This AI-102 practice question tests your understanding of plan and manage an azure ai solution. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 team uses Azure AI Foundry to deploy a custom chat model. The model must meet compliance by explaining its reasoning and citing sources. Which feature should you enable?
Fine-tuning with domain-specific data
Why wrong: Fine-tuning improves accuracy but does not guarantee citations.
Content filtering
Why wrong: Content filtering blocks harmful content but does not provide citations.
Groundedness detection with citation
Groundedness detection ensures the model cites sources for compliance.
Prompt engineering
Why wrong: Prompt engineering guides behavior but does not enforce source citation.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Groundedness detection with citation
Groundedness detection with citation is the correct feature because it directly addresses the compliance requirement for the model to explain its reasoning and cite sources. This feature, available in Azure AI Foundry, evaluates the model's responses against the provided grounding documents and automatically generates citations, ensuring that the output is factually supported and traceable.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Fine-tuning with domain-specific data
Why it's wrong here
Fine-tuning improves accuracy but does not guarantee citations.
Content filtering
Why it's wrong here
Content filtering blocks harmful content but does not provide citations.
Groundedness detection with citation
Why this is correct
Groundedness detection ensures the model cites sources for compliance.
Related concept
Read the scenario before looking for a memorised answer.
Prompt engineering
Why it's wrong here
Prompt engineering guides behavior but does not enforce source citation.
Common exam traps
The trap here is that candidates may confuse content filtering (which blocks unsafe content) with groundedness detection (which ensures factual accuracy and source attribution), leading them to choose option B when the question specifically asks for reasoning and citation capabilities.
Detailed technical explanation
Groundedness detection works by comparing the model's generated text against a set of grounding documents (e.g., retrieved from Azure AI Search) using semantic similarity and entailment algorithms. When a claim is not supported by the grounding data, the system can flag it as ungrounded, and the citation feature appends source references (e.g., document IDs or page numbers) directly in the response. In a real-world scenario, a healthcare chatbot using this feature would cite specific medical guidelines for each recommendation, ensuring auditability and regulatory compliance.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
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..
The correct answer is: Groundedness detection with citation — Groundedness detection with citation is the correct feature because it directly addresses the compliance requirement for the model to explain its reasoning and cite sources. This feature, available in Azure AI Foundry, evaluates the model's responses against the provided grounding documents and automatically generates citations, ensuring that the output is factually supported and traceable.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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