AI Product Descriptions: A Workflow That Stays Accurate

AI product descriptions are now built into the tools sellers already use. Amazon launched a generative AI listing tool at its 2023 seller conference that writes product titles, descriptions and listing details from a few words or sentences of input, and it lets sellers either refine the text or submit it straight to the catalog. Amazon said early feedback showed the majority of sellers who tested it were using the generated content directly.

That last part is the risk. A language model writes fluent copy about any product, including details it has guessed. On a product page, a guessed dimension or an unproven "biodegradable" is a returned order at best and an advertising claim you cannot support at worst. This is the workflow we use to get the speed without the guessing.

AI product descriptions start with a fact sheet

The model should never be the source of facts. Before any prompt, build a one-page fact sheet per product, and treat it as the only truth the AI is allowed to use:

• Identity: brand, product name, model or variant, count per pack.
• Physical facts: dimensions, weight, materials, colors, what is in the box.
• Claims with evidence: every claim such as "compostable," "BPA-free," "food safe" or "fits most standard bins," each with the document that proves it (a test report, a certificate, a supplier spec).
• Use: who it is for, what it is for, and what it should not be used for.
• Care and safety: cleaning, storage, warnings.
• Proof points: the specific reasons someone picks this one over the next listing.

The FTC's advertising guidance for small businesses is short on this point: advertising must be truthful and non-deceptive, and advertisers must have evidence to back up their claims. The fact sheet is that evidence, organized. If a claim has no document next to it, it does not go in the sheet, and the AI never sees it.

Brief the model like a copywriter

A good prompt reads like a brief you would hand a freelance writer:

1. The fact sheet, pasted in full, with the instruction to use only those facts.
2. The channel and its limits: Amazon title, five bullets, a Shopify description, a Google Shopping feed.
3. The reader: a facility manager buying in bulk reads differently from a parent buying one pack.
4. Voice: a few lines from your brand voice guide, plus two descriptions you consider good.
5. Banned words and claims: superlatives you cannot prove, competitor names, medical or environmental claims not on the sheet.
6. An instruction to flag gaps: "If a detail a buyer would expect is missing from the fact sheet, list it as a question instead of writing around it."

That last line is the most useful one. The questions the model asks back are often the ones a customer would otherwise ask after buying.

A small example, with an invented product. The fact sheet says: "Pack of 12 kraft mailer boxes, 9 x 6 x 3 inches, holds up to 5 lb, FSC certificate on file." A grounded bullet reads: "12 kraft mailer boxes, 9 x 6 x 3 inches, rated to 5 lb." An ungrounded one reads: "Eco-friendly, ultra-strong boxes for any shipment." The second adds an environmental claim and a strength claim that appear nowhere on the sheet, which is exactly what review has to catch.

Channel rules the AI does not know

General-purpose models do not reliably know each marketplace's current rules, so put the rules in the brief and check against them afterwards.

Amazon titles. Amazon announced title requirements effective January 21, 2025: for most categories titles may not exceed 200 characters including spaces; a set of special characters, among them the exclamation point, dollar sign, question mark, underscore, curly braces and caret, is not allowed unless part of the brand name; and the same word may not appear more than twice, with prepositions, articles and conjunctions excepted. Category style guides in Seller Central can be stricter, so check yours.

Google Merchant Center. Google's Merchant Center help says AI-generated titles and descriptions must be provided through the structured title and structured description attributes, with the digital source type sub-attribute set to "trained_algorithmic_media." If your feed is generated by AI, your feed setup needs to say so.

Your own website. Google Search's guidance on generative AI content calls it useful for research and for adding structure to original content. It also asks publishers to manually fact-check and review AI output before publishing, and warns that generating many pages without adding value for users may violate its spam policy on scaled content abuse. A store with five hundred near-identical AI descriptions is exactly that pattern.

Review every claim before it goes live

Review is where the time saving is kept or lost. A checklist that takes a few minutes per product:

• Trace every factual statement back to a line on the fact sheet. Delete anything that does not trace.
• Check every number against the spec: sizes, counts, capacities, compatibility.
• Compare the copy with the images. If the description says "kraft paper box" and the photo shows a printed carton, one of them is wrong.
• Read for implied claims. "Gentle enough for newborns" is a safety claim even without a number.
• Read it on a phone, and check that the first two lines carry the facts a buyer needs most.
• Have one named person sign off, and keep the fact sheet and the approved copy together for the next update.

Where AI helps and where it should not lead

AI is genuinely useful for the repetitive part: turning one approved description into variants for each size or color, rewriting for different channels, drafting bullet structures and producing first drafts for a catalog of similar items. For a printing and packaging company with dozens of box styles, or a seller with a large range of near-identical SKUs, that saves real hours.

It should not lead on regulated or high-risk categories: health products, supplements, children's products, anything with a safety or environmental claim. In those categories, write the claim lines by hand from the documentation, and let AI handle only structure and tone around them. The same applies to translations for other marketplaces: have a native speaker check them, since a wrong unit or warning in another language is still your listing.

Keep the copy and the images in step

Descriptions and images make one listing, which is why we wrote a separate guide to Amazon product listing images. The same fact sheet should brief the photographer and the infographic designer, so every image callout and every bullet say the same thing about the same product.

How we work on listings

At Pinn.Media we build listings from the fact sheet out: packaging, photography, listing images, A+ content and the copy that ties them together. Our Amazon launch for a dust sheet brand shows the approach, with the packaging, the images and the copy all built from one set of product facts. If you have a catalog to write or a listing that is not converting, book a discovery call at /contact#book.