80% of organizations say their AI agents have already taken unintended actions — and most still have no identity governance layer around them.
AI agents are being deployed into production pipelines right now — accessing systems, executing tasks, and touching sensitive data at machine speed with no human in the loop. That’s not a future risk. It’s the current state for most enterprises, and the identity controls haven’t caught up.
What this webinar covers
This session goes straight to the operational question: how do you govern AI agents the same way you govern human and non-human identities — without slowing down the automation that makes them valuable? The agenda covers:
- Centralized AI workforce management — Managing AI agents from a single platform alongside your human and NHI workforce.
- Platform-native onboarding — Integrating agents from AWS Bedrock AgentCore, Salesforce Agentforce, Snowflake Cortex, GCP Vertex AI, Azure AI Foundry, Microsoft Copilot Studio, ServiceNow, and Databricks directly into your identity governance layer.
- Risk controls that scale — Assigning human owners, enforcing structured succession, and running access reviews across the full AI agent lifecycle.
Why it’s worth an hour of your time
The identity perimeter has already expanded to cover service accounts, bots, and API keys. AI agents are next — and the governance model is different enough from NHI that practitioners need a clear framework before they’re dealing with an incident. This session is that framework.
📌 Source: BrightTalk — Mission Security: Deploying AI Agents in Production