AI-103 Implement Generative AI And Agentic Solutions Practice Question
Which TWO factors directly influence the embedding quality and retrieval relevance in an Azure AI Search vector retrieval pipeline? (Choose two.)
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
✓
The choice of embedding model (e.g., text-embedding-3-large vs text-embedding-3-small) and its dimensionality.
Embedding model choice and chunking strategy are primary determinants of vector retrieval quality.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The background color of the source documents in blob storage.
Why it's wrong here
Document display styling has no impact on vector embeddings.
- ✓
The choice of embedding model (e.g., text-embedding-3-large vs text-embedding-3-small) and its dimensionality.
Why this is correct
The embedding model determines how accurately semantic meaning is captured in vector space.
- ✗
The font family used in the original PDF documents.
Why it's wrong here
Text extraction abstracts font styling away before vectorization.
- ✗
The client browser version used by the end user.
Why it's wrong here
Client browser has no bearing on server-side vector indexing and search.
- ✓
The chunking strategy and chunk size used to segment source documents.
Why this is correct
Chunking strategy determines the granularity and contextual coherence of retrieved passages.
About these practice questions
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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.