A plausible AI suggestion is not permission to act.
An operational change has consequences beyond the model response. Teams need evidence, constraints and explicit authority before a suggestion becomes work.
Use intelligence to support a bounded decision while keeping approval and execution visible to the person responsible.
Define a narrow task and its inputs. Evaluate recommendations against representative cases, then separate the candidate response, operator approval and downstream action acknowledgement.
Core design considerations
Task boundaries
define the question and permitted context.
Human review
expose options, uncertainty and constraints.
Controlled execution design
specify approvals, scoped interfaces and recovery.
A workflow worth proving
Who can see, decide and act?
Validate model data handling, approval authority and permissions at execution time. Include adversarial inputs, uncertain outputs and failed actions in evaluation.
Fit the implementation to the environment.
Evaluate model endpoints and workflow interfaces against the intended task. Let demonstrated reliability and control determine the automation scope.
Agree what success would mean.
Evaluate unsafe suggestions, inappropriate approvals, failed requests and successful acknowledgements alongside the time saved on routine review.
Logistics: move from an exception to a reviewed response. ↗