Data lineage for securing enterprise AI agents, per sponsored MIT Technology Review piece
Overview
A sponsored article from Insights, MIT Technology Review's custom content arm, argues that enterprises need data lineage to secure AI agents.
Lineage means tracking how data is ingested, copied, summarized and reused across systems and agents. The article's example is a sales agent whose pricing data reached a proposal containing restricted and confidential information, with no one able to trace where that data entered the workflow. It says application, system, network and endpoint controls are not enough on their own, and that AI security is a data visibility problem. The article's claims are the sponsor's view and no independent evidence is cited.
Written by AI from the articles below · updated Nov 4, 8:44 AM ET
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The articles in this story. Times are ET.
- MIT Technology Review · AINewsSecuring the agentic enterprise with data lineage
AIThe article argues that enterprise AI agents need data lineage, meaning visibility into how data is ingested, copied, summarized, and reused across systems and agents. It gives an example in which a sales agent's pricing data reached a proposal with restricted and confidential information, and no one could trace where it entered the workflow. The piece says AI security is a data visibility problem, so application, system, network, and endpoint controls are not enough. It is sponsored content from Insights, MIT Technology Review's custom content arm.
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