Invisible Machines podcast by UX Magazine

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

Jan 29, 2026
Joe DosSantos, VP of Enterprise Data and Analytics at Workday, leads data infrastructure strategy. He discusses why a single authoritative source of truth matters for enterprise AI. Short conversations cover canonical knowledge, semantic layers that translate human meaning into machine-readable formats, and reviving data governance as the unglamorous foundation for reliable AI.
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INSIGHT

LLMs Predict Language, Not Truth

  • LLMs are predictive engines that guess likely language, not guaranteed truth.
  • Enterprises need deterministic, governed facts rather than probabilistic inferences.
ADVICE

Verify Facts Before Interpretation

  • First verify the facts before building interpretation on top of them.
  • Use a canonical source so inferred analysis rests on accurate, agreed data.
INSIGHT

Clarify Ambiguous Queries With Semantics

  • LLMs should ask clarifying questions when prompts are ambiguous.
  • A semantic layer and defined corpus let models route queries to deterministic sources.
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