50 Microsoft Certified: Azure AI Engineer Associate Practice Questions: Question Bank 2025

You are building an internal app that identifies objects in photos uploaded by employees. The app must return bounding boxes and labels for common objects with minimal custom training. Which Azure service should you use?

You need to store and manage multiple prompt templates for a generative AI application, track versions, and evaluate prompt changes over time. Which approach is most appropriate?

You are implementing a chatbot that must detect user intent and extract entities such as city and travel date from messages. You want a managed service optimized for intent classification and entity extraction. Which Azure service should you use?

A team is indexing thousands of PDF contracts and wants to enable semantic search over extracted key clauses. They need to extract text and structure from PDFs, then index it for search with enrichment. Which combination of Azure services best fits this requirement?

Your solution uses an Azure AI services resource from multiple apps. You must ensure that API keys are not stored in code and can be rotated without redeploying the apps. What should you use?

You built an Azure AI Search index with an indexer that enriches documents using a skillset. New documents added to the data source are not appearing in the index. The indexer status shows "idle" with no errors. What is the most likely action to make the new documents searchable as soon as possible?

You need to detect Personally Identifiable Information (PII) in customer support transcripts and redact it before storing the text. Which feature should you use?

You are implementing Retrieval-Augmented Generation (RAG) for an enterprise knowledge base. The system must reduce hallucinations by grounding responses in company content and must return citations. Which design is most appropriate?

You built a Custom Vision object detection model for a manufacturing line. In production, detection accuracy drops significantly when lighting conditions change and when new camera angles are introduced. You must improve robustness with minimal changes to the app. What should you do first?

Your organization requires that all calls to Azure OpenAI from an internal application remain on the private network and are not accessible over the public internet. Which configuration best meets this requirement?

You are deploying an Azure AI Services resource to support multiple apps across different subscriptions. Your organization requires that all access be managed using Azure AD identities rather than API keys. What should you implement?

You need to extract printed text from images captured by a mobile app. The app can send the image to Azure for processing. Which Azure AI Vision capability is best suited for this requirement?

A customer support team wants to analyze incoming messages and determine whether each message expresses a positive, negative, or neutral opinion. Which Azure AI Language feature should you use?

You built a chat app using Azure OpenAI. Users report that the assistant sometimes reveals internal system instructions and hidden context when asked directly. Which mitigation is most appropriate?

You must build a searchable knowledge base over thousands of PDFs and Office documents stored in Azure Blob Storage. You need to extract text and structure, enrich the content with key phrases and entities, and enable full-text search and filters. Which architecture is most appropriate?

A document processing pipeline uses Azure AI Document Intelligence to extract fields from invoices. Some invoices have a new layout and the extraction quality drops. You want to improve extraction without writing complex parsing code. What should you do?

You are implementing Retrieval-Augmented Generation (RAG) with Azure AI Search and Azure OpenAI. You want to reduce hallucinations by ensuring the model answers only from retrieved sources and cites them. Which approach best supports this goal?

You need to design a multilingual customer support analytics solution. Requirements: detect the language, translate messages to English for downstream processing, and then run entity recognition and sentiment analysis. Which sequence of services is most appropriate?

A security team requires that all calls to Azure AI Services originate only from your virtual network, and public internet access must be blocked. You also need name resolution to route traffic privately. What should you configure?

You are troubleshooting a RAG implementation. Azure AI Search returns relevant documents, but the Azure OpenAI responses ignore them and answer from general knowledge. You want the assistant to strictly ground responses in the retrieved passages. What is the most effective change?

You are deploying an Azure AI Services resource that will be called from an internal web app. The security team requires that traffic to the service not traverse the public internet. What should you configure?

A retail company wants to prevent their image moderation workflow from flagging products that contain their brand logo as adult content. They use Azure AI Vision's image analysis for content safety signals. What is the most appropriate approach?

You build a chatbot using Azure AI Language. Users ask questions in English, Spanish, and French. You want to identify the input language before routing the query to the correct knowledge base. Which capability should you use?

Your team is indexing thousands of PDFs into Azure AI Search. Each PDF can contain multiple languages and some pages are scanned images. You need the index to support full-text search across both digital text and scanned pages. What should you include in the skillset pipeline?

You are using Azure OpenAI to generate summaries of customer emails. The output must not include phone numbers, email addresses, or credit card numbers. Which approach best enforces this requirement at runtime?

