In short
AI is most useful in ecommerce when it takes the repetitive middle of a task. I use it to draft, sort and check. I still decide, approve and publish.
Where AI earns its place
The best AI use cases in ecommerce are boring on purpose. They are tasks you repeat every week, where a good first draft is worth more than a perfect blank page.
- Product copy: first drafts of titles, bullet points and descriptions from supplier specs.
- Catalog cleanup: spotting inconsistent attributes, sizes and naming across hundreds of rows.
- Messages: drafting supplier follow-ups and customer replies I then edit.
- Research: summarising product pages and comparing options side by side.
- Spreadsheets: formulas and small scripts that would otherwise take an afternoon.
Where I keep a human in the loop
Anything a customer can rely on needs a person behind it. That means pricing, product claims such as materials or safety, and anything published without review.
AI is also weak at your brand voice until you show it examples. I treat its output as a draft that has not earned trust yet.
A simple rule: draft, check, ship
Every AI-assisted task I run follows the same three steps.
- Draft: let the model produce a first version from clear inputs.
- Check: compare it against the source facts and fix anything invented or vague.
- Ship: publish only after a person has approved it.
Start with one workflow
Pick the one task you repeat most often. Write the prompt once, save it, and note how many minutes it saves. When it works, move to the next task. Small, repeatable wins beat a big AI strategy that never ships.
Written by
Atmiya Jadvani, ecommerce and ai practitioner building Likhao.
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