AI's first role in the workplace was answering questions. Now it is going a step further: preparing invoice records, sending emails, opening requests, resetting passwords. It no longer just talks; it writes to systems.
The margin of error does not go away
However good language models become, they can misread a document, confuse two similar records or guess with incomplete information. In a system that gives information, the mistake lands in front of a reader and can be caught. In an AI that writes to systems, the mistake turns straight into a record: an invoice with the wrong amount, an email to the wrong person.
What the approval card does
The approval card shows the work the AI has prepared to a person before it is carried out: what will be done, with which data, in which system. The person reads the card, corrects it if needed, then approves or rejects it. As a result:
- The decision stays with a person. AI speeds the work up; it does not take over responsibility.
- Mistakes are caught before they become records. The check happens when it is cheapest.
- "Who approved it?" has an answer. Every action is logged with the person who approved it.
Doesn't approval slow things down?
Designed well, it does not. The card brings everything about the work onto one screen; nobody has to browse several screens. Threshold rules help too: actions below a set amount can be approved in bulk, those above come one by one. A short undo window leaves a final safety margin.
The same rule for agents
For scheduled or event-triggered agents, approval matters even more, because the person who set up the work is not at the screen when it runs. The agent prepares the work, places it in the approval queue, and carries it out once the right person approves.
In Bizz AI products this is not a setting but a core principle: every step that writes to a system comes for approval first.