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

AI-103 real exams

Exam Code: AI-103

Exam Name: Developing AI Apps and Agents on Azure

Updated: Jul 28, 2026

Q & A: 159 Questions and Answers

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Microsoft AI-103 Exam Syllabus Topics:

SectionWeightObjectives
Implement computer vision solutions10–15%- Build multimodal solutions
  • 1. Combine vision and language capabilities
  • 2. Process and analyze video content
- Implement image analysis and processing
  • 1. Implement object detection and image classification
  • 2. Use Azure AI Vision services
  • 3. Extract text and structure from images
Implement information extraction and knowledge mining10–15%- Build knowledge bases and search solutions
  • 1. Implement Azure AI Search
  • 2. Create and manage vector indexes
  • 3. Design knowledge mining pipelines
- Extract structured data from documents
  • 1. Use Azure AI Document Intelligence
  • 2. Process forms, invoices, and unstructured content
Implement text and speech analysis solutions10–15%- Implement speech capabilities
  • 1. Speech-to-text and text-to-speech integration
  • 2. Speech translation and speaker recognition
- Implement natural language processing
  • 1. Build conversational language understanding
  • 2. Use Azure AI Language services
  • 3. Perform sentiment analysis, entity recognition, and summarization
Implement generative AI and agentic solutions30–35%- Build generative AI applications
  • 1. Implement prompt engineering and optimization
  • 2. Integrate Azure OpenAI and other models
  • 3. Implement function calling and tool use
  • 4. Build retrieval-augmented generation (RAG) solutions
- Design and implement intelligent agents
  • 1. Integrate agents with external systems and data sources
  • 2. Select agent architecture patterns
  • 3. Implement multi-agent workflows and orchestration
  • 4. Manage state, memory, and context
Plan and manage Azure AI solutions25–30%- Design Azure AI infrastructure
  • 1. Plan for security, compliance, and responsible AI
  • 2. Select appropriate Azure AI Foundry services
  • 3. Design for scalability, availability, and cost optimization
- Manage AI solution development lifecycle
  • 1. Monitor and maintain AI workloads
  • 2. Integrate with CI/CD pipelines
  • 3. Configure model and agent deployments

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have a Microsoft Foundry project that contains an agent for a customer support chat app.
The agent uses a memory store and a memory search tool.
You need to ensure that the conversation history does NOT persist across separate sessions.
To what should you set the scope of the memory tool?

A) {{$userId}}
B) global
C) session
D) {{$conversationId}}


2. You have an Azure AI agent solution.
You plan to create an agent-based app named App1 that will analyze and summarize data for users and generate data-driven recommendations. App1 will be used by non-technical business users and must adapt to new and unforeseen business challenges and improve its performance over time.
You need to identity which type of agent to use in App1. The solution must meet the following requirements:
- Adapt and improve the agents' performance over time based on user
feedback.
- Provide tailored recommendations to help users make informed
decisions.
- Provide the best possible performance of the app.
Which agent type should you identify?

A) task automation
B) cognitive
C) prompt-and-response
D) autonomous


3. Hotspot Question
You are creating an enrichment pipeline that will use Azure AI Search. The knowledge store contains unstructured JSON data and the text from scanned PDF documents.
Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


4. You are building an image sharing app that will use Azure AI to prevent users from sharing sexually explicit images.
You need to ensure that inappropriate images are identified correctly. The solution must minimize development effort.
What should you use?

A) Vision Studio in Azure AI Vision
B) Azure AI Studio
C) Visual Studio
D) Azure AI Content Safety Studio


5. A developer needs a managed identity to call a Microsoft Foundry project endpoint to run inference and use agents. Security policy requires the least-privilege role that grants data-plane access and nothing more. Which built-in role should you assign to the managed identity?

A) Azure AI Developer
B) Foundry Account Owner
C) Foundry User
D) Cognitive Services Contributor


Solutions:

Question # 1
Answer: C
Question # 2
Answer: B
Question # 3
Answer: Only visible for members
Question # 4
Answer: D
Question # 5
Answer: C

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