Why Canonical Knowledge Is the Foundation for Enterprise AI ft Joe DosSantos, VP at Workday

About this episode

Joe DosSantos discusses the importance of canonical knowledge and data governance for effective AI deployment in enterprises.

Before enterprises can deploy AI agents that actually work, they need something most organizations don't have: a single, authoritative source of truth. Joe DosSantos, Workday’s VP of Enterprise Data and Analytics, joins Robb and Josh for a wide-ranging conversation about canonical knowledge, the semantic layer, and why data governance, a concept from the 1990s, has suddenly become essential for AI deployment. Large language models are predictive engines modeled to anticipate what users probably likely mean. For B2C applications where multiple interpretations are acceptable, this works fine. But enterprises need deterministic truth, not probabilistic guesses. The trio outline a solution in three layers: establishing canonical knowledge, building a semantic layer to translate between human definitions and machine-readable formats like YAML, and using LLMs as an interface to deterministic back-end systems. For leaders evaluating AI investments, this episode clarifies what actually needs to be built before agents can deliver value: not flashy use cases, but the unglamorous, essential work of data governance and semantic translation. ---------- Support our show by supporting our…

People in this episode

Guest: Joe DosSantos

Topics covered

• AI
• data governance
• enterprise technology
• semantic layer
• canonical knowledge

Keywords

• canonical knowledge
• semantic layer
• data governance
• large language models
• deterministic truth
• B2C applications
• AI investments

Sponsors

OneReach.ai

Mentioned in this episode

Products: GSX, OneReach.ai

Books & works: Age of Invisible Machines

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