AI-102 · topic practice

Implement generative AI solutions practice questions

Practise Microsoft Azure AI Engineer Associate AI-102 Implement generative AI solutions practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Reviewed byJohnson Ajibi· MSc IT Security
20 questionsDomain: Implement generative AI solutions

What the exam tests

What to know about Implement generative AI solutions

Implement generative AI solutions questions test whether you can apply the concept in context, not just recognise a definition.

How the topic appears in realistic exam-style scenarios.

Which detail in the question changes the correct answer.

How to eliminate plausible but wrong options.

How to connect the question back to the wider exam objective.

Watch out for

Common Implement generative AI solutions exam traps

  • Answering from memory before reading the full scenario.
  • Missing a constraint such as cost, availability, security, scope or command context.
  • Choosing a broad answer when the question asks for the most specific fix.
  • Ignoring why the wrong options are tempting.

Practice set

Implement generative AI solutions questions

20 questions · select your answer, then reveal the explanation

A company wants to generate personalized product descriptions for its e-commerce site using Azure OpenAI. They need to ensure the model's output adheres to brand guidelines and does not generate prohibited content. Which approach should they use?

Question 2hardmultiple choice
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A healthcare startup is developing a chatbot that uses Azure OpenAI to answer patient questions. They need to ensure that the chatbot only uses information from their verified medical database and does not generate unsupported medical advice. What is the best approach?

A developer wants to deploy a custom generative AI model using Azure Machine Learning. Which compute target should they choose for low-latency real-time inference?

A company uses Azure OpenAI to generate code snippets. They notice that the model sometimes produces code that uses deprecated APIs. They want to minimize this without retraining the model. What should they do?

A financial services firm wants to use Azure OpenAI to generate investment advice summaries. They must ensure that the model does not produce any advice that could be interpreted as personalized financial advice. What is the most effective strategy?

A developer wants to use Azure OpenAI to generate text from a prompt. Which parameter controls the diversity of the generated output?

A company is using Azure OpenAI to generate customer support responses. They want to ensure the model does not use any personally identifiable information (PII) in its outputs. What should they implement?

A research lab wants to use Azure OpenAI to generate synthetic data for training a model. They need to generate a large volume of data quickly and cost-effectively. Which approach should they use?

Which TWO actions should you take to reduce the cost of using Azure OpenAI for a chatbot that handles high traffic?

Which THREE factors should you consider when selecting a model for a generative AI solution on Azure?

Which TWO Azure services can be used together with Azure OpenAI to implement a Retrieval-Augmented Generation (RAG) solution?

You are a machine learning engineer at a large retail company. The company has thousands of product descriptions that need to be updated regularly. They currently use a manual process. You propose using Azure OpenAI to generate new descriptions based on product attributes. You have a dataset of existing product descriptions and attributes stored in an Azure SQL Database. The solution must be cost-effective, scalable, and must not require retraining the model. You need to design the solution. You have the following options:

Option A: Use Azure OpenAI with few-shot learning by including examples in the prompt for each product. Deploy the model on an Azure Kubernetes Service (AKS) cluster for high throughput.

Option B: Use Azure OpenAI with prompt templates that include product attributes and call the API for each product. Use Azure Logic Apps to orchestrate the workflow and store results back to Azure SQL Database.

Option C: Fine-tune a custom model on the existing product descriptions and deploy it as a managed endpoint. Use Azure Data Factory to batch process all products.

Option D: Use Azure OpenAI with the batch API to generate descriptions for all products at once, using a single prompt that lists all products and attributes. Store the batch output in Azure Blob Storage and then import into Azure SQL Database.

Which option should you choose?

Question 13mediummultiple choice
Read the full NAT/PAT explanation →

You are a cloud solution architect at a legal firm. The firm needs to automate the summarization of legal documents. They have a large corpus of past case summaries and legal documents stored in Azure Blob Storage. They want to use Azure OpenAI to generate summaries for new documents. The solution must ensure that the generated summaries are accurate and do not contain hallucinated legal facts. The firm also requires that the solution be serverless and minimize operational overhead. You need to design the solution.

Option A: Use Azure OpenAI with a system message that instructs the model to be accurate. Deploy the model as a web app on Azure App Service and call it from Azure Functions triggered by new blob uploads.

Option B: Use Azure OpenAI with Retrieval-Augmented Generation (RAG) by indexing the past case summaries in Azure AI Search. Use Azure Functions to process new documents, retrieve relevant cases, and pass them as context to the model. Store summaries in Azure Cosmos DB.

Option C: Fine-tune an Azure OpenAI model on the past case summaries and deploy it as a managed endpoint. Use Azure Logic Apps to trigger summarization when new blobs are added.

Option D: Use Azure OpenAI with the chat API and provide the entire document in the prompt. Use Azure Container Instances to run a service that calls the API and writes summaries back to Blob Storage.

Which option should you choose?

A company is building a chatbot using Azure OpenAI Service to answer customer queries. The chatbot must not generate harmful or offensive content. Which Azure AI service should be integrated to filter inappropriate content?

A company uses Azure OpenAI to generate product descriptions. They notice that the model occasionally produces descriptions that include false claims about product features. The company needs to reduce the frequency of these inaccuracies without changing the training data. Which parameter adjustment would be most effective?

A developer wants to integrate a pre-built AI model that can extract key information from invoices, such as vendor name, invoice date, and total amount. Which Azure AI service should they use?

Question 17hardmultiple choice
Read the full NAT/PAT explanation →

An organization is deploying a conversational AI solution using Azure OpenAI. They want to ensure the model's responses are grounded in their own knowledge base documents to reduce hallucinations. Which approach should they implement?

Which TWO actions are required to enable a custom chatbot built with Azure OpenAI to answer questions based on a company's internal PDF documents?

Question 19hardmultiple choice
Read the full NAT/PAT explanation →

You are a data scientist at a healthcare company. You have deployed a GPT-4 model using Azure OpenAI to answer patient inquiries about medical conditions. The model is configured with temperature=0.3 and max_tokens=200. Recently, the compliance team flagged that some responses contain contradictory information compared to the official medical guidelines. You need to ensure the model's answers align strictly with the provided medical documents (stored as PDFs in Azure Blob Storage). You have access to Azure Cognitive Search and Azure AI Document Intelligence. The solution must minimize hallucinations and not require retraining the model. What should you do?

A company is deploying a generative AI solution using Azure OpenAI Service to generate product descriptions. The solution must comply with responsible AI principles, specifically ensuring that generated content does not include harmful or offensive language. Which Azure AI service feature should they implement to automatically filter the output?

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Frequently asked questions

What does the AI-102 exam test about Implement generative AI solutions?
Implement generative AI solutions questions test whether you can apply the concept in context, not just recognise a definition.
How should I use these practice questions?
Select your answer before revealing the explanation. Then read why each option is right or wrong — this active recall approach builds retention far faster than re-reading notes.
Can I practise just Implement generative AI solutions questions in a focused session?
Yes — the session launcher on this page draws every question from the Implement generative AI solutions domain. Use a 10-question session first to gauge your baseline, then move to 20 or 30 once the weak spots are clear.
Where can I practise other AI-102 topics?
Use the topic links above to move to related areas, or go back to the AI-102 question bank to see all topics.
Are these real exam questions or dumps?
These are original practice questions written to test the same concepts the AI-102 exam covers. They are not copied from any real exam or dump site.