AI-103 Practice Question 88: Face Service Limited Access

Microsoft Azure AI Apps and Agents Developer Associate (AI-103) · Test 9 · question 8 of 10

Implement computer vision solutionseasy

A city transit agency wants to automatically blur faces in dashcam footage before releasing it publicly, using only face detection bounding boxes; it never needs to identify who anyone is. Because no identification or verification is involved, the team assumes no special approval process applies and plans to start calling the Face service right away.

What should they be told?

Show answer and explanation

Answer:

A. They still need to apply for and be granted access through the Face Recognition intake form before using the Face service at all; access to the Face service is limited based on eligibility and usage criteria, independent of whether identification is used

Microsoft gates the whole Face service, not just its recognition operations: "Face service access is limited based on eligibility and usage criteria... Face service is only available to Microsoft managed customers and partners. Use the Face Recognition intake form to apply for access." Face redaction (the blur-for-privacy scenario the agency wants) is listed as one of the service's own example use cases, built on the same gated resource as identification and verification. Detection-only use doesn't exempt a team from that gate.

- B is wrong because it's the exact mistaken assumption the team started with: the Limited Access requirement applies to the Face resource itself, not only to the identification and verification operations layered on top of detection. - C is wrong because it's a pointless workaround: it still calls a gated Face recognition operation, so it doesn't remove the access requirement, and it adds complexity that returns nothing the Detect operation didn't already provide. - D is wrong on the mechanics, not the access question: Image Analysis 4.0's people-detection feature returns bounding boxes around whole people, not faces, so it doesn't give the agency the face-level regions a blurring pipeline needs, regardless of its access model.

Reference: What is the Azure Face service?

Practice Test 9 ›

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.