AI-102 Plan and manage an Azure AI solution Practice Question
You are planning an Azure AI solution that will use several Azure AI services, including Azure AI Vision and Azure AI Language. The solution must be deployed to multiple regions and must provide a single endpoint and key for all the services. Which Azure resource type should you create?
⚠ Common exam trap
Test-takers frequently confuse an API gateway such as API Management with a unified Azure AI services key, when the gateway still requires managing a separate credential for each backend.
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
✓
An Azure AI services multi-service account
A multi-service account is designed to expose several Azure AI services through one endpoint and one key. It supports deployment in multiple regions while keeping a consistent management and authentication model. Separate resources or an API Management layer would still leave you managing per-service credentials, so they do not satisfy the single-key requirement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
An Azure API Management instance with a backend for each service
Why it's wrong here
API Management can front multiple services behind a single URL, but it does not provide a single Azure AI services key. You would still need to manage credentials for each backend service, and the scenario asks for a single key. API Management is useful for throttling and transformation, but it is not the resource type that supplies the unified key.
- ✗
An Azure Machine Learning workspace with online endpoints
Why it's wrong here
An Azure Machine Learning workspace is used for training and deploying custom models, not for consuming prebuilt Azure AI services such as Vision and Language. It does not expose those services through a single key, and it adds model-management complexity that the scenario does not require. This resource type is a poor fit for the stated goal of unified access to multiple cognitive services.
- ✓
An Azure AI services multi-service account
Why this is correct
A multi-service account provides one endpoint and one key that can be used across supported Azure AI services such as Vision and Language. It also supports multi-region deployment by creating the account in each region while keeping a consistent management model. This directly satisfies the requirement for a single endpoint and key across several services.
- ✗
A separate Azure AI services resource for each service in each region
Why it's wrong here
Creating a separate resource for each service in each region would require managing multiple endpoints and keys, which contradicts the requirement for a single endpoint and key. It also increases operational overhead because each resource has its own access control and quota. This approach is valid when services need independent scaling or isolation, but it does not meet the stated single-endpoint goal.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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.