How to set up Zendesk AI agent for multilingual support

Supporting customers in their native language is not just nice to have anymore. Research shows that 75% of consumers are more likely to purchase from brands that offer customer care in their language. For global businesses, this means multilingual support has become a competitive necessity.

Zendesk AI agents offer built-in multilingual capabilities that can help you scale support across dozens of languages without proportionally increasing headcount. This guide walks you through configuring these features step by step, from basic language setup to advanced customization.

Whether you're just getting started with AI-powered support or looking to optimize an existing setup, you'll learn how to configure language detection, enable automatic translation, and set up custom translations for brand-specific terminology. We'll also cover when you might want to consider alternative approaches for teams with unique multilingual requirements.

What you'll need to get started

Before diving into configuration, make sure you have the following in place:

• Zendesk account with appropriate plan. AI agents require Suite Team or higher, or Support Team with the Help Center add-on. Advanced AI agent features require additional add-ons.
• Admin Center access. You'll need administrator permissions to configure AI agent settings.
• List of target languages. Know which languages your customers actually use. Check your existing ticket data to identify the highest-volume languages.
• Understanding of your primary channels. The setup differs slightly depending on whether you primarily use messaging, email, or both.

How Zendesk AI agent handles languages

Understanding how language detection works will help you configure your AI agent more effectively. Zendesk uses different detection methods depending on the channel:

Messaging channels (chat, web widget, social messaging): The AI detects the customer's language from their first message automatically. This works for 80+ languages at native fluency according to Zendesk's documentation.

Email and API channels: Language is determined by the requester's profile language setting rather than message content analysis.

Web widget: Uses the customer's browser language settings as a fallback when message detection is inconclusive.

Once detected, the AI agent responds in the customer's language if that language is supported by the AI model and activated in your settings. If the language cannot be detected or is not supported, the AI falls back to your configured default language.

Important distinction: There's a difference between languages Zendesk supports as a platform (40+ for the help center) and languages the AI model supports for generative replies (80+). Make sure the languages you need are covered by both.

Step 1: Configure your default language

Your default language serves as the fallback when the AI cannot detect a customer's language or when the detected language is not supported. Here's how to set it up:

1. Navigate to Admin Center > AI > AI agents in your Zendesk dashboard.
2. Select the AI agent you want to configure and open the Settings tab.
3. Expand the Language section.
4. Choose your default language from the dropdown. This should typically match your primary market or the language most of your agents speak.
5. Click Save changes.

The default language also determines the language used for your AI agent's persona and system messages. If you support multiple markets equally, choose the one where you've got the most established support processes.

Step 2: Enable automatic translation

Automatic translation allows your AI agent to respond in languages other than your default without requiring pre-translated content. This is ideal for handling common questions across many languages quickly.

When to use automatic translation: For standard responses, FAQ-style answers, and situations where speed matters more than perfect brand voice localization.

When to use custom translations instead: For brand-specific terminology, product names, or when you need precise control over tone and phrasing.

To enable automatic translation:

1. In your AI agent settings, go to Language > Translate messages.
2. Toggle automatic translation on.
3. Select which languages you want to enable for translation. You can enable all supported languages or just specific ones based on your customer base.
4. Review what gets translated: standard AI agent responses, answer flows, and system messages.
5. Click Publish changes to make them live.

Note: Automatic translation uses machine translation, so it might not capture nuances of your brand voice. Test responses in your key languages before rolling out to customers.

Step 3: Set up custom translations (optional)

Custom translations give you precise control over how your AI agent communicates in each language. This is particularly important for:

• Brand terminology and product names
• Specific tone requirements (formal vs. casual)
• Industry-specific jargon
• Pronouns and gendered language

To create custom translations:

1. Go to Admin Center > AI > AI agents > Language > Custom translations.
2. Select the message or response you want to customize.
3. Add translations for each target language.
4. Save and publish your changes.

