The answer is establishing data governance policies for training data, configuring built-in content filtering, and implementing a process for human oversight of model outputs. These three are required because Azure OpenAI Service’s responsible AI compliance framework, governed by Microsoft’s Responsible AI Standard, mandates that you control the data used to train or fine-tune models to prevent bias, deploy content filters to block harmful outputs like hate speech or violence, and maintain human review loops to catch edge cases the filters miss. On the AI-102 exam, this question tests your understanding of the operational guardrails for generative AI, often appearing as a multi-select scenario where distractors like “enable private endpoint encryption” or “use a custom neural voice” are tempting but irrelevant to responsible AI principles. A common trap is assuming content filtering alone suffices, but Microsoft requires all three pillars: governance, filtering, and oversight. Memory tip: think “Data, Filter, Human” as the three-legged stool of responsible AI compliance.
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.
Which THREE are required when planning to use Azure OpenAI Service for a generative AI application that must comply with responsible AI principles?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement content filters to block harmful outputs.
Option B is correct because Azure OpenAI Service provides built-in content filtering that can block harmful outputs such as hate speech, violence, or self-harm. This is a core requirement for responsible AI compliance, as outlined in Microsoft's Responsible AI Standard, and must be configured to prevent the model from generating unsafe content.
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.
✗
Restrict the model to a maximum of 1000 tokens.
Why it's wrong here
Not a requirement of responsible AI.
✓
Implement content filters to block harmful outputs.
Why this is correct
Required for safety.
Related concept
Read the scenario before looking for a memorised answer.
✓
Design with human-in-the-loop for critical decisions.
Why this is correct
Human oversight is a key responsible AI principle.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable rate limiting to prevent abuse.
Why it's wrong here
Rate limiting is operational, not specifically responsible AI.
✓
Establish data governance policies for training data.
Why this is correct
Ensures data privacy and compliance.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse operational controls (like token limits or rate limiting) with responsible AI requirements, which are specifically about fairness, safety, transparency, and accountability, not performance or security.
Detailed technical explanation
How to think about this question
Content filters in Azure OpenAI Service operate at the API level, using Azure AI Content Safety to classify and block outputs based on severity levels for categories like hate, sexual, violence, and self-harm. These filters can be configured with custom severity thresholds, and they work alongside the model's own safety system messages to provide defense-in-depth. In a real-world scenario, a healthcare chatbot must block any medical advice that could cause harm, making content filters essential for compliance.
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.
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: Implement content filters to block harmful outputs. — Option B is correct because Azure OpenAI Service provides built-in content filtering that can block harmful outputs such as hate speech, violence, or self-harm. This is a core requirement for responsible AI compliance, as outlined in Microsoft's Responsible AI Standard, and must be configured to prevent the model from generating unsafe content.
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.
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Question Discussion
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