“Let AI take care of it” leaves important questions unanswered: take care of what, using which information, how far may it go and who checks?
An agent combines an objective, state, tools, a working cycle, limits and evaluation.
The cycle that gives it purpose
Observe → decide → act → verify. Verification matters just as much as action. If a system makes recommendations but never checks the outcome, we do not know whether it helped or merely generated activity.
In a service team, the objective might be to reduce overdue requests. The state includes open cases and due dates. Tools let the agent read authorized records and prepare drafts. A boundary may be clear: it proposes replies, while a person approves anything sent to customers. Evaluation asks whether cases were resolved without sacrificing quality.
Autonomy in proportion to risk
- It can do independently: organize information, detect duplicates, flag exceptions and draft summaries.
- It can propose: priorities, drafts and alternatives supported by evidence.
- It must escalate: external messages, changes to commitments or prices, and decisions that are hard to reverse.
Less autonomy does not make a system less useful. The design decision is where human judgment changes the risk and how to measure whether the whole process works better.