- A
Use the GPT-4 model with safety prompts
Why wrong: GPT-4 is a text-based model and cannot generate images; safety prompts are not a built-in content filtering mechanism.
- B
Enable content filtering on the DALL-E deployment
Content filtering is a built-in feature of Azure OpenAI that automatically screens for harmful content, including in images generated by DALL-E.
- C
Train a custom image classification model to filter outputs
Why wrong: While possible, this is unnecessary because Azure OpenAI already includes content filtering; training a separate model adds complexity and does not leverage the native safety feature.
- D
Use the Embeddings model to detect inappropriate content
Why wrong: The Embeddings model converts text to numerical vectors for similarity search and does not generate images or filter content.
Quick Answer
The answer is to enable content filtering on the DALL-E deployment. This built-in feature automatically blocks sexually explicit, violent, or otherwise inappropriate images from being generated, ensuring all output is suitable for general audiences without requiring any custom model training or additional data. On the Microsoft Azure AI Fundamentals AI-900 exam, this question tests your understanding of Azure OpenAI’s responsible AI safeguards, specifically the content filtering system that operates at the deployment level. A common trap is assuming you need to train a custom moderation model or use a separate Azure service, but the correct approach is simply to toggle the content filter on the DALL-E deployment itself. Remember the mnemonic “Filter First” — before generating any images, always confirm that content filtering is enabled to block harmful outputs automatically.
AI-900 Practice Question: Describe features of generative AI workloads on Azure
This AI-900 practice question tests your understanding of describe features of generative ai workloads on azure. 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.
A creative agency wants to use Azure OpenAI to generate marketing images from text descriptions. They need to ensure that the generated images are appropriate for all audiences by automatically blocking sexually explicit or violent content. Which Azure OpenAI feature should they configure 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
Enable content filtering on the DALL-E deployment
Azure OpenAI's DALL-E deployment includes built-in content filtering that automatically blocks sexually explicit, violent, or otherwise inappropriate images from being generated. This feature is configured at the deployment level and requires no custom model training, making it the simplest and most effective way to meet the requirement for all-audience appropriateness.
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 the GPT-4 model with safety prompts
Why it's wrong here
GPT-4 is a text-based model and cannot generate images; safety prompts are not a built-in content filtering mechanism.
- ✓
Enable content filtering on the DALL-E deployment
Why this is correct
Content filtering is a built-in feature of Azure OpenAI that automatically screens for harmful content, including in images generated by DALL-E.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Train a custom image classification model to filter outputs
Why it's wrong here
While possible, this is unnecessary because Azure OpenAI already includes content filtering; training a separate model adds complexity and does not leverage the native safety feature.
- ✗
Use the Embeddings model to detect inappropriate content
Why it's wrong here
The Embeddings model converts text to numerical vectors for similarity search and does not generate images or filter content.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may assume custom training or text-based models are needed, when Azure OpenAI's DALL-E deployment already includes built-in content filtering that directly addresses the requirement.
Trap categories for this question
Similar concept trap
The Embeddings model converts text to numerical vectors for similarity search and does not generate images or filter content.
Detailed technical explanation
How to think about this question
Azure OpenAI's content filtering for DALL-E uses a combination of pre-trained classifiers and rule-based systems to evaluate prompts and generated images against Microsoft's Responsible AI policies. The filtering operates at multiple stages: it checks the input text prompt for prohibited content, and also analyzes the output image for policy violations, automatically blocking or replacing harmful results. This is a managed service feature that requires no custom configuration beyond enabling it on the deployment.
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
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe features of generative AI workloads on Azure — This question tests Describe features of generative AI workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable content filtering on the DALL-E deployment — Azure OpenAI's DALL-E deployment includes built-in content filtering that automatically blocks sexually explicit, violent, or otherwise inappropriate images from being generated. This feature is configured at the deployment level and requires no custom model training, making it the simplest and most effective way to meet the requirement for all-audience appropriateness.
What should I do if I get this AI-900 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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Last reviewed: Jun 11, 2026
This AI-900 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-900 exam.
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