An AI chatbot for your own company knowledge answers employees' questions from your documents, and lives right inside Microsoft Teams. Not general answers from the internet, but the answer that is in your handbook, policy or product documentation, with a reference to the source. The employee does not need to know which folder something is in, and nobody has to disturb a colleague.
The condition is that such a chatbot is set up well. It answers only from what you have written down yourselves, and says honestly when it does not know.
Why do the same questions keep coming back?
Almost every company already has the answers. They are in a handbook, on SharePoint, in a PDF or in a colleague's head. The problem is that employees do not know where to look, which document is current and which rule applies to them. So they ask the person who is sure. Every week, and each time phrased a little differently.
What does an AI chatbot in Teams look like in practice?
Take HR as an example. Suppose a company has fifty employees and one colleague ends up answering all the questions about leave, reporting sick, travel expenses and working hours. It happens by email, in Teams messages and at the coffee machine. It is not a big problem, but it costs hours every week that nobody planned.
In this fictional example there is now a colleague in Teams called "HR Assistant". An employee types: "I fell ill during my holiday. What do I do?" The chatbot replies with the company's policy and names the section of the handbook where it is written. If someone asks for their personal leave balance, the chatbot invents nothing but points to the HR system where that balance is kept.
The difference is not the technology. Employees get their answer at the moment they need it, and the colleague who used to answer everything has time left for conversations that need a person.
What else can you use an AI chatbot for?
HR is just one example. Wherever the same questions keep coming back and the answer is written down somewhere, it can work:
- IT: "How do I connect my phone to the wifi?" and "How do I request access to an application?"
- Finance: "What is the maximum I can spend on a hotel?" and "When must I submit my expense claim?"
- Sales: "What are the terms for product X?" and "What is the maximum discount I may give?"
- Operations: "What do I do when a delivery is delayed?"
- Customer service: "What is our returns policy?" The same knowledge can also be offered to customers, for example on your website.
- Management: "Where is our information security policy?"
For years employees had to adapt to how company information is organised. They had to know which folder something is in, what the document is called and which department is responsible. With an AI chatbot you turn that around: the employee asks the question, and the technology finds the company knowledge.
How does an AI chatbot in Microsoft Teams work, roughly?
You give the chatbot the documents that hold the answers. You set down how it should behave: answer only from those documents, always name the source, and refer on when the answer is missing. Then you publish it in Microsoft Teams, where employees already spend the day. Microsoft offers Copilot Studio for this, a low-code environment for building such assistants. Microsoft calls them agents, and they can help employees and customers through Teams and websites, among other places (Microsoft, Copilot Studio overview).
If the documents are stored in SharePoint, the chatbot works with the employee's own sign-in. It only shows what that employee is allowed to see (Microsoft, Knowledge sources summary).
At Hello Growth we tried this ourselves with a fictional HR handbook of twenty pages. We built an assistant in Microsoft Copilot Studio and made it available in Teams. After that we could ask questions such as "What happens if I fall ill during my holiday?" and "How much leave do I get if I work 24 hours?". It was a test, not a client project.
What makes an AI chatbot reliable enough for your organisation?
A chatbot that works in a test is not yet a chatbot an organisation can trust. The difference is in the set-up:
- which knowledge the chatbot may use, and who keeps it up to date;
- which information each employee may see;
- what it does when the answer is missing, and when it hands over to a person;
- how you prevent invented answers and test that answers are correct;
- how you put it in Teams safely and who manages it afterwards;
- how you measure whether employees really use it.
That is where much of the work is, and it is where we help organisations.
Where are the limits?
An AI chatbot does not replace HR, IT or Finance. Questions about a personal situation, a conflict or an exception belong with a person. There are technical limits too. According to Microsoft, a Copilot Studio assistant in Teams group chats and channels cannot use knowledge sources that require sign-in, such as SharePoint, and when you add it to Teams, data may flow outside your own compliance and regional boundaries (Microsoft, Connect and configure an agent for Teams and Microsoft 365). Have your IT team and data protection officer assess that beforehand. More on what AI may do on its own is in Using AI agents safely.
What is a good next step?
Think of the questions that come back most often. Which department answers them, and is the answer written down somewhere? If so, there is probably an AI chatbot in it.
Want to work out which internal knowledge in your organisation suits this? Book a conversation. If you first want a shared picture in the team, the workshop Introducing AI in your organisation can help.
Sources
- Microsoft, Copilot Studio overview, Microsoft Learn, last updated 25 September 2026
- Microsoft, Knowledge sources summary, Microsoft Learn, last updated 4 August 2026
- Microsoft, Connect and configure an agent for Teams and Microsoft 365, Microsoft Learn, last updated 17 August 2026
