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AI-103
  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: Aug 28, 2026
  • No. of Questions: 159 Questions and Answers
  • Download Limit: Unlimited
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Microsoft AI-103 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement text analysis and information extraction solutions10-15%- Analyze and extract information
  • 1. Use document intelligence services
  • 2. Implement natural language processing
  • 3. Extract entities and structured data
Topic 2: Implement generative AI solutions25-30%- Optimize and evaluate models
  • 1. Implement multimodal AI capabilities
  • 2. Evaluate responses and grounding
  • 3. Configure content filters and safety
- Develop generative AI applications
  • 1. Build retrieval-augmented generation solutions
  • 2. Implement prompt engineering
  • 3. Use Azure OpenAI and Foundry models
Topic 3: Plan and manage Azure AI solutions25-30%- Plan Azure AI resources
  • 1. Manage deployments and monitoring
  • 2. Configure authentication and security
  • 3. Select Azure AI services and Foundry resources
- Manage AI solution lifecycle
  • 1. Apply responsible AI practices
  • 2. Implement CI/CD for AI applications
  • 3. Monitor model and application performance
Topic 4: Implement agentic solutions20-25%- Manage agent operations
  • 1. Monitor and debug agents
  • 2. Secure agent interactions
  • 3. Implement scalable deployments
- Build AI agents
  • 1. Configure memory and orchestration
  • 2. Create autonomous and multi-agent workflows
  • 3. Integrate tools and external knowledge
Topic 5: Implement computer vision solutions10-15%- Analyze visual content
  • 1. Use multimodal vision APIs
  • 2. Implement OCR and visual understanding
  • 3. Process images and video

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

Question 1

You are building a customer support web app named App1 in Microsoft Foundry that uses a GPT realtime model.
App1 must support:
- Live, low-latency voice conversations that use Azure OpenAI
- Streaming audio input from users and playback audio responses
You need to configure a connection method that supports real-time audio streaming in client application and targets approximately 100 ms latency.
Which connection method should you use?

A. SIP
B. WebSocket
C. RTMP
D. WebRTC


Question 2

Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
Users report that some responses omit required regulatory clauses, even when the clauses are present in the retrieved content.
You need to improve response completeness.
Solution: You run an evaluation flow that scores responses for completeness and blocks responses that fall below a defined threshold.
Does this meet the goal?

A. Yes
B. No


Question 3

You have a Microsoft Foundry project that contains a model deployment.
You have an application that calls the deployment by using the Azure OpenAI v1 API and DefaultAzureCredential.
The developers at your company receive HTTP 403 errors when they send inference requests, even after running az login.
You need to ensure that the developers can perform model inference. The solution must follow the principle of least privilege.
Which role-based access control (RBAC) role should you assign to the developers?

A. Cognitive Services OpenAI User
B. Cognitive Services Data Reader
C. Cognitive Services User
D. Contributor


Question 4

You have an Azure Speech in Foundry Tools resource that hosts a custom speech to text model deployed to a custom endpoint. An agent uses the endpoint to perform real-time speech recognition.
You are approaching the expiration date of the custom speech to text model.
What is the expected behavior when the model expires?

A. Speech recognition requests will fall back to the most recent base model for the same locale.
B. The custom model will be deleted automatically when the model expires.
C. Speech recognition requests will continue to use the expired custom model until the model is removed manually.
D. Speech recognition requests will return a 4xx error until a new custom model is deployed.


Question 5

You have a Microsoft Foundry agent that grounds responses from an Azure Search index that contains the following:
- Searchable text fields for product names and product codes
- A vector field that stores embeddings for product descriptions
You need to ensure that users can query the index by using the following:
- Exact product names or codes
- Natural language descriptions of the products
What should you configure?

A. vector search only
B. semantic search only
C. hybrid search
D. keyword search only


Solutions:

Question 1
Answer: B
Question 2
Answer: B
Question 3
Answer: A
Question 4
Answer: A
Question 5
Answer: C

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