Let the model write structure, framing and first drafts, and never let it supply a number. Every figure, score, price or client result should come from a human reading real data before the draft is written. Fabricated statistics are the single most damaging thing a marketing team can publish about itself.
What is AI drafting actually good at?
Shape. Turning a set of facts into a coherent argument, proposing a structure, producing eight variations of a hook so a human can pick one. That work is genuinely faster and rarely worse.
It is also good at the unglamorous parts — alt text, meta descriptions, turning one asset into three formats — where the cost of doing it manually is why it usually does not get done.
Where does it fail in a way that matters?
Specifics it was not given. A model asked to write about campaign performance will produce plausible percentages, because plausible text is what it generates. Nothing marks them as invented.
For a marketing team the damage is asymmetric. A clumsy sentence costs nothing; a fabricated statistic published under your name costs credibility you cannot easily rebuild, especially if you sell measurement.
What is the rule that prevents most of it?
Data before draft. If a post needs a number, a human pulls that number from the real source first and hands it to the model, which then writes around it.
- Human supplies every figure, score, price and result.
- Model supplies framing, structure, hooks and variants.
- Anything that cannot be backed by a real number is written as opinion, not implied evidence.
- A screenshot of a product is captured, never generated.
Who should check it before it publishes?
Someone who knows the subject, not just someone who can read. The errors that survive an AI draft are confident and well-formed, which makes them easy to skim past and hard to spot without domain knowledge.
Build the check into the workflow rather than relying on discipline. An approval step that something has to pass through is more reliable than an intention to read carefully.
Frequently asked questions
- Does AI-written content rank or get cited worse?
- Not because of how it was produced. What gets penalised is thin, unhelpful or inaccurate content, which is a quality problem that AI makes easier to produce at volume rather than a property of the tool.
- Should AI-assisted content be disclosed?
- Practice varies and no general rule requires it for ordinary marketing copy. What matters more is that the claims are accurate and that a person stands behind them.
- How does NexPulse handle this?
- Content Lab drafts multi-format content and an approval queue sits between drafting and publishing, so nothing reaches a channel without a person passing it.