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

AI-103 real exams

Exam Code: AI-103

Exam Name: Developing AI Apps and Agents on Azure

Updated: Aug 16, 2026

Q & A: 159 Questions and Answers

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

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have a web app named App1 that processes user prompts by integrating with a Microsoft Foundry project named Project1. App1 performs the following actions:
- Sends prompts directly to a model by using the Azure OpenAI Responses API
- Invokes the Azure AI Content Safety tool by using a Foundry
connection within the same request
You need to configure end-to-end visibility into each step of the request workflow.
What should you do?

A) Enable logging by using the client SDK for Content Safety.
B) Enable application tracing in Project1.
C) Route requests through the Azure OpenAI endpoint.
D) Enable logging by using Foundry Local.


2. You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
You need to improve response completeness. The solution must be implemented in the logic of the application code before responses are returned.
What should you do?

A) Replace the model with a smaller deployment.
B) Decrease the value of the temperature parameter.
C) Increase the value of the presence_penalty parameter
D) Add a retry evaluation before the responses are returned.


3. You have a Microsoft Foundry project that contains a customer support agent built on a deployed chat model.
The agent responses are validated by using an automated testing system that compares generated answers to stored expected outputs. Identical prompts must return consistent response to prevent automated test failures.
You need to reduce response variability, without modifying the prompt or reducing factual accuracy.
What should you do for the model?

A) Increase the temperature parameter.
B) Increase the max_tokens parameter.
C) Decrease the temperature parameter.
D) Remove stop sequences from the requests.


4. 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) Yes
B) No


5. 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 multimodal AI generative model that accepts image uploads and uses extracted image text to generate responses.
You discover that users can upload unsafe images and embed hidden instructions into images to manipulate the model.
You need to implement controls to mitigate the risk.
Solution: You configure protected material detection.
Does this meet the goal?

A) Yes
B) No


Solutions:

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

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