In the race to deploy large language models and generative AI across global markets, many companies assume that “English model → translate it” is sufficient. But if you’re an American executive preparing for expansion into Asia, Europe, the Middle East, or Africa, that assumption could be your biggest blind spot. In those regions, language isn’t just a packaging detail: it’s culture, norms, values, and business logic all wrapped into one. If your AI doesn’t code-switch, it won’t just underperform; it may misinterpret, misalign, or mis-serve your new market.

The multilingual and cultural gap in LLMs

Most of the major models are still trained predominantly on English-language corpora, and that creates a double disadvantage when deployed in other languages. For example, a study found that n

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