A company processes receipts using Azure AI Document Intelligence. They must ensure that no customer data is stored longer than necessary, and they want to minimize exposure of access keys in application code. What is the best practice approach?

You implement a Retrieval-Augmented Generation (RAG) solution with Azure AI Search and Azure OpenAI. Users report that answers are fluent but sometimes contain facts not present in the retrieved documents. What should you do to reduce hallucinations most effectively?

Your organization needs to provide a single endpoint that routes requests to multiple Azure OpenAI deployments (different models/regions) and enforces throttling, authentication, and request logging. Which architecture component is most appropriate?

You are designing an Azure AI Search index for a RAG app. Each document is split into chunks with embeddings. You must ensure that when a user retrieves a chunk, you can also filter by the original document's access control list (ACL) and show citations back to the source file and page number. Which index design best meets the requirement?

You built a conversational app that uses Azure OpenAI with function calling to trigger internal workflows. During testing, the model occasionally selects an incorrect function when user requests are ambiguous. You need to reduce incorrect tool invocation while keeping the experience conversational. What is the best approach?

You are deploying an Azure AI services resource that will be used by multiple internal applications. Security policy requires that no public network access is allowed. Which configuration best meets the requirement?

You need to extract printed text from images captured by a mobile app and return the recognized text to the app. Which Azure AI service capability should you use?

Your team wants to standardize on using Azure AD for authenticating to Azure OpenAI from an internal web app. Which approach is recommended?

You have 500,000 customer support messages in multiple languages. You need to identify the language of each message and store it in a database. Which Azure AI service feature should you use?

You are building a call center solution that must provide real-time transcription and also identify when specific phrases (for example, "cancel my account") are spoken. What is the best approach?

You are ingesting PDFs and images into an Azure AI Search index for enterprise search. You need to extract text and enrich it with entities before indexing. Which Azure AI Search capability should you configure?

Your organization must ensure that user prompts and model outputs from an Azure OpenAI-powered chat application are checked for policy violations before being displayed. What should you implement?

A Document Intelligence extraction pipeline works for most vendor invoices but fails on one vendor that uses a unique layout. You need high accuracy for that vendor while keeping the existing approach for others. What should you do?

You are implementing retrieval-augmented generation (RAG) using Azure AI Search and Azure OpenAI. Users complain that answers often ignore the provided documents and instead rely on the model’s general knowledge. What is the best mitigation?

You have an Azure AI Search indexer pulling documents from a storage account. After moving the search service to use private networking, the indexer begins failing with connectivity errors to the data source. The storage account has public access disabled. What is the most likely fix?

You build an internal support bot using Azure AI Language with a custom question answering project. The support team wants the bot to return an answer only when it is confident, otherwise it should respond with a handoff message. Which configuration should you adjust to meet this requirement?

You use Azure AI Vision to read text from images uploaded by users. Some images contain rotated text and mixed printed/handwritten content. Which feature is most appropriate to extract the text reliably?

You need to limit which applications can call an Azure AI Services resource from your corporate network. You want to avoid exposing keys in client apps. Which approach is recommended?

You are building a retrieval-augmented generation (RAG) solution with Azure OpenAI. You must ensure that user prompts and retrieved documents are not used to train the underlying model. What should you do?

You ingest thousands of PDFs into an Azure AI Search index. Search relevance is poor because key phrases are split across lines and sections. You want to preserve document structure and extract text with layout information for better chunking. Which approach is best?

A sentiment analysis pipeline built with Azure AI Language works well in testing but produces many "unknown" results in production. Logs show users frequently submit empty strings, whitespace, or extremely short inputs like "ok". What is the best fix?

You use Azure AI Search with a skillset that enriches documents (OCR, key phrases, entity recognition). The indexing pipeline is slow and occasionally fails due to transient errors from enrichment skills. What is the best way to improve reliability without losing enrichment results?

You deployed an Azure OpenAI chat application. Security requires that the model must not reveal specific confidential terms (project code names) even if asked directly. What is the best approach to enforce this policy?

You are designing a multi-tenant application that calls Azure AI Services for document processing. Each tenant must be billed internally and must not be able to access another tenant’s data or usage. What is the most appropriate design?

You build a RAG system using Azure AI Search and Azure OpenAI. Users report answers that include outdated policy information even though newer documents are in the index. Investigation shows both old and new policies are being retrieved. You need a robust fix that minimizes irrelevant retrieval. What should you do?