When to use Copilot Studio?
With the introduction of M365 Copilot, Copilot Studio has also seen increased interest. The platform has evolved significantly in recent years and offers numerous features that go beyond the capabilities of the original Power Virtual Agents. But with the variety of AI and agent technologies available, the question arises: When is Copilot Studio the right choice? In this post, you’ll learn in which scenarios Copilot Studio makes sense and when it might be better to use other technologies.
When should you use Copilot Studio?
Copilot Studio is especially a good choice when an interactive, dialog-based solution is needed. The tool’s strength lies in natural language processing, seamless integration into the Microsoft 365 environment, and its ease of creation and maintenance. In the following use cases, Copilot Studio is usually a good choice.
Simple search assistant
Most customers want to use Copilot Studio to create a search assistant for their employees. There’s generally nothing wrong with that. However, as explained in my post on SharePoint search, the quality of the underlying search and data often leaves much to be desired. Therefore, Copilot Studio is particularly suitable when dealing with a manageable number of files to search through. A simple SharePoint site or MS Team is an appropriate size to ensure that the response quality provides added value. Copilot Studio is primarily a tool to formulate answers from existing information. Finding the right information is not its core function. Based on experience, the quality of results decreases noticeably with a medium two-digit number of documents or with very long documents (over 20 pages).
Answering FAQs
A common use case for Copilot Studio is providing predefined answers to frequently asked questions. The structure of Copilot Studio still stems from the Power Virtual Agents era and is tailored to this type of use. Although this approach may initially seem labor-intensive, it quickly provides added value for users. In many areas, employees can be significantly relieved if the agent can reliably answer the 20–30 most frequent questions. An agent that covers a topic broadly but cannot answer reliably offers no added value or won't be used at all. This approach is suitable, for example, in IT support or HR, where the same questions are asked repeatedly. Implementing such a chatbot can optimize communication and increase efficiency.
Creating content
There are many use cases in companies where content needs to be created for internal and external purposes. A common example is the creation of social media posts in the marketing department. In these cases, the content often needs to meet specific criteria, such as style, length, and formatting. Copilot Studio can create various types of content based on keywords, either independently or in combination with AI Builder prompts. The result usually still needs editing, but when a large volume of content needs to be produced, generating a first draft already provides great value.
Chat interface for business applications
Another strong use case for Copilot Studio is providing a chat interface for business applications and processes. This adds value when chat offers a better or faster way to provide information than a form-based user interface. For example, a Copilot in a business application can guide employees through complex processes, validate inputs, or provide information. Instead of just filling out a form, the agent can provide the user with additional information. A direct integration with MS Teams can speed up the process since the app doesn't need to be searched for and loaded.
Executing tasks
Following on from the previous point, Copilot Studio is also suitable for executing certain predefined tasks that can be quickly initiated via a chat interface. Classic examples include a vacation tool that receives leave requests and forwards them to the HR system or quickly populating a to-do list. This saves time and reduces the number of manual steps. These tasks can either be implemented directly in Copilot Studio, or the agent can provide the user interface to trigger Power Automate flows.
Using as an autonomous agent
Recently, the ability to create autonomous agents with Copilot Studio has come into focus. The agent can independently decide which actions to take. This is particularly useful when the agent needs to search for information that it then processes in a subsequent action. Whether the agent is suitable for this depends on the size of the data set (see search above). Another aspect where Copilot Studio can play to its strengths is making decisions that are hard to automate or formalize. For example, an agent can make decisions based on predefined policies or independently process data from various sources.
When should you reconsider using it?
We've now seen some use cases where Copilot Studio is a good choice. However, we’ve also touched on areas where there may be difficulties, and you should reconsider using Copilot Studio. These mainly fall into two categories: large data volumes and automation.
Automation
Although Copilot Studio offers the ability to automate processes using autonomous agents, one should proceed with caution here. If the primary goal is process automation, Power Automate is often the better choice. Especially through the integration of AI Builder prompts, complex tasks can be automated and combined with generative AI. AI Builder prompts are a powerful tool for extracting, analyzing, and summarizing text-based information. This includes making decisions based on predefined criteria and information. Copilot Studio, on the other hand, is especially suitable when decisions are hard to formalize or when information needs to be found.
Improving search
Many companies hope that an AI-powered bot can help their employees find information more effectively because their current search isn't working well. The focus of generative AI in agents is primarily on providing information in natural language. However, Copilot Studio is not designed to efficiently search large data sets. Instead, it relies on existing search engines. This means Copilot Studio cannot improve the existing search.
With more than 50 files or very large documents, the search often fails to deliver satisfactory results if the data has not been extensively cleaned and structured. If users are already having trouble finding information in SharePoint or other data sources, a Copilot Studio agent will not solve these problems. In such cases, specialized solutions like Azure OpenAI in combination with AI Search are often the better choice. These technologies offer more options to tailor output and search to the specific use case. However, Copilot Studio allows agents to be built so quickly that after just a few hours, you can usually tell whether the given use case will work or not. So, it’s worth getting started to see how far you can get with Copilot Studio.
Conclusion
Copilot Studio is a tool that allows you to quickly and easily create chatbots and autonomous agents. It is more suitable for some use cases than others. In my experience, Copilot Studio is particularly well-suited for answering FAQs, creating content, and serving as a chat interface for business applications. Additionally, it can be used to execute simple tasks and as an autonomous agent in the use cases described.
Copilot Studio reaches its limits mainly with large or complex search queries. You should be aware that Copilot Studio only provides reliable answers after the data has been cleaned and structured. For automation processes that don’t involve search, Power Automate is usually the better choice.
Ultimately, choosing the right technology depends heavily on the specific use case. Those who know and use the strengths of Copilot Studio wisely can optimize valuable processes in companies and drive digital transformation.
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