AI adoption is no longer limited to approved platforms or formally sponsored projects. It is appearing across SaaS applications, developer tools, productivity workflows and informal business processes, often faster than security, compliance and governance teams can track.
This session examines the gap between where organizations believe AI is being used and where it is actually influencing work. The session will explore what AI usage looks like in a real enterprise environment, why traditional visibility controls often miss it and how unmanaged adoption can create risks around data exposure, intellectual property, compliance, model dependency and operational accountability. Rather than treating the issue as a reason to slow innovation, the session focuses on practical ways to discover usage, assess exposure and introduce control.
Attendees will learn how to start building an inventory of AI touchpoints, evaluate risk by workflow and data type, and apply governance in a way that supports responsible adoption. The session will provide a pragmatic path for improving visibility and control without blocking the productivity gains that are driving AI use across the business.
