Microsoft's Quest for AI-Ready Data: A Foundation for Enterprise Success

At Microsoft, data is treated as a critical business asset that powers reporting, supports decision-making, and helps leaders understand the organization. However, with the rise of agentic AI, high-quality data has become even more crucial for supporting agents, automation, and employee decision-making.

The shift towards AI models that can produce sophisticated summaries, answer complex questions, and help employees work efficiently has led Microsoft’s teams to ask a new question: What does it mean to have data that’s fully AI-ready? Measuring data quality is just one part of the answer.

According to Naval Tripathi, principal engineering manager at Microsoft Digital, ‘World-class AI agents start with AI-ready data, with the right foundation. That means more than simply making data available.’ This requires quality, governance, and consistent standards so that AI systems can understand the data, trust it, and use it effectively.

Microsoft Digital is creating a repeatable framework for AI-ready data by combining governance, discoverability, semantics, context, ownership, lineage, security, and quality into an overall foundation. This framework helps AI systems interpret enterprise data and use it appropriately.

The team has learned that readiness can’t be treated as a one-time cleanup project. ‘We decided to focus on continuous data readiness,’ says Aishwarya Dinde, senior software engineer at Microsoft Digital. ‘You really can’t say,