Every time a company announces an “AI-powered” feature, there’s an unspoken second half of that sentence that almost never gets said out loud: powered by whom, exactly?
Someone taught the machine what “good” looks like
Before an AI system can recommend a product, flag inappropriate content, or generate a description, someone had to label thousands of examples of what counts as relevant, appropriate, or accurate. That labelling work — largely invisible, frequently outsourced, often poorly paid — is the actual foundation underneath the feature that gets marketed as effortless intelligence. The polish on the front end depends entirely on unglamorous human judgement calls made far away from the press release.
“Automated” often means “reviewed by a person you’ll never see”
A striking number of “AI-powered” systems still have a human in the loop somewhere — checking edge cases, correcting mistakes, handling the situations the model wasn’t confident about. This isn’t a scandal. It’s often sensible engineering. But it’s rarely disclosed, because “AI-powered” sounds more impressive in a press release than “AI-assisted, with meaningful human oversight.” The labour doesn’t disappear when it becomes less visible. It just becomes harder to see, and harder to value fairly.
The data had to come from somewhere
Every recommendation engine, every generated description, every “smart” categorisation was trained on a dataset that someone assembled, cleaned, and structured. In ecommerce specifically, that often means years of purchase history, browsing behaviour, and product catalogues contributed — usually without much explicit awareness — by the very shoppers now being served the “personalised” results. The raw material of AI in retail is, in a very real sense, everyone who shopped before you.
Why this matters for how AI gets talked about
None of this is an argument against AI in ecommerce. It’s an argument for honesty about what the phrase actually describes. “AI-powered” often means a genuinely useful system built on a foundation of human labour, human judgement, and human data — compressed into a phrase that makes all of that invisible.
When we talk about the AI features we’re building at ShopWithMore, we want to be straightforward about what’s genuinely automated, what still involves human oversight, and what the technology can and can’t do yet. The industry’s habit of erasing the labour behind the label doesn’t serve anyone — not the people who did the work, and not the shoppers trying to understand what they’re actually using.
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