Securing the agentic enterprise with data lineage
A sales representative asks an AI agent for customer pricing, and the agent pulls data from multiple sources: restricted pricing systems, internal communications, and archived quotes.
A sales representative asks an AI agent for customer pricing, and the agent pulls data from multiple sources: restricted pricing systems, internal communications, and archived quotes.
The short version
- The output looks accurate to the agent, so a second agent uses the data to draft the proposal for the sales rep.
- Data lineage is the new security perimeter, providing the visibility needed for governance, accountability, and trust, without impeding AI adoption at scale.
- This scenario illustrates why AI governance needs to evolve, rapidly and dynamically.
What happened
In short, AI security isn’t a tool problem; it’s a data visibility problem. Consequently, traditional security approaches built solely around applications, systems, networks, or endpoints are no longer sufficient.
Why it matters
Securing agentic AI at scale requires understanding how data moves.
Summary by Nerd News Network. Read the full article at MIT Technology Review — AI via the links above and below.