Data challenges have always undermined everything from basic reporting to advanced data science. Now AI is introducing new challenges, from probabilistic outputs to opaque decision paths, that traditional data practices were never designed to govern. At the same time, it's forcing a fresh look at legacy problems, exposing which data issues AI can now work around, and which it dangerously amplifies. Explore how closing the real data readiness gap comes down to knowing where AI should be leveraged, where it should be constrained and where governance must still draw hard lines to protect trust, accountability and the business itself.

What you'll walk away with:
• How to tell which legacy data problems AI can work around, and which it dangerously amplifies
• Where to leverage AI on imperfect data, and where to constrain it
• Where governance must still draw hard lines to protect trust and accountability