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Your marketing team searches the CMS for "how to reduce cart abandonment" and gets nothing, because the only article on the topic is titled "Recovering lost checkouts." Keyword search matched zero words, so it returned zero results, even…
Your search box works fine until the day someone renames a product line. Sanity ships the update, the CMS shows the new copy instantly, and then a support agent asks your AI assistant about the old name and gets a confident, wrong answer.
Your search team ships a vector database. Six weeks later, an editor updates a product description, hits publish, and the semantic search index still returns the old copy.
A shopper types "trail runners under $150, in stock at the Portland warehouse, men's size 11" into your AI search box, and the model returns nothing useful, or worse, confidently invents a product that does not exist.
Your semantic search returns confident, plausible, and wrong results, because the embeddings were generated from a nightly batch job that ran against last week's content.
Your editorial team ships a help-center update at 9 a.m.