AI-102 Implement an agentic solution Practice Question
You are designing an agent that uses Azure AI Search as a knowledge store. The agent must handle multiple languages. Which feature should you configure in Azure AI Search to ensure the agent retrieves relevant results for queries in different languages?
⚠ Common exam trap
It's easy for candidates to confuse semantic search (which improves relevance via AI) with language-specific text processing, assuming semantic search alone can handle multilingual queries, but semantic search still relies on the underlying analyzer for tokenization and cannot perform language-specific stemming or stop word removal.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Language analyzers
Language analyzers in Azure AI Search are specifically designed to handle linguistic variations across different languages, such as stemming, stop word removal, and tokenization rules. By configuring the appropriate language analyzer (e.g., 'en.microsoft' for English or 'fr.microsoft' for French) on a searchable field, the agent can retrieve relevant results for queries in multiple languages because the analyzer processes both the indexed content and the query string using the same language-specific rules.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Scoring profiles
Why it's wrong here
Used for custom ranking.
- ✓
Language analyzers
Why this is correct
Handle language-specific text analysis.
- ✗
Semantic search
Why it's wrong here
Improves relevance but not language handling.
- ✗
Synonym maps
Why it's wrong here
Expands query terms.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.