AI-103 Training Materials & AI-103 Certification Training & AI-103 Exam Questions

Microsoft AI-103 : Developing AI Apps and Agents on Azure

Exam Code: AI-103

Exam Name: Developing AI Apps and Agents on Azure

Updated: Sep 15, 2026

Q & A: 159 Questions and Answers

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Microsoft AI-103 Exam Syllabus Topics:

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

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

Question #1

You have a Microsoft Foundry project that contains a prompt agent used by a customer support web app.
The agent is invoked from a Python service that does NOT run in the Foundry portal.
You need to implement end-to-end tracing to capture latency breakdowns and exceptions across agent runs.
Which two components can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. Microsoft Sentinel
  • B. Application Insights
  • C. OpenTelemetry
  • D. a Log Analytics workspace
  • E. the Azure Monitor Agent
Reveal Solution  Discussion  0

Correct Answer: B,C  🗳️

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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 add a reflection pass that regenerates the response if the required clauses are missing.
Does this meet the goal?

  • A. No
  • B. Yes
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #3

Hotspot Question
You have a Microsoft Foundry project that contains an agent.
You use a GitHub Actions workflow for CI/CD.
You need to configure the workflow to automatically evaluate the agent when a pull request (PR) is created and prevent branches from merging if the evaluation results do NOT meet the defined thresholds.
How should you configure the workflow? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Reveal Solution  Discussion  0

Correct Answer:

Question #4

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 User
  • B. Cognitive Services Data Reader
  • C. Cognitive Services OpenAI User
  • D. Contributor
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #5

A multimodal agent processes user-uploaded images. An attacker embeds hidden text instructions inside an image, hoping the agent will read and act on them. Which Azure AI Content Safety capability is designed to detect this kind of attack?

  • A. A content filter set to High severity for the Violence category
  • B. Raising the image resolution threshold on the analyser
  • C. Disabling the agent's file search tool
  • D. Prompt Shields, which detects document and indirect prompt injection
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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