July 16, 2026 | 11:00 AM EDT | 4:00 PM BST | 5:00 PM CEST
Your AI team wants the data. Your instinct says: "not so fast." Who's right?
It's the question landing on every privacy desk: can we actually use this dataset to train or power AI — and can we prove it if a regulator asks? The old answer ("it's anonymized") no longer holds. Regulators now expect contextual, quantitative proof that re-identification risk is genuinely low, and "we ran it through a checklist" won't survive scrutiny.
The good news: the same pressure that's raising the bar is also making it possible to clear it at scale. Join OneTrust Data Guidance for this upcoming session, where we will show how privacy teams are using LLMs to turn slow, subjective data reviews into fast, defensible, repeatable decisions — so you become the team that unblocks responsible AI instead of the one that says no.
