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AI-103 Implement Generative AI And Agentic Solutions Practice Question

You are developing a RAG solution using Azure AI Search. Users are searching using domain-specific acronyms that are not well-represented in standard embedding models, resulting in poor retrieval scores. What feature should you enable in Azure AI Search to improve keyword matching for exact acronyms?

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

Hybrid search combining vector search and full-text BM25 search

Hybrid search combines vector search (for semantic meaning) with full-text keyword search (BM25 algorithm), ensuring exact acronyms and part numbers are matched reliably.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increasing the embedding dimension size to 3072

    Why it's wrong here

    Larger embedding vectors still struggle with rare acronyms unless keyword matching is utilized.

  • Enabling Azure AI Content Safety filters

    Why it's wrong here

    Content Safety filters moderate harmful content, not search ranking algorithms.

  • Setting the semantic ranker threshold to zero

    Why it's wrong here

    Threshold adjustments filter results but do not improve underlying keyword recall.

  • Hybrid search combining vector search and full-text BM25 search

    Why this is correct

    Hybrid search merges vector embeddings with keyword BM25 scoring, capturing both semantic intent and exact keyword matches like acronyms.

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Microsoft exam blueprint

This AI-103 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-103 exam.