From AI Risk to Runtime Control

AI governance does not end at approval. In this on-demand session, Bex Evans explores what it takes to move from policy on paper to operational control at runtime, helping teams scale AI faster without sacrificing trust, visibility, or compliance.

As AI agents and copilots multiply across the enterprise, governance teams are under pressure to do more than define principles. They need a practical way to discover what is running, monitor live behavior, detect policy violations, and enforce guardrails in production. This session shows how OneTrust helps organizations close the gap between governance intent and runtime reality.

What you’ll learn

• Why approval-time governance breaks down as AI systems change in production
• How to connect governance policies to machine-readable rules and measurable runtime signals
• Which runtime signals matter most across evaluation metrics, operational health, and observability
• How OneTrust helps discover AI agents, monitor for violations, and trigger enforcement actions
• Why runtime governance is becoming essential for faster, more confident AI adoption

Why this matters now

AI adoption is accelerating, but so are the risks that emerge after deployment. Models drift. Agents change behavior. Sensitive data appears in places it should not. And what looked compliant at launch can quickly become difficult to govern in practice.

Bex breaks down how organizations can build an operational layer for AI governance, translating policy into enforceable controls and creating a continuous feedback loop between runtime evidence, risk signals, and action.

The live audience reinforced just how urgent this challenge has become.

What is driving urgency for runtime governance?

• 32% of attendees said their top priority is the need to scale AI without slowing delivery
• 26% cited sensitive data and security concerns
• 19% pointed to shadow AI and unknown agent usage
• 16% named regulatory pressure

Where are teams getting stuck today?

• 46% said their biggest bottleneck is turning policy into enforceable controls
• 24% said they lack visibility into what is actually running
• 16% pointed to coordinating owners and reviewers fast enough
• 14% cited monitoring for drift, safety, and PII exposure

In the session demo

Bex demonstrates how OneTrust helps teams:

• Discover AI agents registered across cloud environments such as Azure and AWS
• Monitor live runtime signals tied to safety, fairness, usefulness, reliability, and PII handling
• Detect violations against defined policy thresholds
• Enforce guardrails with clear remediation paths and auditable evidence
• Build a governance feedback loop that supports continuous oversight in production