There is a great deal of noise about how capable AI has become. Far less is said about the one rule that decides whether it actually works inside a real business. The rule is simple. A person stays accountable for anything that matters. AI produces the work, and a human reviews it, corrects it, and approves it before it goes anywhere. We call it build, review, approve, and it sits at the centre of everything we set up.
It sounds almost too obvious to state. The reason it needs stating is that the temptation to skip it grows exactly as the tools get better.
Better output is more convincing, not more correct.
When AI output was clumsy, nobody was tempted to send it straight to a client. It plainly needed a human. The danger now is the opposite. The work comes back polished, confident and well formatted, and it reads as though it has already been checked. Most of the time it is right. Occasionally it is confidently wrong, a figure transposed, a clause invented, a source that does not exist. The more convincing the output, the easier it is to wave through, and the more expensive the one that slips past becomes.
So the discipline matters more as the technology improves, not less. The check is not a sign that you distrust the tool. It is the thing that lets you use a fast tool on work where being wrong has a real cost.
The person keeps the judgement. The AI keeps the volume.
Build, review, approve is not about slowing your people down. It is about moving their time to where it is worth most. The machine carries the volume, the drafting, the formatting, the first pass at research, the repetitive production that used to eat the day. Your specialist spends their time on the part only they can do, reviewing, correcting and signing off. You get the speed of automation without handing over the steering wheel.
In practice it looks like this. A report is produced to the standard you would expect of the finished piece. The person accountable reads it, fixes what needs fixing, and approves it, or sends it back. Only approved work goes downstream. Nothing important ever runs unsupervised.
It is also the standard Australia is setting.
This is not only good practice, it is the direction of policy. Human oversight is one of the core principles of Australia's national AI ethics framework, and the updated Privacy Act expects businesses to be transparent about decisions made by automated systems. A business that builds a human checkpoint into its AI from the start is not bolting compliance on later. It is already working to the standard.
The smartest rule in AI is not a clever prompt or the newest model. It is keeping a person in charge of the things that carry your name. Get that right, and everything else AI can do becomes an asset rather than a risk.