Microsoft AI-103 Q&A - in .pdf

  • AI-103 pdf
  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: May 30, 2026
  • Q & A: 69 Questions and Answers
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  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
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  • Updated: May 30, 2026
  • Q & A: 69 Questions and Answers
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Microsoft AI-103 Q&A - Testing Engine

  • AI-103 Testing Engine
  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: May 30, 2026
  • Q & A: 69 Questions and Answers
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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have a Microsoft Foundry project that contains an agent. The agent has a Model Context Protocol (MCP) tool that queries a knowledge base stored in Azure AI Search.
Some agent runs return answers from the base model without invoking the knowledge base, which results in responses without grounded citations.
You are provided with the following code snippet that runs the agent.
run = project_client.agents.runs.create_and_process(
thread_id=thread.id,
agent_id=agent.id,
)
You need to add the correct tool_choice parameter to the code to deterministically force the agent to invoke the MCP tool on each run.
What should you add?

A) tool_choice ={ " type " : " mcp " }
B) tool_choice={ " type " : " knowledge_base " }
C) tool_choice={ " required " }
D) tool_choice={ " auto " }


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 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) No
B) Yes


3. You have a Microsoft Foundry project that contains three agents as shown in the following table.
Name
Description
TriageAgent
Classifies incoming customer requests
PolicyAgent
Answers policy questions by searching internal content
ActionAgent
Creates or updates tickets by calling an HTTP API
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) a multi-agent group chat session
B) a workflow
C) threads and runs without a workflow
D) separate agent runs coordinated in the application code


4. You need to recommend an invoice review solution that resolves the issue reported by the finance department.
What should you include in the recommendation?

A) Image Analysis
B) Azure Content Understanding in Foundry Tools
C) Azure Document Intelligence in Foundry Tools
D) chat completions


5. You are creating an agent workflow in a Microsoft Foundry project to support natural voice interactions.
The agent must receive continuous audio input, convert the input into text for reasoning, and then return spoken responses to a user. The workflow must meet the following requirements:
. Support turn-taking dynamics, where the agent begins to generate the speech output before the user finishes speaking.
. Operate with low latency to maintain a conversational experience.
You need to enable both speech to text and text to speech in a real-time agent interaction.
What should you do?

A) Use real-time speech to text for incoming audio and text to speech for agent responses.
B) Use an embeddings model to encode the audio, and then decode the audio into text and speech.
C) Use batch transcription to convert the audio input and return text responses from the agent.
D) Use speech translation to convert the audio into another language and return the translated text.


Solutions:

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

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