World Model Readiness Scaling output without scaling risk

Module · Scaling output without scaling risk

The Marketing Team AI Check

AI lets your team produce ten times the content, which is a gift and a trap. The same speed that fills the calendar can flood your channels with off-brand copy, unlicensed images, and posts that read like a robot wrote them because one did. This module checks the five controls that let output scale without the brand paying for it: voice guardrails, human review before publish, asset provenance, channel-fit checks, and honest attribution of what the AI content actually earned.

Question 1 of 5 · Brand voice holds

Does AI-generated copy come out sounding like your brand, not the model?

A model defaults to a generic, over-eager voice that reads the same across every company using it. Guardrails mean a documented voice, examples, and a review that catches the drift, so your content sounds like you and not like everyone else's prompt output.

Question 2 of 5 · Human reads before publish

Does a person read AI content before it goes out the door?

AI produces confident text that can be subtly wrong, off-tone, or embarrassingly generic, and the failure is public the instant it publishes. A human in the loop before publish is the cheapest insurance there is. The alternative is your audience doing the proofreading.

Question 3 of 5 · Asset provenance tracked

Do you know the origin and licence of the AI-generated images and assets you publish?

AI images can reproduce copyrighted work, invent a face that resembles a real person, or come from a tool whose licence forbids commercial use. Provenance means you can say where an asset came from and that you are cleared to use it, before a rights holder asks.

Question 4 of 5 · Content fits the channel

Does your team check that AI content actually fits the channel before it ships?

A model will happily produce copy that is technically correct and completely wrong for the channel: LinkedIn earnestness on TikTok, a wall of text where a subject line belongs. Channel-fit means someone checks the format, length, and register suit where it lands, not just that the words are good.

Question 5 of 5 · Attribution is honest

Can you tell whether the AI content actually performed, or just filled the calendar?

It is easy to celebrate producing more and never ask whether it worked. Honest attribution ties AI-assisted content to real outcomes, engagement, conversion, pipeline, so you can tell the volume that earned its place from the volume that just added noise the audience learned to ignore.

For the statistics · one click each

Three questions for the public picture

These do not affect your score. They feed the anonymised, aggregated statistics; groups under 8 respondents are never shown.

How many people are on your marketing team?

1 to 2
3 to 6
7 to 15
Over 15

What share of your published content is now AI-assisted?

Under 10 percent
10 to 30 percent
30 to 60 percent
Over 60 percent
We do not track it

How does AI content get reviewed before it publishes?

It publishes automatically
A quick skim
A human reviews it
Reviewed against a checklist
It varies by person

Your context

Used to calibrate the report. Company size and sector remain in the anonymized dataset; your email does not.