Since generative AI went mainstream, it has been everywhere in marketing presentations. Here are the uses that, in our experience, actually save time or money for e-commerce brands — and the limits you should know before you rely on them.
1. Product descriptions and category copy
In a store with hundreds of products, writing a careful description for each one is the job everyone postpones. AI produces a good first draft: it turns materials, dimensions, use and care into consistent copy with the same structure across the catalogue.
The catch: the model has never seen your product. It can invent a dimension, an ingredient or a certification. Technical facts should always come from your own data, and someone should read the copy before it goes live. Watch the voice, too — a store where every product is “premium” and “unique” convinces nobody.
2. Translation and localisation
For brands entering new markets, translation used to be a serious cost. AI translation is now good enough for most product pages. The real difference is localisation: in the UK a sweater is a “jumper”, size charts and units change, legal texts are market-specific. Let AI translate and someone who knows the market do the final read.
3. Faster, more varied ad creative
Creative is one of the biggest drivers of ad performance. AI lets you produce variations of headlines, hooks and visual set-ups in minutes, so you can test several ideas at once instead of waiting on a single ad. Use it for backgrounds, scenes and variations — not to change the product itself; misleading visuals upset customers and ad platforms alike. This is how we work in ad creative production.
4. First response in customer service
“Where is my order?”, “Do you have a size chart?”, “How do I return this?” Most customer questions fit a few patterns. An assistant on your site or on WhatsApp can answer them at midnight, look up order status and explain returns. The essential feature of a good set-up is knowing when to hand over to a person: trapping an upset customer in a bot repays the saved time in reputation. We design that handover from the start in WhatsApp & loyalty.
5. Reading data and preparing reports
Ad dashboards, store analytics, marketplace reports — plenty of numbers, little time. AI is good at summarising scattered data and giving a quick first answer to “what changed since last month?”. But if your tracking is wrong, AI will explain the wrong numbers more convincingly. First accurate measurement, then summaries.
6. Being visible in AI search
The newest item, and possibly the most important. Customers now ask ChatGPT, Gemini and Perplexity which brand to buy, not only Google. Which brands they name depends on how clear your site is, what other sites say about you and whether your facts are consistent. We explain how this works in how to get recommended by ChatGPT.
What AI cannot do for you
Which product to grow with, what your brand stands for, how much budget each channel deserves — AI cannot decide these, because they require knowing your product, your customers and your numbers. Use AI as a tool that makes your team faster; do not hand it the decisions.
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