How to Limit Sensitive Data Exposure from AI Agents
Summary
Nol8 CEO Kelly Herrell recommends mapping AI agents’ data paths and enforcing runtime policies to control what sensitive information agents can access, receive, and disclose.
Key points
- Agents can quickly combine sensitive context from ticketing systems, CRM platforms, shared drives, knowledge bases, and chat history.
- Herrell recommends mapping connections among agents, data sources, models, and tools before attempting a broad redesign.
- He advises measuring sensitive data flows, then applying runtime controls first on the highest-risk paths.
- Data policies can redact or block sensitive fields per agent and role while allowing other authorized data through.
- Authentication identifies an agent and authorization governs where it can go; data governance determines what information should cross a boundary.
- Herrell argues that enforcement in the data path is more reliable than controls embedded in each agent’s code, which depend on developers implementing them.
Article Details
- Topic
- Securing enterprise data access and disclosure in AI agent workflows