An information barrier is a control that prevents material non-public information from moving between business units that are required to stay separate — most commonly between an investment bank's advisory side and its trading and research functions. The obligation is long-standing and well understood in email, chat and document systems. It is largely unimplemented in AI.
The AI problem is structural. A shared assistant, a shared vector index or a shared cache is a channel between everyone who can reach it. A banker asks a question about a live deal; the content is embedded, retrieved or cached; a colleague on the other side of the barrier asks something adjacent and the system, doing exactly what it was built to do, surfaces it. No one leaked anything. The architecture did.
How it differs from access control. Access control asks whether a person may reach a system. An information barrier asks whether this content may reach this person, and the answer depends on which deal, which desk and which day. It is a content-and-identity decision made per request, not a permission granted once.
Why the cache is the exposure people miss. Deduplication and semantic caching are both, by design, mechanisms for showing one person something produced for another. Any AI cost-optimisation layer deployed across a barrier needs a partition that honours it, or the saving comes out of the control.
Smartflow enforces barriers at the AI gateway, using LDAP/AD group identity combined with real-time content classification.
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