Designing the Approval Loop: A Healthy Boundary Between AI and Human Decisions
The principle "AI recommends, human approves, automation executes" is easy to say but needs deliberate design to actually work. Without explicit boundaries, AI ends up either given too much authority or too little to be useful.
The first step is defining scope: which decisions AI is allowed to prepare, and which must always go through a human. This scope needs to be specific — not "AI helps with marketing" but "AI drafts follow-up messages for leads scoring above 70".
The second step is making sure approval happens at a point that doesn’t slow things down. Approval that’s too heavy pushes teams back to manual work. Ideal approval is a single click backed by full context.
Finally, every approved or rejected decision needs to be logged. That log becomes the evidence for expanding or narrowing the AI’s scope going forward.
- ▸"AI recommends, human approves, automation executes" needs a specific scope, not just a general principle.
- ▸Clearly define which decisions AI is allowed to prepare and which must always go through a human.
- ▸Approval should take one click with full context — not a heavy, slow process.
- ▸Every approved or rejected decision needs to be logged, to inform how AI’s scope evolves going forward.