Best practices for maintaining consistency:

• Create a glossary of key terms and their approved translations
• Document your brand voice guidelines for each language
• Regularly review and update translations based on customer feedback
• Consider regional variants (e.g., Spanish for Spain vs. Latin America)

Step 4: Configure advanced language settings (Advanced AI agents)

If you're using Advanced AI agents (available as an add-on), you'll get additional language configuration options:

Adding supported languages beyond the default: Advanced AI agents allow you to configure multiple active languages with more granular control over which responses use which languages.

Activating languages for specific replies: You can set language preferences at the reply level, useful for teams that handle different types of inquiries in different languages.

Setting locale info for CRM integration: Advanced agents can pass language and locale information to connected CRM systems for better customer context.

Language-based routing: Configure conditional flows that route conversations based on detected language, sending certain languages to specialized agent groups.

To access these settings, you'll need the Advanced AI agents add-on. Contact Zendesk sales for pricing and availability.

Testing your multilingual AI agent

Before going live, thoroughly test your multilingual setup:

1. Use the built-in testing interface. Zendesk provides a test environment where you can simulate conversations in different languages.

2. Test your highest-volume languages first. Focus on the languages that represent 80% of your customer base.

3. Verify translation quality. Check that automatic translations make sense and that custom translations appear correctly.

4. Check escalation paths. Ensure that when the AI cannot handle a request, it escalates properly to human agents who speak the appropriate language.

5. Test edge cases. Try mixed-language conversations, unsupported languages, and unusual character sets.

Best practices for multilingual AI support

Based on what we've seen work for teams scaling multilingual support:

• Start with your highest-volume languages. Get these working well before expanding to niche languages.

• Maintain a glossary of brand terms. Consistent terminology across languages builds trust and reduces confusion.

• Regularly review AI responses. Set up a process to spot-check responses in each language weekly or monthly.

• Set up proper escalation. Make sure complex issues reach agents who speak the customer's language.

• Consider regional variants. Spanish for Spain differs from Spanish for Mexico. Portuguese for Brazil differs from Portuguese for Portugal. Decide whether you need separate handling for these variants.

Alternative approach: AI-powered multilingual support without manual translation

While Zendesk's approach works well for many teams, maintaining translations at scale can become challenging. Each new language requires ongoing effort to keep content current, and automatic translation doesn't always capture brand voice accurately.

This is where AI-native solutions take a different approach. At eesel AI, we handle multilingual support by leveraging the underlying language capabilities of modern AI models. Instead of requiring you to pre-translate content or manage dynamic content strings, our AI agent generates responses directly in the customer's detected language. You can also explore our AI Copilot for teams that want AI assistance without full automation.

How it works: When a customer sends a message in German, the AI understands the intent, retrieves relevant information from your knowledge base (regardless of what language it is stored in), and generates a response in German. No manual translation required.

When this approach makes sense:

• You support many languages (10+) and maintaining translations would be impractical
• Your team lacks dedicated localization resources
• You need conversational, context-aware responses rather than templated replies
• You want to minimize setup time while still offering multilingual support

eesel AI integrates with Zendesk alongside your existing setup, so you can use both approaches for different types of inquiries or gradually transition as your needs evolve. Learn more about eesel AI pricing and how it compares to traditional per-agent pricing models.

Choosing the right approach for your team

The best multilingual AI setup depends on your specific situation. Here's a simple framework:

Choose Zendesk native AI agents if:

• You have 2-5 primary languages with established translation workflows
• Your team includes native speakers who can review and customize translations
• You need tight integration with Zendesk's existing automation and routing
• You prefer predictable, templated responses over generative AI

Consider AI-native alternatives like eesel AI if:

• You support many languages and translation maintenance is unsustainable
• You want minimal setup overhead
• You need conversational responses that adapt to context
• You're open to a hybrid approach using both tools

Hybrid approaches work well when:

• You use Zendesk AI for common, templated responses in major languages
• You use an AI-native solution for complex inquiries or less common languages
• You're transitioning from one approach to the other gradually