An FI plans and implements robust controls covering the whole life cycle of each AI use case, system or model, from inception to retirement, assigns clear roles across business and functional units, and reviews the controls regularly for newer AI technologies. Controls may be applied proportionately to the assessed risk materiality of the use case; where practical constraints exist, for instance inadequate disclosure by a third-party AI provider, the FI identifies the resulting risks and puts mitigants in place such as limiting the AI's use, and confirms residual risk remains within appetite. Partial deployments such as pilots or phased rollouts may need adjusted controls, governed by clear policies and procedures covering deviations, for example time and user limits, success criteria, conditions of use, close monitoring of usage and outputs and compliance with the limited scope.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.