If you run a WooCommerce store with hundreds or thousands of products, writing unique descriptions for each one is a real bottleneck. AI-generated product descriptions promise to solve this — but the reality is more nuanced than the marketing suggests.

The Problem with Generic AI Output

Drop a product name into ChatGPT and ask for a description. You’ll get something grammatically correct, reasonably structured, and completely generic. It reads like every other AI-generated description on the internet. Search engines notice this. Your customers notice this.

The stores that succeed with AI-generated content don’t use AI as a “write it for me” button. They use it as a first-draft engine with heavy human curation.

A Workflow That Actually Works

Here’s the approach we’ve implemented for several WooCommerce clients with large catalogs:

1. Structured input, not freeform prompts. Instead of asking AI to “write a product description,” we feed it structured data: SKU attributes, material specs, use cases, and target audience. The output is dramatically better when the input is specific.

2. Brand voice training. We provide 10-15 examples of the client’s best existing descriptions as reference. The AI learns the tone — whether it’s technical, casual, luxury, or straightforward — and mirrors it.

3. Human review loop. Every AI-generated description goes through a human editor. Not for rewriting — for fact-checking, brand alignment, and adding the details that only someone who has actually seen the product would know.

SEO Considerations

Google’s position on AI content is clear: quality matters, not origin. But “quality” means unique value. If your AI descriptions are just rearranged spec sheets, they won’t rank. The stores we’ve seen succeed combine AI-generated base descriptions with unique elements — real customer use cases, comparison notes, and specific compatibility details that no AI would know to include.

The Bottom Line

AI can cut your WooCommerce content production time by 60-70%. But only if you treat it as a tool in a larger workflow, not as the entire workflow. The stores that publish raw AI output are building on sand. The ones that use AI as a starting point and add genuine expertise on top are the ones seeing real results.