Summary: Join an interactive roundtable on what it really takes to make your data AI-ready—covering permissions, labeling, lifecycle, and risk. Bring your questions and experiences as we discuss practical governance patterns that unlock AI value.

Outcome: Clear understanding of data readiness requirements for AI initiatives

Takeaway: A data readiness checklist to assess your organization's AI preparedness

Key Discussion Points:

• What 'AI-ready data' actually means in practice
• Data permissions: who can access what, and how AI changes the equation
• Data labeling: classification and metadata requirements
• Data lifecycle: retention, archival, and deletion considerations
• Data quality: completeness, accuracy, and consistency standards
• Risk assessment: what can go wrong with AI and your data
• Governance patterns that enable AI without compromising security
• Compliance considerations: regulatory requirements for AI data use
• Quick wins: where to start improving data readiness
• Peer discussion: challenges and solutions from attendees