human-in-control AI systems
A human-in-control system is not one where a person is nominally available to intervene. It is one where the workflow makes clear what the system can do, what evidence it used, when review is required, and who has authority to make the final call.
( The Detail )
Match review to consequence
Low-consequence internal assistance may need occasional quality checks. Work that affects customers, money, sensitive information, or material decisions needs a tighter review and escalation path. The control should reflect the consequence, not an abstract fear of AI.
How to approach it
Begin with the decision rather than the tool. Name the recurring judgement this affects, the information it depends on, and the person accountable for acting on the result. That framing keeps the first build small enough to inspect and useful enough to matter.
Keep a human review point in the loop until the quality and the failure modes are understood. A system that shows its working - what it drew on, where it is uncertain, and what it deliberately left alone - is one a business can keep running after the initial build.
( Next Step )
Start small enough to review, but on a workflow important enough to show whether a better system is worth building.