Home · Business · Operations & Logistics · Inventory & stock
As of 13 August 2026, AI can create a product catalogue from your stock list.
This still needs a person who signs their name to it.
Can you do it?
5 minutesto a draft.
1 hourto something you’d act on.
Cost, all in£0
Skill neededchat-fluent
Who has to check ityou
What the alternative costsThe available tool data gives no price for a human catalogue service.
If this goes wrong: customers see an incorrect price, specification or availability status and you have to correct the catalogue, handle the resulting orders and manage any complaint.
What to actually do
Hand it to a person
The route this page recommends
A person who owns the outcome does this end to end, worth it when the failure is dear.
Use a tool built for this
Second choiceDo it yourself
The distant thirdA chat interface, chat-fluent skill, and roughly 1 hour until you can act on the result.
How to actually do it
- Open your stock system or spreadsheet and export the current stock list with SKUs, product names, variants, quantities, prices and units.
- Gather the current product specifications, image filenames or URLs, categories, delivery details and any wording or disclaimers that must appear.
- Paste the stock list and supporting information into a chatbot using the supplied prompt, asking it to keep missing values marked rather than guessed.
- Copy the generated catalogue into a new spreadsheet and compare every SKU, product name, variant, price, unit and quantity against the source stock list.
- Open the product records and image files for each item, then check the descriptions, measurements, materials, specifications, claims and image references against those records.
- Correct the spreadsheet and descriptions, remove any unchecked claims, and send the final catalogue to the person responsible for your website, shop system or printed material.
Prompt
Create a product catalogue from the stock data below. Stock data: [PASTE YOUR STOCK LIST HERE] Additional business rules: [PASTE YOUR PRICES, AVAILABILITY RULES, PRODUCT CATEGORIES, BRAND VOICE, DELIVERY INFORMATION AND ANY REQUIRED LEGAL OR PRODUCT DISCLAIMERS HERE] Produce: 1. A clean table with SKU, product name, short description, category, price, currency, stock status, key specifications and image filename or URL where supplied. 2. A longer product description for each item using only facts in the supplied data. 3. A list of missing fields and unclear entries. 4. A separate list called CHECK BEFORE PUBLISHING containing every claim, price, stock status, variant, measurement and image reference that I must verify. Rules: - Do not invent product facts, prices, stock levels, materials, dimensions, delivery times, certifications, benefits, reviews or images. - Preserve SKUs, product names, prices, units and stock quantities exactly unless you clearly label a proposed correction. - If a value is missing or ambiguous, write [MISSING] or [CHECK] rather than guessing. - Keep product descriptions plain, specific and suitable for a UK customer. - Do not merge products or variants unless the stock data explicitly says they are the same. - Return the catalogue in a format I can paste into a spreadsheet, followed by the descriptions and the checking list.
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
What it gets wrong
- AI cannot know whether two similar stock entries are separate products or variants unless your data states the relationship.
- AI cannot supply missing specifications, reliable stock levels, current prices or suitable product images without source information.
- AI cannot decide which claims are commercially appropriate for your products or match the catalogue to your customers without your business context.
- AI cannot take responsibility for an incorrect catalogue after you publish it.
Even on a YES, the friction has a name: verification cost, judgement under ambiguity and context depth.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 2 |
| Inputs | 2 |
| Verification | 1 |
| Liability | 1 |
| Effort delta | 2 |
| Total | 8 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can ChatGPT make a product catalogue from Excel?
- Yes. Give it the spreadsheet and the rules for prices, categories, stock status and descriptions, and it can turn the data into a catalogue structure. Check every factual field against the spreadsheet before publishing.
- Can AI write product descriptions from a stock list?
- Yes, if the stock list contains enough product facts. It can rewrite those facts into consistent descriptions, but it must not be allowed to fill gaps with invented materials, dimensions, benefits or claims.
- Will AI keep my product prices and stock levels accurate?
- Only from the data you provide at the time. A chatbot does not automatically know when your stock or prices change, so compare the finished catalogue with your current records immediately before publication.
- What is the best AI tool for making a product catalogue?
- Hypotenuse AI is the closest fit in the available tool list because it is designed for product descriptions and ecommerce content at catalogue scale. It can help with the writing and structure, but you still need to supply and verify the product data.
Nearby answers
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
The newsletter
AI news, new answers and product picks, straight to your inbox.