Give AI a boundary. And an owner.
Decide what it may do, what it must explain, and when a person takes over.
Useful autonomy has edges.
An AI system needs an explicit job. Which sources may it read? Which actions may it take? What requires approval? Where should it stop?
These are operating decisions. Make them before an impressive demonstration turns into a process that people depend on.
Keep the evidence close to the answer.
For consequential work, an answer should carry enough context for someone to challenge it: the source, the definition, the relevant time period, and any material uncertainty.
Access should follow the person and the purpose. An assistant should not become a new route around the controls your organization already relies on.
Design the handoff.
Name the person responsible for the outcome. Give them a way to review, stop, and correct the system. Test ordinary cases, edge cases, and failures.
Our standard is practical: can the people responsible understand what happened, decide whether it was acceptable, and intervene when it was not? That is the foundation for trust.
When access changes, what happens to the answers already in circulation?
A working prompt for your team or an approved AI tool. It asks for evidence, names the open decisions, and leaves room to disagree.
A KimberLyte perspective.
Data, AI, and the human side of change.