EY

As a trusted provider of financial and tax services, the EY Global Tax team processes, manages, and protects huge volumes of data so they can gain insights to help thousands of clients around the world thrive in a rapidly changing and unpredictable business environment. To focus those efforts even more precisely, while addressing security, the EY Global Tax team previewed Microsoft Copilot for Microsoft 365 and developed a plugin to evaluate the ability to extend the capabilities of Copilot to fit the Tax organization’s specific, internal needs. The EY Global Tax team built a proof of concept of the plugin on a developer tenant provided by Microsoft. The goal is to use Copilot to add an AI-powered productivity layer to Microsoft 365 apps. This productivity layer will allow authorized users to query specified data sources in their natural language to generate a single, unified view of all relevant information—and all within security and compliance guidelines. Once the plugin for Copilot is fully deployed, the EY Global Tax team expects to spend less time hunting for information and more time using the latest, most relevant data to drive smarter business decisions for itself and its clients.

EY brings more data into focus with Copilot for Microsoft 365

In the past, the sheer volume of data involved in client engagements resulted in a long lag time between accessing data and developing trends. EY Global Tax is looking to prove whether using Copilot together with Teams will help EY professionals build broader insights much faster.

That’s the daunting task facing the EY Global Tax team.

The first step in generating those insights is to bring the internal EY data from many sources and geographic areas into a single, unified view. Historically, EY Global Tax executives had to wait for internal data to be cleaned up, accessed centrally, and then pulled into a Microsoft Power BI report. That process could take a week or two, so by the time the data was ready, it was already at least two weeks old. If an error was found, the data had to be sent back to the originator to find the source of the error, correct it, and send the data back, creating more delay.