Building an AI application might sound like a task for skilled developers secluded in rooms full of monitors, tapping into the arcane lore of deep learning and cloud computation. However, with tools like Microsoft Copilot Studio, the reality is far more accessible and collaborative. Today, let’s walk through the creation of an AI agent that serves as an IT support assistant. By the end of this post, you’ll see that constructing an efficient AI agent is less about arcane knowledge and more about thoughtful, systematic integration of accessible technology.
Let’s start by setting the scene. Imagine you’re part of an IT department inundated with the same questions day in and day out: “How do I reset my VPN?” or “What to do when my email stops syncing?” Automation through an AI agent can relieve your team of this repetitive burden, allowing them to focus on more complex issues.
This video is from Anders Jensen.
Firstly, navigate to CopilotStudio.microsoft.com and initiate a new AI agent. We’ll name ours “IT Support Agent” and give it an icon for easy identification among other agents you may create in the future. The primary function of this AI agent will be to assist users with common IT requests and issues by leveraging internal knowledge sources rather than scouring the internet.
The next crucial step is to select the appropriate model for our agent. While experimental models tempt with cutting-edge features, they lack stability, which is critical for our purposes. Opting for a robust, production-ready model like DBT5 chat ensures reliability.
To provide our AI the necessary information, we’ll integrate a knowledge base; in this case, a 20-page IT service document stored on OneDrive. This ensures that any updates to the document automatically refresh the agent’s responses, keeping the support relevant and accurate without manual intervention.
However, merely having the knowledge isn’t enough. The agent must also refer to this internal knowledge exclusively when resolving queries, which we ensure by adjusting its settings to disable web search and general knowledge models, refining its source to our specific documentation.
As our AI navigates inquiries, it’s bound to encounter questions outside its scope. For these instances, we configure the agent to politely decline providing an answer, reinforcing its role as a dedicated IT support entity. This specificity helps maintain clarity and focus in the interactions it handles.
Moving beyond responding to queries, I integrated the capability for our AI to initiate IT support tickets when issues exceed simple answers and require direct human intervention. A user’s inquiry about resetting a Salesforce password, for example, triggers a pathway that offers to create a support ticket if the internal documentation doesn’t cover the query.
Implementing this feature involves creating ‘Topics’—specific response pathways that our AI can employ based on the given situation. Furthermore, through integration with tools like Microsoft Planner, once a user confirms the need for a ticket, the AI can automatically generate a task in a designated Planner board, ensuring the issue is queued for IT’s attention.
Think of it like this: Our AI agent isn’t just a virtual assistant lurking in the digital shadows of a network. It’s more akin to a triage nurse, equipped to address the straightforward cases and knowledgeable enough to escalate the more challenging scenarios to the right channels effectively.
Finally, embedding this agent into a real-world application involves linking it with communication platforms commonly used within organizations, like Microsoft Teams and Microsoft 365 Copilot. This integration ensures that accessing the AI’s capabilities is as seamless as sending a message to a colleague.
And there you have it. What begins as a dive into the capabilities of Copilot Studio ends up demonstrating a profound shift in how we approach workplace automation. By combining clear objectives with strategic tools, creating an AI agent becomes a manageable, even enjoyable, endeavor. The key takeaway? Empowering your IT support through AI isn’t just about technology; it’s equally about understanding and designing thoughtful interactions.
