Everyone’s asking whether their data is AI-ready. Far fewer are asking what that actually means or being honest about what happens when the answer is no. In this on-demand webinar, Atorus experts skip the demos and the buzzwords for an unscripted conversation about a problem most teams are either avoiding or getting wrong.
Aga Rasinska, Christine Kanalis, and Michael Collins bring three different vantage points to a practical look at what AI-readiness really requires and who owns it.
During this session, they discuss:
- What “data as a product” means in practice, and why the buzzword gets in the way
- How to assess AI-readiness as a data quality question
- Why data quality is a continuous process, not a one-time deliverable
- When to use AI and when to wait
- Who owns data quality once AI is in the picture
Watch now for an honest conversation about what AI-ready data really takes and what to do when your data isn’t there yet.