As organizations accelerate their adoption of AI, Information Governance is at a turning point. Many IG programs remain rooted in observational governance—focused on discovering, classifying, and reporting on data risks without meaningfully reducing them. While visibility is essential, it is no longer sufficient. Actionable remediation is what actually mitigates risk.
This session introduces a practical framework for shifting from observational to operational governance, where insights drive automated or semi-automated action. We will explore how modern AI capabilities enable organizations not only to identify sensitive, redundant, or non-compliant data, but to remediate it at scale and in real-time—through defensible deletion, policy enforcement, and lifecycle automation.
Attendees learned how to bridge the gap between insight and action, including:
- The limitations of traditional, observation-heavy governance models
- How AI can operationalize governance decisions safely and defensibly
- Real-world use cases for automated remediation and risk reduction
- Key considerations for trust, auditability, and change management
By the end of the webinar, participants gained a clear roadmap for evolving their governance programs from passive oversight to proactive, measurable impact.
