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: Aug 07, 2026

Q & A: 159 Questions and Answers

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Microsoft AI-103 Exam Syllabus Topics:

SectionObjectives
Topic 1: Plan and Manage Azure AI Solutions- Responsible AI principles and governance
- Azure AI resource provisioning and configuration
- Model selection and lifecycle management
Topic 2: Implement Computer Vision Solutions- OCR and document intelligence
- Image classification and object detection
Topic 3: Develop Generative AI Applications and Agents- AI agents architecture
  • 1. Memory and state management
    • 2. Agent orchestration and workflows
      - Azure OpenAI Service integration
      • 1. Function calling and tool use
        • 2. Prompt engineering and prompt flow design
          Topic 4: Implement Natural Language Processing Solutions- Text analytics and summarization
          - Language understanding and intent recognition
          - Translation and multilingual support
          Topic 5: Knowledge Mining and Information Retrieval- Azure AI Search configuration
          - RAG (Retrieval Augmented Generation) patterns
          - Indexing and semantic search

          Microsoft Developing AI Apps and Agents on Azure Sample Questions:

          1. You have a Microsoft Foundry project that contains three agents as shown in the following table.

          You need to orchestrate the agents to ensure that the customer requests meet the following requirements:
          - Support a deterministic, step-based process that uses conditional
          branching and shared state across the agents.
          - Optionally trigger a ticket action based on the triage result.
          The solution must minimize development effort.
          What should you include in the solution?

          A) threads and runs without a workflow
          B) a multi-agent group chat session
          C) a workflow
          D) separate agent runs coordinated in the application code


          2. You are building a text-to-speech solution that uses Azure Speech in Foundry Tools to read instructions from the script in a text file.
          You discover that the solution often pronounces technical terms incorrectly.
          You need to prevent the incorrect pronunciations. The solution must minimize development effort.
          What should you do?

          A) From Speech Studio, train a custom neural voice
          B) Use Speech Synthesis Markup Language (SSML) to apply say as rules.
          C) From Azure OpenAI use the Whisper model.
          D) Use Speech Synthesis Markup Language (SSML) to adjust the prosody of the voice.
          E) Use Speech Synthesis Markup Language (SSML) to specify phonemes.


          3. A copilot must answer multi-part questions that depend on earlier turns in the conversation. You want the system to break each complex question into focused subqueries, run them in parallel, and semantically rerank the results before composing an answer. Which Azure AI Search capability provides this?

          A) Increasing the top-k value on a single keyword query
          B) A single vector query with a high similarity threshold
          C) Agentic retrieval
          D) Classic keyword search with a scoring profile


          4. You have an app named App1 that uses a Microsoft Foundry multimodal model deployment.
          App1 runs optical character recognition (OCR) on uploaded images and appends the OCR output to the prompt as additional context.
          Some uploaded images contain embedded text.
          You need to prevent potentially malicious instructions from being processed by the model.
          What should you use?

          A) image moderation
          B) prompt shields for documents
          C) prompt shields for user prompts
          D) protected material text


          5. You have a Semantic Kernel agent that provides answers to product questions.
          You plan to extend the capabilities of the agent to answer questions about the status of orders.
          You need to ensure that the agent answers order status questions as quickly as possible. The solution must minimize development effort.
          What should you include in the solution?

          A) an agent
          B) a kernel
          C) a function
          D) a plugin


          Solutions:

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

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