AI agents at work: start with a specific problem

Choose a well-defined task

Instead of starting with an agent that “answers everything,” choose a problem you can evaluate: finding internal procedures, routing support requests, or helping a team look up information. Define who will use it and the outcome you expect.

Microsoft Copilot Studio lets you build agents and workflows, connect knowledge sources, and add tools. The official documentation covers building, testing, publishing, and monitoring.

Prepare information and permissions

An agent needs relevant, up-to-date sources. Identify the reference documents, their owners, and who is allowed to access them. Plan authentication and data policies before making the agent available.

Copilot Studio governance includes controls over access and data use. Review the connections and actions allowed for the use case. An agent that answers questions and one that changes records require different decisions.

Test before expanding access

• Create real-world questions, including some that the sources cannot answer.
• Check that the agent recognizes its limits and refers users to a person when needed.
• Test with users who have different permissions.
• For consequential actions, plan for human confirmation before execution.
• Collect feedback and assign someone to maintain the agent.

This is an example of a project approach, not a promise of automatic results. The agent’s usefulness depends on the problem, the sources, and the controls you define.