Microsoft has introduced a new approach to evaluating its AI-powered assistant, Microsoft Copilot, at an enterprise scale. The challenge lies in creating test data that mirrors the complexity of real organizations without compromising sensitive information. To address this, Microsoft developed the Industry Evaluation Data Generation Platform, which generates full-scale synthetic enterprise environments using publicly available data sources like O*NET occupational data, online job postings, and SEC filings.
The platform simulates realistic business workflows, allowing Microsoft to identify issues that generic benchmarks might overlook. Safety and privacy are prioritized, with automated content-safety checks ensuring the generated data is free of harmful or personally identifiable material. This approach enables Microsoft to test Copilot's performance without ever accessing customer data.
The evaluation system is built on three core pillars: synthetic enterprise environments, automated query generation pipelines, and structured quality frameworks. These components help ensure that Copilot delivers accurate, complete, and properly grounded responses to user queries. The synthetic environments are dynamic, simulating time-evolving organizations with meeting histories, project timelines, and email threads that develop over weeks.
Microsoft has created three industry-specific synthetic environments: a pharmaceutical setting with regulatory submission workflows, a capital markets environment featuring deal pipelines, and an IT/software company simulating sprint planning. These environments allow for realistic evaluation queries tailored to each industry's specific needs. The automated query generation pipeline further enhances the evaluation process by turning generic query ideas into industry-specific questions, ensuring scalable and reliable testing of Copilot across real-world scenarios.