A common AI content workflow looks reassuringly simple: generate a draft, have someone read it, publish. On paper, there is a human in the loop. In practice, that human may be doing little more than proofreading.
Picture a localised landing page for a winter campaign: the copy is clean, the tone is right and the reviewer signs it off after fixing two commas. It also states that 78% of customers reorder within a year, a figure nobody at the brand has ever measured. And it promises next-day delivery in a market where the courier service changed to three to five days in the spring. Nothing in it is grammatically wrong and both errors go live.
That step has value but it cannot be called review. Generative AI produces fluent, grammatical text by default, so a proofread checks the part of the content least likely to be wrong. The mistakes that cost brands credibility are rarely grammatical ones.
Article 50 of the AI Act has applied since 2 August 2026, and the European Commission’s guidance on it, last updated in July 2026, draws the same line in writing: spelling and grammar checks do not count as human review. The rule itself is narrow in scope, but the definition behind it is a useful standard for any team publishing AI-assisted content.
What the EU AI Act means by “human review”
Under Article 50(4) of the EU AI Act, organisations using generative AI must label AI-generated or manipulated text when it is published to inform the public on matters of public interest. The Commission’s examples include politics, public health, consumer safety and economic or financial developments that may be the subject of public debate. In practice, that points to news and informational articles. Ordinary product descriptions and promotional copy will often sit outside this specific disclosure obligation, since it is focused on text intended to inform the public.
The rule has an exemption: text that has gone through human review or editorial control does not need a label. The Commission’s guidelines on Article 50 sets out what that means.
- Human review is a deliberate examination of the substance of the content by people with relevant knowledge and professional judgement in the subject.
- Editorial control sits with a responsible editorial function that can approve, change or reject the text on substantive grounds, including fact-checking and the reliability of sources.
- Editorial responsibility means a legal or natural person (an individual, an editorial board or the publishing company) holds ultimate legal responsibility for what is published.
Then the line that matters most: “superficial, solely formal or procedural checks” (such as spell-checking or grammar correction) do not qualify.
The Commission has described what meaningful review looks like and that description holds for a product page in six markets as much as for a news article.
Why proofreading is not enough
Fluency hides mistakes
Large language models are built to produce plausible text. The output reads well whether or not it is accurate, which removes a warning sign editors have always relied on: weak writing often signals weak thinking. With AI drafts, that link is gone.
The mistakes that matter are substantive: a statistic with no source or a source that does not say what the draft claims. A product feature that was discontinued last year. A price, delivery promise or availability claim that is out of date. None of these will be caught by a grammar check, because none of them are grammatical problems. They also travel further than they used to: when AI search tools summarise and cite a page, its errors go with it.
A reviewer’s first job is to verify, not to polish.
Brand claims are a commercial and legal surface
Every brand has claims it can make and claims it cannot. Superlatives, guarantees, environmental statements, health or financial wording and returns policies all carry commercial and legal weight and the rules that govern them differ by market. A claim that is routine in one country can require substantiation in another.
AI tools do not know a brand’s approved claims and they tend to make copy more persuasive. Claim review is therefore a separate task from editing, it needs access to the approved claims for each market and the authority to remove what does not comply.
Localisation: why translated AI content can still be wrong for the market
This is where the gap between proofreading and review is widest. A translated page can be correct in every sentence and still wrong for the market.
The failures are rarely visible from outside that market. Our local team in Spain has flagged how the choice between tú and usted shapes the way a brand is perceived. Our team in Portugal has observed that checkout content built around card payments overlooks how central MB Way is to the way people pay.
A reviewer who doesn’t know the market can confirm that the text is fluent. Only someone who does can confirm that it belongs there.
AI content review checklist: who checks what
Meaningful review is a set of distinct checks, each owned by someone with the knowledge to make the call. When one person covers all of them, some of them quietly stop happening.
| Check | What it covers | Who owns it | Done when |
| Factual verification | Every number, date and product capability | Writer or editor, with specialist sign-off on technical claims | Each fact traces to a named source |
| Brand claims | Superlatives, guarantees, regulated wording, offers | Brand or legal owner | Every claim matches the approved list for that market |
| Market fit | Register, cultural references, local search intent, trust and payment cues | Native-speaker specialist for that market | It reads as written for the market, not translated into it |
| Editorial sign-off | The piece as a whole | A named editor with authority to reject | Approved, recorded and locked |
The last row carries the most weight. A review only means something if someone can say no and if that decision is recorded. Two questions are worth asking of any current process: who can say no and where is that decision recorded?
What to do about it
- Lock the text once it is approved. A substantive AI edit after sign-off (rewriting, adding content, changing tone) means the published version is no longer the reviewed one. At that point the review no longer counts and has to be repeated. Version control should make this visible rather than relying on memory.
- Scale scrutiny to risk. Not all content needs the same depth of review. Informational articles, anything with financial, health or legal wording, pricing and offer terms and content for a market being entered for the first time deserve the closest attention.
- Bring native-market reviewers in at the substance stage. Market fit is a judgement about content, not a final read. Native specialists who only see finished copies end up proofreading it.
- Record who approved what and on what basis. A short approval log naming the reviewer and the checks completed turns review from an assumption into something a brand can demonstrate.
AI has made content faster to produce. It has not made it any easier to know whether that content is accurate, compliant and right for each market and that judgement is where review earns its place.
Publishing AI-generated content in multiple markets? Don’t let a mistranslated claim or an off-tone message cost you trust. Our native specialists check accuracy, claims and market fit, in their own language. Talk to our team!
Sources
- European Commission: Transparency obligations under Article 50 of the AI Act (FAQ, last updated 24 July 2026)
- https://ai-act-service-desk.ec.europa.eu/en/ai-act/article-50
Article author
Daniela Montella and Fabiana Cakilli
Senior Account Executive & Account Specialist
