‹ All AI-103 questions

AI-103 Practice Question 43: Content Filter Severity Threshold

Microsoft Azure AI Apps and Agents Developer Associate (AI-103) · Test 5 · question 3 of 10

Plan and manage an Azure AI solutionmedium

A financial services company runs two Foundry model deployments: one behind an external customer chatbot, one behind an internal research assistant. After an incident review, the customer chatbot needs stricter filtering on the hate and violence categories than the platform default. The research assistant's filtering must not change.

What should the team do?

Select one answer
Show answer and explanation

Answer:

  • D. Lower the severity threshold for the hate and violence categories on a content filter configuration, and associate that configuration with only the chatbot's deployment

Severity thresholds are configurable per category (low, medium, high), and lowering one blocks more content in that category; the default filters at medium, so moving to low also catches low-severity hate and violence content. Critically, "content filters can be configured at the resource level. Once a new configuration is created, it can be associated with one or more deployments." Creating a stricter configuration and attaching it only to the chatbot's deployment tightens that deployment's filtering while the research assistant keeps its existing configuration untouched.

- A is wrong because a blocklist screens for literal terms and phrases you supply; it doesn't change how aggressively the hate and violence classifiers themselves fire, so it wouldn't tighten filtering on content that doesn't happen to contain the blocked strings. - B is wrong because Prompt Shields targets adversarial instructions hidden in user input or documents (jailbreaks and indirect attacks), not the hate and violence harm categories. - C is wrong because a configuration change at the resource level doesn't apply itself to every deployment automatically; a configuration must still be explicitly associated with a deployment, and doing that to every deployment would also tighten the research assistant's filtering, which the team was told not to touch.

Reference: Configure content filters (classic)

Practice Test 5 ›

Study guides for AI-103

AI engineer roadmap 2026: skills, certs and the orderAI engineer roadmap for 2026: skills to learn in order, AI engineer vs ML engineer, which certifications fit each stage, and what to skip.
AI-200 exam guide: Azure AI Cloud Developer AssociateAI-200 replaced AZ-204: what the Azure AI Cloud Developer exam tests, how it differs from AI-103, price in USD and INR, format and how to prepare.
How AI Is Changing Software Jobs: Where to PrepareHow AI is changing software jobs: what history shows, the evidence on junior developers, what Klarna learned, new AI roles and five domains to prepare for.
AI-901 exam guide: Azure AI Fundamentals after AI-900AI-901 replaced AI-900: learn what changed, how much Python and Microsoft Foundry you need, exam costs in India, and how to prepare.
Best AI certifications 2026: AWS, Google, Microsoft, ClaudeThe best AI certifications in 2026 from AWS, Google, Microsoft, Claude and Databricks, by level, with price, status and which one to take first.
Microsoft AI certification path 2026: which exam firstMicrosoft AI certification path for 2026 - AI-901, AB-730, AI-103, AI-200, AI-300, AB-100, AI-500 and GH-300 by role, and which exam to take first.
AI-103 Certification Guide: What Changed From AI-102The AI-103 certification replaced AI-102 in 2026. Exam format, cost, the five skill domains, what changed and how to prepare, with free practice questions.
What Is RAG? How Retrieval-Augmented Generation WorksWhat RAG is and how it works: chunking, embeddings, vector search, hybrid search, reranking, GraphRAG and agentic RAG on AWS, Google and Azure.
Prompt engineering vs RAG vs fine-tuningWhen to use prompt engineering, retrieval-augmented generation, fine-tuning or continued pre-training, compared on cost, freshness, hallucination and privacy.