What is an AI agent in Microsoft Copilot? 

Microsoft Copilot has already become a part of everyday life in many companies. It is used to write emails, summarize meetings, structure documents, and find information faster. 

But as Copilot is used more actively, there is also a need to make AI more targeted. Because even though Copilot can help with many different tasks, it is not always enough to ask individual questions from time to time. 

This is where AI agents come in. They can be used to make Copilot more concrete, more task-oriented, and better adapted to the workflows the company already has. This could be in HR, sales, support, project management, or internal knowledge sharing, for example. 

To understand the value of AI agents, it is therefore important to first look at what an AI agent actually is. 

What is an AI agent? 

An AI agent is a digital assistant created to assist with a specific task, process, or workflow. It can receive instructions, use selected data sources, and respond based on the purpose for which it was built. 

This means that an AI agent doesn't need to know everything. On the contrary, it often works best when it is defined. The clearer the task, the easier it is to get useful answers. 

A typical Copilot conversation can be used broadly. You can ask for help with an email, an analysis, a summary, or a text. An AI agent is more focused. For example, it can be built to know a specific process, a specific area, or a specific type of information. 

Examples of AI agents can be: 

• An HR agent who answers questions about vacation, sick leave, and internal policies  
• A sales agent who helps prepare for client meetings  
• A support agent who finds answers in internal guides  
• A project agent that helps collect status, tasks, and decisions

In this way, an AI agent can help make Copilot more concrete and useful in everyday life. The most important thing is not that the agent sounds advanced. The most important thing is that it solves a real task. 

Why use an AI agent in the company? 

AI agents make especially sense when employees often search for the same information, ask the same questions, or repeat manual tasks. 

In many companies, knowledge is scattered across emails, Teams, SharePoint, documents, and old files. This means employees spend time searching, asking colleagues, or recreating something that already exists. 

This is where an AI agent can help create more structure. It can find internal procedures, summarize material before a meeting, or help new employees find answers without having to ask around the organization. 

This does not mean that an AI agent replaces the employee. It acts as an aid to access knowledge faster and make the workday more efficient. Because the problem is rarely that the company lacks information. The problem is often that the information is scattered and difficult to find when the employee actually needs it. 

How to create an AI agent in Copilot 

Microsoft has made it possible to create agents directly in Microsoft 365 Copilot. Users can open the Microsoft 365 Copilot app, select Agents, click on New Agent and describe what the agent should help with. Then follow the setup in Copilot. 

This means you don't necessarily need to know how to code to get started. Microsoft's Agent Builder in Microsoft 365 Copilot is designed to let you build agents using plain language and existing content. 

But even though it has become technically easier, the company should still think twice before setting up an agent. 

How to build a good AI agent:  

1. Start with the purpose. 

First, you should define what the agent should help with. 

It could be, for example: 

• To answer questions about internal procedures 
• To help with meeting preparation 
• Finding information in specific documents 
• To support the onboarding of new employees 
• To gather knowledge from a specific team or project
  
  

If the purpose is unclear, the agent will also be unclear. Therefore, you should start simple. 

A good question is: 

What specific task should this AI agent make easier? 

2. Describe the agent's task 

Once the purpose is clear, the agent's task must be described in plain language. 

Here you should explain what the agent should help with, who it is relevant to, and how it should respond.  

• Should it be short and precise?  
• Should it refer to internal documents?  
• Should it ask follow-up questions if it lacks information? 
• The clearer the instruction, the better the agent's response.
  
  

3. Choose relevant data sources 

An AI agent will only be as good as the material it is given access to. 

If the agent is going to answer questions about internal guidelines, they need to rely on the right documents. If they are going to help the sales team, they need to have access to relevant sales materials. If they are going to help with support, they need to know the relevant guides. 

Here it is important not to just give access to everything. This can create noise and increase the risk that the agent uses incorrect or irrelevant information. 

It's better to start with a few, precise sources. 

4. Test the agent 

Before the agent is widely shared, it should be tested. 

Ask the questions that employees would realistically ask. Check if it answers correctly, if it misunderstands anything, and if it actually makes the workflow easier. 

If the agent responds imprecisely, it is often a sign that the instruction or data sources need to be adjusted. 

AI agent in Copilot or Copilot Studio? 

There are several ways to work with agents in the Microsoft universe. 

An agent in Microsoft 365 Copilot is relevant when you want to create a relatively simple agent for yourself or a small team. It could be an agent that helps with internal questions, meeting preparation, or document searching. 

Copilot Studio is more relevant if the company needs more advanced agents, more customizations, or integrations with other systems. 

In short: 

• Use Microsoft 365 Copilot when the need is simple and close to the daily workflow  
• Use Copilot Studio when the agent needs to be more advanced or integrated more broadly

The business doesn't have to start big. It's often best to start with one specific workflow and learn from the experience. 

How to get the business off to a good start 

It's easy to get caught up in the possibilities. But AI agents shouldn't be created haphazardly. 

Before the company gets started, it should decide on some simple questions: 

• What workflow do we want to improve?  
• Who needs the agent?  
• What data sources may the agent use?  
• Who owns the agent?  
• Who tests whether it answers correctly?  
• Who updates it when information changes?  
• How do we assess whether it actually saves time?

A good start is to choose one workflow where there is already a lot of repetition. This could be internal questions, onboarding, meeting preparation, or searching documentation. 

Then, the company can build a simple AI agent, test it, and tweak it before sharing it more widely. 

AI agents require structure  

AI agents can make Microsoft Copilot more relevant to everyday life. They can help employees find information, save time, and create more consistent workflows. 

But the value depends on how they are used. 

An AI agent should have a clear purpose, relevant data sources, and a clear owner. Otherwise, the company risks the agents becoming just another unstructured tool in the IT landscape. 

Therefore, when the company starts using more AI agents, the next question becomes: How do we keep an overview? 

That's what the next blog post is about, where we take a closer look at Microsoft Agent 365 and how companies can create structure, security, and control around their AI agents. 

At MainBrain, we help companies get more out of Microsoft 365, Copilot and AI, with a focus on structure, security and solutions that work in practice. Book a non-binding meeting here.