A SharePoint AI Agent for Your HR Questions

You run HR for a company of 120 people. Every week the same questions arrive by email, in Teams, at the coffee machine: how many days of leave do I have left, how do I file an expense claim, what are the rules for working from home, how do I add my partner to the health plan. The answers exist. They sit in SharePoint, in a company agreement, a policy, a procedure. Nobody finds them, so they ask you.

A SharePoint AI agent answers those questions for you, from your own documents, inside Teams, at any hour. Here is how we build one so that it can be trusted, and above all what we forbid it to do.

What a SharePoint AI agent actually does

The agent is built in Copilot Studio, Microsoft's tool for creating agents inside your Microsoft 365 tenant. You give it one or more SharePoint libraries as knowledge sources: the remote-work policy, the expense procedure, the health plan guide, the staff handbook. When an employee asks a question in Teams, the agent searches those documents, writes an answer in plain language and cites the document it came from.

That last point matters. An answer with its source is an answer the person can verify and you can correct. An agent that answers without saying where the information comes from makes you lose control at the first mistake.

Another useful point: the agent reads the documents as they are in SharePoint today. When you update the policy, it answers with the new version, with no retraining and no technical work.

Access rights are respected, on one condition

The legitimate worry: "what if the agent shows a document it should not?" With Microsoft authentication enabled in Copilot Studio, the agent searches with the rights of the person asking. What they cannot open in SharePoint, the agent cannot read on their behalf. A document reserved for the management committee stays invisible to the rest of the company, even if someone asks for it by name.

That does not excuse you from groundwork: if your SharePoint permissions have been sloppy for years, the agent will expose it. Before go-live, we review the source libraries and remove anything that does not belong: disciplinary files, salary grids, sick leave records. Those folders are never an agent's source, whatever the permissions say.

What the agent must never do

• Decide. It explains the leave policy, it does not grant leave. The decision stays with the manager, through the usual channel.
• Promise. "You will get your bonus in March" is not an acceptable answer, even if a document suggests it. The agent points to the right person.
• Compute an individual case. A person's leave balance lives in your payroll or HR system, not in a policy document. Until the agent is connected to it with validated rules, it says it does not know and points to where to look.
• Improvise. On an out-of-scope question it answers "I do not have that information, here is how to reach HR". That sentence is the most important one in the whole project.

The hand-off is set up with you: HR mailbox, Teams channel, form. The agent absorbs the procedural questions, HR keeps the human situations. That is the goal, not a fallback.

Measuring the quality of answers

An agent is not judged on a demo. Before go-live, we build a set of thirty to fifty real questions, collected from employees, each with the expected answer validated by HR. We put them to the agent and grade every answer: correct, incomplete, wrong, or out of scope and properly declined. We fix the sources, we run it again. We go live only above a threshold agreed together.

After that, Copilot Studio provides a dashboard: number of conversations, questions left unanswered, hand-offs to a human, and user ratings. A thirty-minute monthly review is enough to read the unanswered questions and decide: add a document, sharpen an instruction, or confirm it really is out of scope.

Keeping the sources current

An HR agent is only as good as its documents. Three simple rules: one single "source of truth" library with a named owner; old versions archived elsewhere, never next to the new ones; and a mandatory stop at that library every time a rule changes (new remote-work agreement, new health plan, new collective agreement). The agent follows on its own, provided the update actually happened.

For a project like this we start with a scoping session to list the questions, the sources and the forbidden zones, then we build the agent at a fixed price, set at scoping, with tests on your real questions before any go-live. The steps are described on our method page, and our article on your first Copilot Studio agent helps you pick a reasonable scope.