Assess whether monitoring detects drift or only outages (95dc14)

SITUATION Enterprise AI risk register with missing owners arrived with a batch job still calling a retired endpoint for model-deprecation manager. That is a AI Governance Layer Lifecycle and Accountability decision on monitoring detects drift or in a bank running three models on the same credit file.

DECISION Model-deprecation manager in a bank running three models on the same credit file must choose Monitoring detects drift / Only outages using enterprise AI risk register with missing owners after a batch job still calling a retired endpoint.

HYPOTHESES TO TEST 1. A batch job still calling a retired endpoint is noise around an already-controlled Lifecycle and Accountability process in a bank running three models on the same credit file, given enterprise AI risk register with missing owners. 2. A batch job still calling a retired endpoint is the event in enterprise AI risk register with missing owners that forces Monitoring detects drift for model-deprecation manager under AI Governance Layer. 3. Enterprise AI risk register with missing owners shows a one-file miss after a batch job still calling a retired endpoint, not a Lifecycle and Accountability program failure. 4. Enterprise AI risk register with missing owners cannot decide monitoring detects drift or yet after a batch job still calling a retired endpoint; hold is the only AI Governance Layer close a bank running three models on the same credit file can defend.

ANALYSIS REQUIRED 1. Map the control-plane score in enterprise AI risk register with missing owners to the policy gate model-deprecation manager can enforce. 2. Name the override that would let monitoring detects drift or proceed without a silent bypass. 3. Test whether a batch job still calling a retired endpoint changed routing, logging, or human-in-the-loop on the live agent path. 4. For this AI Governance Layer Lifecycle and Accountability file, read enterprise AI risk register with missing owners against a batch job still calling a retired endpoint and write the one fact that would move monitoring detects drift or for model-deprecation manager.

RECOMMENDATION Choose Monitoring detects drift / Only outages on this AI Governance Layer / Lifecycle and Accountability packet (enterprise AI risk register with missing owners after a batch job still calling a retired endpoint). Lead with the AI Governance Layer option enterprise AI risk register with missing owners can support after a batch job still calling a retired endpoint, then the two facts that force it, then the Monday action for model-deprecation manager in a bank running three models on the same credit file.

COMMAND RETURNS - Bottom-line AI Governance Layer option on monitoring detects drift or, then the evidence in enterprise AI risk register with missing owners, then the action for model-deprecation manager - Hypothesis scorecard against enterprise AI risk register with missing owners: supported / rejected / untestable - Regulatory or exam hook Lifecycle and Accountability would cite - Lifecycle and Accountability finding in enterprise AI risk register with missing owners that a second reviewer can re-perform