Google AI Overviews, Gemini and Perplexity, and score each language separately. A single blended score hides exactly the imbalance you are trying to find. Track a Brand Mention Rate per language, and compare who wins each side.
Native reading matters here. Scoring the tone and accuracy of an Arabic answer through translation loses the nuance that decides whether a mention actually sells. Every AI Visibility Audit we run tests both languages natively for exactly this reason.