- A
Use Azure OpenAI with function calling to retrieve knowledge base documents, and enable content filtering.
Why wrong: Function calling requires custom code and does not enforce citations automatically.
- B
Use prompt engineering with system messages to restrict knowledge, and enable content filtering.
Why wrong: Prompt engineering is not reliable; the model may still produce ungrounded responses.
- C
Use Azure OpenAI on your data with Azure AI Search as the data source, enable content filtering, and configure the model to use the search index with strict grounding.
Azure OpenAI on your data grounds responses in the knowledge base, content filtering ensures safety, and strict grounding enforces citations.
- D
Fine-tune the GPT-4 model on the knowledge base and deploy with content filtering.
Why wrong: Fine-tuning does not guarantee responses are limited to the knowledge base; it may still hallucinate.
Quick Answer
The correct choice is to use Azure OpenAI on your data with Azure AI Search as the data source, enable content filtering, and configure the model to use the search index with strict grounding. This configuration directly meets all requirements because it grounds the chatbot’s responses exclusively in the indexed knowledge base, preventing reliance on general internet knowledge, while content filtering removes toxic or harmful output, and strict grounding forces the model to cite sources from the search index. On the AI-102 exam, this scenario tests your understanding of RAG with Azure AI Search and content filtering for chatbot solutions, often appearing as a multi-requirement question where distractors suggest using the model’s pre-trained knowledge or omitting citation enforcement. A common trap is assuming that simply connecting Azure AI Search is enough, but you must explicitly enable strict grounding to ensure citations. Memory tip: think “Search, Filter, Ground” — the three pillars for a safe, citation-based RAG chatbot.
AI-102 Plan and manage an Azure AI solution Practice Question
This AI-102 practice question tests your understanding of plan and manage an azure ai solution. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
Your organization deploys an Azure AI Foundry solution for a customer service chatbot. The chatbot uses a large language model (LLM) hosted on Azure OpenAI Service with a GPT-4 model. Requirements: (1) The chatbot must only use information from the company's internal knowledge base, not general internet knowledge. (2) Responses must include citations from the knowledge base. (3) The solution must filter out any toxic or harmful content. (4) The chatbot must be deployed in a secure environment with network isolation. You have an Azure AI Foundry project with a connected Azure OpenAI resource. The knowledge base is stored in Azure AI Search. You need to configure the solution. What should you do?
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 Azure OpenAI on your data with Azure AI Search as the data source, enable content filtering, and configure the model to use the search index with strict grounding.
Option C is correct because it uses Azure OpenAI on your data with Azure AI Search as the data source, which ensures the model only retrieves and generates responses from the indexed knowledge base, meeting the requirement to avoid general internet knowledge. Enabling content filtering satisfies the toxicity requirement, and configuring strict grounding ensures responses include citations from the search index. The secure environment with network isolation is achieved through Azure AI Foundry's managed network capabilities, which are compatible with this configuration.
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 Azure OpenAI with function calling to retrieve knowledge base documents, and enable content filtering.
Why it's wrong here
Function calling requires custom code and does not enforce citations automatically.
- ✗
Use prompt engineering with system messages to restrict knowledge, and enable content filtering.
Why it's wrong here
Prompt engineering is not reliable; the model may still produce ungrounded responses.
- ✓
Use Azure OpenAI on your data with Azure AI Search as the data source, enable content filtering, and configure the model to use the search index with strict grounding.
Why this is correct
Azure OpenAI on your data grounds responses in the knowledge base, content filtering ensures safety, and strict grounding enforces citations.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Fine-tune the GPT-4 model on the knowledge base and deploy with content filtering.
Why it's wrong here
Fine-tuning does not guarantee responses are limited to the knowledge base; it may still hallucinate.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse fine-tuning (Option D) with RAG, not realizing that fine-tuning cannot provide citations and still risks hallucination, while RAG with Azure AI Search directly satisfies the grounding and citation requirements.
Detailed technical explanation
How to think about this question
Azure OpenAI on your data uses a retrieval-augmented generation (RAG) pattern where the model queries Azure AI Search at inference time to retrieve relevant chunks, then generates responses grounded in those chunks. Strict grounding enforces that the model's output is limited to the retrieved content, and citations are automatically appended as metadata from the search index. This approach also supports network isolation by deploying the Azure OpenAI service and AI Search within a managed virtual network, preventing data exfiltration.
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 healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
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.
- →
Plan and manage an Azure AI solution — study guide chapter
Learn the concepts, then practise the questions
- →
Plan and manage an Azure AI solution 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?
Plan and manage an Azure AI solution — This question tests Plan and manage an Azure AI solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Azure OpenAI on your data with Azure AI Search as the data source, enable content filtering, and configure the model to use the search index with strict grounding. — Option C is correct because it uses Azure OpenAI on your data with Azure AI Search as the data source, which ensures the model only retrieves and generates responses from the indexed knowledge base, meeting the requirement to avoid general internet knowledge. Enabling content filtering satisfies the toxicity requirement, and configuring strict grounding ensures responses include citations from the search index. The secure environment with network isolation is achieved through Azure AI Foundry's managed network capabilities, which are compatible with this configuration.
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 →
Last reviewed: Jun 24, 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.