Securing the agentic enterprise with data lineage

This MIT Technology Review Insights piece describes a scenario in which AI agents pull from restricted pricing systems, internal communications and archived quotes, and a second agent drafts a proposal without human checks, leaving no way to trace where confidential data entered the workflow. It argues that AI security is a data visibility problem, and that securing agentic AI at scale requires data lineage to manage governance, accountability and trust across human, agentic and hybrid workflows.