Search once returned a page of options. Now it delivers a verdict. That looks like convenience, but it is also a transfer of judgement, from us to a system we cannot inspect. A few years ago, buying an office chair meant suffering for it. You opened a dozen tabs, read strangers bickering about lumbar support, squinted at star ratings of dubious origin, and eventually committed to something while quietly suspecting you had chosen wrong. The work was tedious. It was also, in its small way, yours. You did the comparing. Now you type a sentence into a chatbot and a chair surfaces at the top of the reply, already picked, with three tidy reasons attached. No tabs. No bickering strangers. No low hum of doubt that a better option is buried two pages down. The weighing-up has happened somewhere unseen, performed by something you cannot easily question, and returned to you as a single confident answer. One chair, settled on your behalf; the alternatives you never compared recede behind it. This is not a niche habit. In a January 2026 survey of US shoppers by Clutch, seven in ten said they now use AI somewhere in the buying process, and 65% turn to it to research a product before they spend a thing. Most still want the final tap to be their own: only 4% said they would let the AI go ahead and buy the item for them. We have handed over the digging, then, without quite handing over the wallet. That difference is the interesting part. We are not delegating the purchase. We are delegating everything that comes before it, the part where we used to sift and second-guess and form a view. The more that slips offstage, the more it matters who is waiting in the wings. Because somebody is. The same shift has already begun reshaping the work of the people who make the content . They now have to write and build as much for the crawler as for any human landing on the page. Those at the other end of it, the ones still doing the buying, are changed too, just less visibly. A whole industry has grown up around shaping what the machine suggests. The reasons we trust a neat conclusion more readily than a messy list of links are oddly specific to how our minds work. The line between a helpful recommendation and a paid placement, meanwhile, grows fainter by the month. Worth knowing, surely, what we signed up for when we stopped opening tabs. Where the legwork went For three decades, searching meant being handed a list. You typed a few words, the engine served up its ten blue links, and the sorting was left to you. The ranking was a suggestion rather than a ruling. You could distrust it, scroll past it, open the fourth link because the first three smelled of advertorial. A generated answer removes that step. Ask which cordless vacuum to buy, and you get a recommendation, not a directory. The shortlist you would once have assembled yourself arrives ready-made, and often it holds just one name. The same has happened to reviews. Wading through them to reach your own opinion used to be part of the ritual; now the machine boils them down for you. A pile of reviews nobody reads now, reduced to a single rating we take on trust. The behaviour has moved faster than almost anyone predicted. Klaviyo’s survey of nearly 8,000 consumers across eight countries late last year found that 41% had bought something an AI recommended in the previous six months, with a further 27% nudged towards a product they then went away to research. A separate study by the fraud-prevention firm Riskified, covering more than 5,000 shoppers worldwide, put the share now using AI somewhere in their shopping at close to three-quarters . The tool has stopped being a curiosity at the edge of the process. It is becoming the front door. Retailers have followed the traffic. Amazon’s assistant, used by more than three hundred million people last year, no longer merely answers a question about a product but runs searches, balances your budget against your constraints, and returns a favourite. A growing li