AI-103 Implement Generative AI And Agentic Solutions Practice Question
When configuring vector embeddings and search indexes in Azure AI Search for RAG, which THREE factors directly impact vector search performance and recall accuracy? (Choose THREE)
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
✓
Embedding model dimension size and consistency with source generation
Embedding model dimensionality, vector similarity metric (e.g., cosine, dot product), and HNSW algorithm index parameters impact search performance and recall.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Embedding model dimension size and consistency with source generation
Why this is correct
Query and document vectors must use the exact same embedding model and dimensionality.
- ✗
Azure App Service CPU architecture (x64 vs ARM)
Why it's wrong here
App Service architecture does not govern Azure AI Search vector indexing mechanics.
- ✓
HNSW (Hierarchical Navigable Small World) algorithm parameters such as m and efSearch
Why this is correct
HNSW index parameters balance search speed and recall accuracy.
- ✓
Choice of vector similarity metric (Cosine, Dot Product, or Euclidean)
Why this is correct
The similarity metric determines how vector proximity is calculated during search.
- ✗
Configuring Azure Front Door DNS CNAME records
Why it's wrong here
DNS records route web traffic, not vector search recall.
About these practice questions
This AI-103 question is part of Courseiva's 510-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.