Core question
How much independence should an AI agent have, and how do we control it?
Short answer
Only as much as the consequence of being wrong justifies. Grant the least access the job requires, put approval points where actions become hard to reverse, log what it does, and keep a way to stop it. Capability should never automatically become permission.
Autonomy is a spectrum rather than a switch. At one end, the system gathers information and prepares a recommendation for a person. Further along, it handles routine cases on its own and escalates the exceptions. At the far end it acts with little supervision. The right position depends entirely on what happens when it is wrong.
Four questions place it. What is the damage if this goes wrong? Can the action be reversed? How quickly would anyone notice? And what can the system reach, as opposed to what does it need to reach?
That last one is the practical control. If an agent only needs to read certain information, do not give it the ability to change that information. If it drafts a customer message, decide deliberately whether a person approves before it sends. If it updates records, define which records and under what conditions. Least necessary authority is not a technical nicety. It is the single cheapest way to bound the failure.
Monitoring matters as much as permissions, particularly for systems that run continuously rather than when someone opens them. Logs, exception alerts, an approval queue, and a defined escalation path are what turn autonomy into something you can be accountable for. Autonomous systems should not become invisible systems.
And for anything with real operational reach, you need a way to suspend it fast. Start with less independence than the technology permits and increase it when you have evidence, not when the vendor demonstration was persuasive.