AI-102 Implement generative AI solutions Practice Question
Your organization is deploying a generative AI chatbot using Azure OpenAI Service. The chatbot must answer questions based on internal documents stored in Azure Blob Storage. You need to implement a retrieval-augmented generation (RAG) solution. Which THREE components are required? (Select THREE.)
⚠ Common exam trap
Many exam-takers confuse optional preprocessing components (like Azure Functions) or auxiliary storage (like Azure SQL Database) as mandatory, when the three essential pillars are the search index, the embedding model, and the Azure OpenAI On Your Data integration that ties retrieval to generation.
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
✓
Azure AI Search index
Azure AI Search is the core indexing and retrieval engine in a RAG solution. It ingests documents from Azure Blob Storage, creates a searchable index, and enables vector or hybrid search to retrieve relevant chunks. The chatbot then uses these retrieved chunks as context for the Azure OpenAI model to generate grounded answers.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Functions for preprocessing
Why it's wrong here
Not a required component; can be done by other means.
- ✓
Azure AI Search index
Why this is correct
Stores embeddings and enables vector search.
- ✓
Azure OpenAI On Your Data configuration
Why this is correct
Orchestrates retrieval and generation with the model.
- ✗
Azure SQL Database for metadata
Why it's wrong here
Metadata can be stored in Azure AI Search; SQL is not required.
- ✓
Embedding model deployment in Azure OpenAI
Why this is correct
Generates embeddings for documents and queries.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
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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.