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AI-102 Implement generative AI solutions Practice Question

You are designing a generative AI solution using Azure OpenAI Service. The solution must meet compliance requirements by preventing the model from generating sensitive personal data. Which TWO configurations should you implement? (Select TWO.)

⚠ Common exam trap

Watch out — candidates often choose a system message (Option C) as a reliable control, but Microsoft explicitly warns that system messages are not a security boundary and can be bypassed, whereas DLP and content filters provide enforceable guardrails.

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

Implement data loss prevention (DLP) policies using Microsoft Purview

Microsoft Purview DLP policies can scan and block sensitive data (e.g., PII, credit card numbers) in prompts and responses when integrated with Azure OpenAI Service, ensuring compliance by preventing data exfiltration. Azure AI Content Safety content filters allow you to configure severity thresholds to block harmful or sensitive content categories, directly preventing the model from generating personal data at the inference layer.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Implement data loss prevention (DLP) policies using Microsoft Purview

    Why this is correct

    DLP policies provide data governance and protection.

  • Configure content filters in Azure AI Content Safety

    Why this is correct

    Content filters can block sensitive data patterns.

  • Add a system message instructing the model not to generate personal data

    Why it's wrong here

    System messages are not enforced and can be bypassed.

  • Deploy the model in a specific region

    Why it's wrong here

    Region deployment does not prevent generation of personal data.

  • Fine-tune the model with a dataset that excludes personal data

    Why it's wrong here

    Fine-tuning does not guarantee the model won't generate personal data.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.