Workday faced a choice: crank out hundreds of purpose-built agents, each with its own interpretation of business terms, or build one shared semantic layer that defines meaning once for everyone. The answer was clear: just like teams shouldn't argue about what "revenue" or "churn" means, AI shouldn't interpret these terms differently across tools.
Key takeaways:
Building custom semantic layers for each AI agent creates the same mess as having 900 different dashboards
Business definitions like "churn," "renewal," and "attrition" need formal, standardized meanings AI can use
Semantic layers shouldn't live inside BI or governance tools — they sit at the crossroads where all tools access them
Contextual meaning needs to be understood consistently by everyone calling it from different platforms
This unified approach frees teams to focus on what AI does best: understanding unstructured data and answering "why"
