- A
Use a custom model fine-tuned on the knowledge base and disable content filtering.
Why wrong: Fine-tuning does not guarantee adherence to a specific knowledge base and disabling filtering is risky.
- B
Use a system message that says 'If you don't know, say you don't know' and rely on the model's training.
Why wrong: The model may still generate incorrect information despite the instruction.
- C
Use 'use your own data' feature with strict content filtering and set the model to only respond based on retrieved documents.
This ensures responses are grounded in the provided data.
- D
Use prompt engineering with a system message that instructs the model to only answer from the knowledge base, with no additional filtering.
Why wrong: Prompt engineering is not sufficient to prevent hallucinations.
Quick Answer
The correct answer is to use the 'use your own data' feature with strict content filtering and set the model to only respond based on retrieved documents. This configuration directly addresses the need for grounding responses with retrieved documents in Azure OpenAI, as it forces the model to anchor every answer exclusively to the provided knowledge base, preventing hallucination. Strict content filtering acts as a safety net to block any unverified output, while the explicit setting ensures the agent will state when it lacks a matching document, rather than guessing. On the AI-102 exam, this scenario tests your understanding of how to implement Retrieval Augmented Generation (RAG) patterns within Azure OpenAI, often appearing as a question about controlling model behavior for enterprise compliance. A common trap is confusing content filtering with response grounding—filtering blocks harmful content, but grounding restricts the source of truth. Remember the mnemonic: "Ground first, filter second" to prioritize data source restriction over content moderation.
AI-102 Implement agentic AI solutions Practice Question
This AI-102 practice question tests your understanding of implement agentic ai solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is using Azure OpenAI Service to power a customer support agent. The agent sometimes generates incorrect information when it cannot find an answer in the knowledge base. The team wants to ensure the agent only responds using information from the knowledge base and explicitly states when it does not know the answer. Which configuration should the team use?
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
Use 'use your own data' feature with strict content filtering and set the model to only respond based on retrieved documents.
Option C is correct because the 'use your own data' feature in Azure OpenAI Service allows you to restrict the model to answer only from the retrieved documents, ensuring responses are grounded in the knowledge base. Strict content filtering further prevents the model from generating unverified information, and the explicit setting to respond based solely on retrieved documents directly addresses the requirement to state when it does not know the answer.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a custom model fine-tuned on the knowledge base and disable content filtering.
Why it's wrong here
Fine-tuning does not guarantee adherence to a specific knowledge base and disabling filtering is risky.
- ✗
Use a system message that says 'If you don't know, say you don't know' and rely on the model's training.
Why it's wrong here
The model may still generate incorrect information despite the instruction.
- ✓
Use 'use your own data' feature with strict content filtering and set the model to only respond based on retrieved documents.
Why this is correct
This ensures responses are grounded in the provided data.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use prompt engineering with a system message that instructs the model to only answer from the knowledge base, with no additional filtering.
Why it's wrong here
Prompt engineering is not sufficient to prevent hallucinations.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse prompt engineering (Option D) with a reliable grounding mechanism, not realizing that without a retrieval-augmented generation (RAG) architecture and strict content filtering, the model can still hallucinate even when instructed otherwise.
Detailed technical explanation
How to think about this question
The 'use your own data' feature in Azure OpenAI Service implements a retrieval-augmented generation (RAG) pattern, where the model's response is constrained to the context of documents retrieved from a configured data source (e.g., Azure Cognitive Search). Under the hood, the system uses a strict 'grounding' parameter that forces the model to only generate answers based on the provided document chunks, and if no relevant document is found, the model is configured to respond with a default 'I don't know' message. This is fundamentally different from prompt engineering because it operates at the API level, using a 'strictness' setting that controls how closely the model must adhere to the retrieved content, with a value of 5 (on a scale of 1-5) ensuring the model does not generate information outside the retrieved documents.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Implement agentic AI solutions — study guide chapter
Learn the concepts, then practise the questions
- →
Implement agentic AI solutions practice questions
Targeted practice on this topic area only
- →
All AI-102 questions
988 questions across all exam domains
- →
Microsoft Azure AI Engineer Associate AI-102 study guide
Full concept coverage aligned to exam objectives
- →
AI-102 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related AI-102 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Implement an agentic solution practice questions
Practise AI-102 questions linked to Implement an agentic solution.
Implement computer vision solutions practice questions
Practise AI-102 questions linked to Implement computer vision solutions.
Implement knowledge mining and information extraction solutions practice questions
Practise AI-102 questions linked to Implement knowledge mining and information extraction solutions.
Implement image and video processing solutions practice questions
Practise AI-102 questions linked to Implement image and video processing solutions.
Implement natural language processing solutions practice questions
Practise AI-102 questions linked to Implement natural language processing solutions.
Implement generative AI solutions practice questions
Practise AI-102 questions linked to Implement generative AI solutions.
Implement agentic AI solutions practice questions
Practise AI-102 questions linked to Implement agentic AI solutions.
Implement knowledge mining and document intelligence solutions practice questions
Practise AI-102 questions linked to Implement knowledge mining and document intelligence solutions.
Plan and manage an Azure AI solution practice questions
Practise AI-102 questions linked to Plan and manage an Azure AI solution.
Implement content moderation solutions practice questions
Practise AI-102 questions linked to Implement content moderation solutions.
AI-102 fundamentals practice questions
Practise AI-102 questions linked to AI-102 fundamentals.
AI-102 scenario practice questions
Practise AI-102 questions linked to AI-102 scenario.
Practice this exam
Start a free AI-102 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this AI-102 question test?
Implement agentic AI solutions — This question tests Implement agentic AI solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use 'use your own data' feature with strict content filtering and set the model to only respond based on retrieved documents. — Option C is correct because the 'use your own data' feature in Azure OpenAI Service allows you to restrict the model to answer only from the retrieved documents, ensuring responses are grounded in the knowledge base. Strict content filtering further prevents the model from generating unverified information, and the explicit setting to respond based solely on retrieved documents directly addresses the requirement to state when it does not know the answer.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more ways this is tested on AI-102
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company is building an agent that uses Azure OpenAI to answer questions from a large document library. The agent must use a Retrieval Augmented Generation (RAG) pattern. Which TWO actions should the team take to implement RAG effectively?
medium- A.Ensure the model is large enough to memorize the entire document library.
- B.Fine-tune the Azure OpenAI model on the document library.
- ✓ C.Index the documents into a vector database like Azure Cognitive Search.
- D.Train a custom language model from scratch.
- ✓ E.Use a retrieval step to fetch relevant document chunks before generating a response.
Why C: Option C is correct because indexing documents into a vector database like Azure Cognitive Search enables efficient similarity search over embeddings, which is the retrieval foundation of RAG. This allows the system to quickly find the most relevant document chunks based on semantic meaning, rather than relying on the model to memorize or be fine-tuned on the entire library.
Last reviewed: Jun 11, 2026
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.