Can you believe it’s been over a year since Microsoft announced its partnership with OpenAI? Within that time, we’ve been gifted with an entirely new vocabulary: Large Language Models (LLMs), prompting and grounding, trainable classifiers and more.
On the product side, there are new solutions centered around Copilot for Microsoft 365 and Azure AI Studio. If you’re expected to take action on AI, it can be difficult to sort through a landslide of information to make the right decisions for your organization.
Understanding the distinction: Azure AI Studio vs. Copilot for Microsoft 365
There are many misconceptions about Microsoft’s generative AI products — as one of Microsoft’s largest partners, we’ve heard it all. And we’d like to help clarify the difference between Azure AI Studio and Copilot for Microsoft 365 and their respective use cases.
Let’s start with what these two things are:
- Azure AI Studio wraps together Azure AI Infrastructure, Machine Learning, Cognitive Services and OpenAI Service to provide everything that’s needed to build AI solutions in one place.
- Copilot for Microsoft 365 is a generative AI tool that is integrated with your data in Microsoft 365 and productivity apps like Outlook, Word and more to provide you with an AI assistant.
AI implementation: Two unique paths
While they are both using AI, these solutions are not interchangeable and don’t do the same things. Creating a solution in Azure AI Studio requires you to build the infrastructure and code, provide data and then train the model yourself. The outcome is a customized solution that responds to prompts from a specific set of data that is trained over time. On the other hand, Copilot for Microsoft 365 uses content already available in your tenant, so there is no need to build infrastructure or code, but it is not trained and does not learn anything from your data. Because Copilot for Microsoft 365’s source data operates within the Microsoft 365 Trust Boundary, every user has access to something different, which limits the function of the LLM strictly to natural language processing.
Watch the video to hear from Insight Director and Distinguished Engineer Joe Flynn as he unpacks how Insight and Microsoft join forces to drive more modern workplace ROI from your Microsoft investments.
How Copilot for Microsoft 365 and Azure AI learn and give you answers
“Copilot for Microsoft 365 does not learn from your data” is probably the number one misconception we hear about the difference between it and Azure AI solutions. Think of Copilot for Microsoft 365 and Azure AI as two different nine-year-old children who both have basic reading and comprehension skills. Let’s call Copilot for Microsoft 365 Child A. Child A is given a giant, generalized textbook and then is asked to use that textbook to answer questions. Child A has reading comprehension skills and can pick out key words and things that might fit together — but you will have to be very specific about what you need for them to give you the correct answer. Furthermore, the textbook you give them will have to be organized in a way that makes sense to the child.
Child B, a custom solution built using Azure AI Studio, has the same reading and comprehension skills. But instead of providing a generalized textbook, you give Child B a textbook on a specific subject that you use to teach the child. When you ask questions, they provide answers based on the textbook and what you have taught them. They learn more from the knowledge you share as time goes on; they learn from mistakes and can even make connections between topics, eventually interacting as an expert. In this way, Copilot for Microsoft 365 is a general assistant, whereas custom solutions built with Azure AI Studio can work to become experts, each with their own use cases.
Examples of Copilot for Microsoft 365 in daily productivity
Copilot for Microsoft 365 can assist knowledge workers with their day-to-day activities and make them more productive. Below are just a few of the basic use cases for Copilot for Microsoft 365 that anyone with access to a license can get started with in productivity apps right away. Keep in mind that Microsoft is continually adding Copilot capabilities to its solutions and can be found in Power Platform, Power BI, Dynamics 365 and more.
Examples of Azure AI Studio in daily productivity
Use cases and possibilities for building solutions with Azure AI Studio are limitless. We always advise our clients to begin with an evaluation of your organization’s needs, but below are a couple of common use cases:
- Smart Virtual Agents can automate and enhance call center operations. For example, your customer service agents can improve customer experience by focusing on resolving complex issues while service bots handle common questions.
- AI models can be leveraged for Enhanced Search Capabilities by processing large datasets for interactions using natural language. Imagine how great it would be if your employees could easily find information on complex financial data, inventory levels, healthcare benefits and more.
What you need to consider
Here are a few more things to take into account when evaluating Copilot for Microsoft 365 and Azure AI Studio for your organization:
- Microsoft announced the availability of Copilot Studio, which is a low-code development tool that will allow you to refine Copilot responses, among other capabilities such as low-code creation of Copilot instances. Think of the refinement capability as the equivalent of telling the nine-year-old the chapter in which the answer to your question is located. It will get them closer to the correct answer but is still not a stand-in for an expert.
- Just like nurturing a nine-year-old to eventually hold a doctorate on a particular subject, getting your solution developed using Azure AI Studio to operate indefinitely at an expert level requires effort. This includes maintenance of infrastructure, data models, GUIs and more.
- Remember that old anecdote “garbage in, garbage out” (GIGO)? This applies to both Azure AI Studio development and Copilot for Microsoft 365. This is much easier to accomplish with datasets that can be controlled, in which case planning for custom-developed solutions with Azure AI Studio is mandatory. Copilot for Microsoft 365 is a bit more complex. We’ve been telling our clients for years about best practices for content and data storage in Microsoft 365; now is the time to employ technical and governance best practices — and educate users on why data hygiene is more important than ever.
As you think through your options, Insight can help.
From readiness assessments to adoption, our team shows clients how to master everyday AI in their organizations and get the most from their investments. Learn more here.
Start your AI adoption journey.
Insight’s deep expertise in Microsoft and AI help organizations get more AI from their AI initiatives.