Source: Fable (Claude) analysis of a discussion and my own research

I like this definition. “That’s the same structural question the agentic AI governance work circles — capable systems doing consequential work below the threshold of human attention”

It’s worth keeping. The phrase captures why agentic AI governance is harder than model governance: the risk isn’t capability, it’s unattended capability. Regulators know how to audit a decision; they don’t yet know how to audit ten thousand small decisions nobody watched.

Banking is the cleanest test case. Payment routing, fraud scoring, reconciliation, treasury sweeps — all already run below the threshold of human attention, and agentic AI widens that layer from rule-following to judgment-exercising. The governance gap is that accountability frameworks (SMR in the UK, OSFI E-23 here) assume a human somewhere made the consequential call. When the consequential call is an aggregate of sub-threshold actions, there’s no natural point of accountability to attach.

If you want it for Bankwatch, the Tchaikovsky hook works well — fiction noticing the problem before regulation does. Elder Race and Green City Wars as two variants: the misperceived intelligence and the invisible one.

#invisible #regulation #intelligence #misperceived #governance