Large language models (LLMs) are inherently multilingual, processing numerous languages, yet their security measures are often designed with an English-first approach, leaving them vulnerable to attacks in other languages. This gap allows adversaries to exploit non-English prompts, code-switching, and translation-based tricks to bypass AI safeguards, leading to potential data leaks and inconsistent policy enforcement. Evidence shows real-world cases where attackers have successfully bypassed AI defenses by using multilingual queries, revealing critical security risks. To mitigate these threats, it's crucial for businesses to implement multilingual security strategies that address these vulnerabilities and ensure consistent protection across all languages. Lakera Guard exemplifies a solution that offers comprehensive AI security for over 100 languages, emphasizing the need for global, multilingual security measures as AI becomes more integrated into business operations.