Generative AI

What generative AI means

Generative AI produces new content: text, images, audio, video and code. Unlike systems that sort existing data, it produces something that did not exist before. Technically it works with probabilities, not with a database of templates. That is why the result differs between identical requests, and why it can sound plausible without being correct.

Where it helps in online retail

• Wording: rewriting, shortening and adapting product copy on the basis of existing data.
• Translation: moving catalogue content into several languages. The result needs a native check, but the groundwork saved is considerable.
• Summarising: condensing long customer enquiries, reviews and reports so a person can grasp them quickly.
• Structuring: turning unordered notes into an outline, a table into a draft for a category page.
• Images: producing variants and placeholders where no photo shoot is possible.

Why the output always has to be reviewed

The systems write fluently and give no sign of uncertainty. A wrong sentence reads as convincingly as a correct one. On top of that they know nothing about prices, stock, delivery times or legal duties unless those were handed to them. Anyone adding generative AI to a shop without a review step shifts the errors from production to publication, and there they are more expensive.

Three review questions are enough for daily work. Is every factual statement correct. Is the wording appropriate for the audience. Does it contain anything that could be read as a promise. The third question is overlooked most often and is the riskiest.

Which duties are attached

For synthetic content the EU AI Act requires labelling so it stays recognisable what was produced artificially. For text it applies to content that informs the public and is published without editorial review. Images, video and audio produced with AI have to be labelled in every case.

Three further points come with it. First the contract with the provider, which has to settle whether input is used for training. Second a check on whether personal data enters the input, which is the case with real customer data. Third traceability: anyone producing a text with AI should be able to record what it was based on.

How to scope the use sensibly

Generative AI belongs where existing material is reshaped. It does not belong where a fact is supposed to come into being. The practical sequence is therefore: assemble the data, have it produced, review it, publish it. Anyone automating the first two steps and skipping the third loses control exactly where it is needed.

Frequent questions

• Does generative AI replace copywriters? It shifts the work. Less writing, more reviewing.
• Do I own the generated content? That depends on the provider's terms and on whether third party rights are touched.
• Can I use it for legal texts? For a draft yes, for publication a specialist review is needed.