Everybody's using AI to write product descriptions now. The question isn't whether AI can write them — it clearly can. The question is whether AI descriptions actually sell products as well as human-written ones.
The honest answer: it depends on how you use AI, and most people use it wrong.
What the data says
Several e-commerce studies from 2024-2025 have compared AI-generated and human-written product descriptions. The results are consistent: AI descriptions that are generic perform worse, and AI descriptions that are specific perform about the same as human-written ones.
The difference isn't AI vs. human. It's specific vs. generic. A human who writes "Beautiful handmade mug, perfect gift" performs just as badly as an AI that writes the same thing.
Where AI descriptions fail
The most common failure mode is this: someone pastes 50 product names into ChatGPT and asks for descriptions. They get back 50 descriptions that all follow the same structure, use the same transitions ("Whether you're..."), and include the same filler phrases ("elevate your experience").
Buyers can tell. Not consciously, but when every product on your store reads the same way, nothing stands out. The descriptions become wallpaper.
Where AI descriptions work
AI descriptions work when they include specific product data: materials, dimensions, weight, origin, use cases. An AI that knows a mug is 12oz, stoneware, matte-glazed, and dishwasher-safe can write a much better description than a human who only knows it's a "ceramic mug."
The key is input quality. Give AI specific data and it writes specific descriptions. Give it just a product name and it writes generic filler.
The brand voice problem
Most AI tools produce descriptions in a single default voice — slightly formal, slightly enthusiastic, interchangeably corporate. If your store sells handmade candles, that voice doesn't fit. If your store sells industrial equipment, it doesn't fit either.
This is why "describe this product" prompts produce bad results. The AI doesn't know whether your store sounds like Patagonia or Home Depot.
How to use AI descriptions effectively
- Feed it real data — Materials, dimensions, weight, color, origin. The more specific the input, the more specific the output.
- Define your voice — Give the AI explicit instructions about tone, sentence length, and words to avoid. "Write like a knowledgeable friend" produces very different results than "write like a luxury brand."
- Edit the output — AI gets you 80% there. A human eye catches the generic phrases, fixes the factual errors, and adds the details only you know.
- Be consistent — One good description doesn't help. You need every description on your store to hit the same quality bar. That's where AI's scale advantage matters.
The Catalogd approach
Catalogd addresses each of these problems. It pulls descriptions from your actual product data (not just the title), writes in your chosen brand voice, and lets you edit every description before downloading. The result is AI-generated descriptions that sound like your store, not like ChatGPT. Try it free with 5 products.