From Early Warning to Action: Managing Risk in Federal AI

As government agencies are moving AI from experimentation into operational systems, new challenges for security, oversight, and mission assurance are moving in. Traditional monitoring can reveal whether infrastructure is running, but it may not be able to show when an AI model begins producing unreliable answers, an AI agent takes an unexpected action, or sensitive information is exposed. Agencies that rely on AI to support critical services and government operations need to understand not only whether systems are available, but also how they behave and whether their outputs can be trusted.

This webcast dives into how agencies can use AI and agentic observability to catch issues early and safeguard mission success. Government and industry experts will discuss how this approach creates a foundation for governed autonomy in federal environments, learn how to spot risks such as inaccurate outputs or data exposure, investigate incidents more quickly, and keep people involved in critical decisions. Attendees will hear from experts on how agencies can maintain auditable human-in-the-loop oversight, and keep the operational costs of scaling Agentic AI visible and controlled.