AI-103 Implement Generative AI And Agentic Solutions Practice Question
You are building an agent in Azure AI Foundry using a prompt flow. You need to ensure that the agent only uses company-approved documentation for its responses. Which feature should you implement to meet this requirement?
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
✓
Configure Grounding with data
Grounding with data is the primary mechanism in Azure AI Foundry to limit an agent's knowledge to specific data sources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable prompt tuning
Why it's wrong here
Prompt tuning optimizes the model performance but does not restrict the knowledge base.
- ✗
Implement system message constraints
Why it's wrong here
System messages set behavior but are prone to jailbreaking if not backed by grounding data.
- ✓
Configure Grounding with data
Why this is correct
Grounding with data allows you to connect your agent to specific data sources like Azure AI Search to restrict the scope of answers.
- ✗
Deploy a fine-tuned model
Why it's wrong here
Fine-tuning updates model weights but is not the correct approach for dynamic data retrieval.
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.