AI product descriptions is software that writes the text on an online store's product pages, fills in each product's details and cleans up its photos, using AI models. More and more, the model starts from the product photo itself. The industry calls all of this product content: the title, the description, the bullet points, the attributes and the images of each product.
Attributes are the separate facts about a product that a store can sort and filter by: colour, size, material, pattern, sleeve length and so on. They matter even more than the description. A shopper who filters for "cotton, blue, double bed" sees only the products whose attributes say so. A product with missing attributes does not appear, even if it is exactly what she wants.
Writing all this by hand is slow. A brand that adds 300 products a season must write 300 titles and descriptions, and fill in about 15 attributes for each one. On top of that, every marketplace that sells the products wants them described in its own format.
Take, for example, a home-textiles maker in Panipat that launches 300 new bedsheets. The team uploads one photo of each bedsheet, together with a sheet of facts from the factory: size, thread count and fabric. A computer vision model reads each photo. It finds the colour, the pattern, such as floral or geometric, and the style. A language model then writes a title, five bullet points and a description in the brand's style, for example "Floral cotton double bedsheet with 2 pillow covers, 144 thread count". The software removes the background from the photos, because many marketplaces ask for a plain white one. It also writes a Hindi version of each page. Then an employee in the catalogue team checks each page and approves it. This takes minutes per product instead of an hour.
The check by a person is needed. A model can write a fact that is not true, such as "100% cotton" for a blend, because it guessed. This is called AI hallucination. So the hard facts must come from the factory's data, and the model writes only the words around them. This way of working, where a model drafts and a person approves, is called human in the loop.
Good product content helps the rest of the store. E-commerce search and recommendations finds products through their attributes. An online marketplace needs the same attributes for its own filters. Large manufacturers keep the master copy of each product's data in product information management (PIM) software, and the AI reads from it and writes into it. Similar models also write ads and banners. That is generative AI for marketing content, which writes to persuade a shopper, while product descriptions are written to describe the product accurately.