AI-103 Certification Exam Guide + Practice Questions Updated 2026

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?

DRAG DROP -
You have a Microsoft Foundry project that contains a customer support agent grounded in internal documentation.
After a recent update, users report the following issues:
Some answers are unsupported by retrieved documents.
A small number of responses are flagged for policy violations.
You need to evaluate each issue.
Which observability signals should you use for each issue? To answer, drag the appropriate observability signals to the correct issues. Each observability signal may be used once, more than once, or not at all. You may need to drag the spit bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.

HOTSPOT -
Your company is piloting a customer support agent in a Microsoft Foundry project name Project1. Project1 is connected to an existing Application Insights resource, and the company’s support team reviews runs in the Traces tab.
The Foundry Agent Service is configured to perform the following actions:
Retrieve the Application Insights connection string by calling project_client.telemetry.get_application_insights_connection_string().
Call configure_azure_monitor(connection_string=...) to enable telemetry.
A separate LangChain service is configured to use OpenTelemetry and has the following configurations:
Uses AzureAIOpenTelemetryTracer(connection_string=..., enable_content_recording=False)
Passes the tracer by using config={“callbacks”:[azure_tracer]}
Company policy has the following requirements:
Telemetry from LangChain and OpenTelemetry must be distinguishable within the same Application Insights resource.
Secrets and credentials must NOT be stored in prompts, tool arguments, or span attributes.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

HOTSPOT -
You have a Microsoft Foundry project that contains an agent.
You use a GitHub Actions workflow for CI/CD.
You need to configure the workflow to automatically evaluate the agent when a pull request (PR) is created and prevent branches from merging if the evaluation results do NOT meet the defined thresholds.
How should you configure the workflow? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

DRAG DROP
You have a Microsoft Foundry project that contains a deployed ticket-triage agent.
You discover that sometimes the agent responds without calling any tools, even when a tool is required.
You need to ensure that the agent calls a tool during execution.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.