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

AI-103 actual test
  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: Aug 02, 2026
  • Q & A: 159 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $59.99  

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Microsoft AI-103 Exam Syllabus Topics:

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

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have a product support manual.
You need to build a product support chatbot based on the manual. The solution must minimize development effort and costs.
What should you use?

A) Azure OpenAI GPT-4 with grounding data that uses Azure AI Search
B) Azure AI Phi-3-medium with fine-tuning
C) Azure AI Language Custom question answering
D) Azure AI Document intelligence


2. In mid-2026 you are starting a brand-new agentic application on Azure and want to build on the generally available, supported entry point for Foundry agents. Which API should you target?

A) The Assistants API
B) The Responses API via Foundry Agent Service
C) The legacy text Completions API
D) The LUIS runtime API


3. You have a Microsoft Foundry project named Project1.
Project1 contains an application that processes PDF vendor invoices.
You need to configure Azure Document Intelligence in Foundry Tools to generate a Markdown output that preserves the sections and table structure of the PDFs. The solution must minimize development effort.
What should you do?

A) Configure output=figures when you analyze the PDF.
B) Configure content=markdown when you analyze the document.
C) Increase the confidence threshold.
D) Set the output_content_format=ContentFormat.MARKDOWN value.


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 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 image moderation to block unsafe content before processing the images.
Does this meet the goal?

A) Yes
B) No


5. You have a Microsoft Foundry project that generates short promotional product videos.
After several clips are approved, reviewers notice a small watermark in the top-right corner of some videos.
You need to remove the watermark without regenerating the videos.
What should you do?

A) Apply a mask-based inpainting edit to the affected part of the video.
B) Modify the original prompt to exclude watermarks.
C) Increase the guidance scale.
D) Crop the video by using the size parameter.


Solutions:

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

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