Human approval for ecommerce teams
Human approval is a named person agreeing to a specific output before it has an effect. The useful version is narrow: approval on anything that reaches a customer, moves money, changes a price, or commits the organisation to something. Everything else runs without a gate, which is what keeps approval meaningful rather than ceremonial.
( The Detail )
What this control means in practice
Write down who approves what, what they are actually checking for, and what happens when they are on leave. An approval step nobody can describe is a delay, not a control. A fair check is whether the approver has ever rejected anything; if not, the gate is probably being waved through.
Realistic for this kind of team
An ecommerce team holds order histories, addresses and contact details, and usually runs a stack of connected apps that each hold a slice of it. The governance question is rarely about one AI tool. It is about how many systems already have standing permission and whether anyone has reviewed that list this year.
Realistic controls: keep customer identifiers out of AI prompts, use product and catalogue data freely because it is already public, and put an approval gate on anything published to a storefront or sent as a campaign. Automated content that reaches customers is where a small error becomes a large one.
How to approach it
Begin with the decision rather than the tool. Name the recurring judgement this affects, the information it depends on, and the person accountable for acting on the result. That framing keeps the first build small enough to inspect and useful enough to matter.
Keep a human review point in the loop until the quality and the failure modes are understood. A system that shows its working - what it drew on, where it is uncertain, and what it deliberately left alone - is one a business can keep running after the initial build.
( Next Step )
Start small enough to review, but on a workflow important enough to show whether a better system is worth building.