Amazon is using AI to make it easier to see if a product is any good. The company is now rolling out AI-generated review summaries, which boil down hundreds or thousands of Amazon reviews into a one-paragraph blurb explaining what most people like or dislike about a product.
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Amazon adds AI-generated review summaries so you don’t have to read the comments
Amazon is rolling out generative AI product summaries in the US on mobile across a variety of product categories.


The summaries have been in testing for at least a couple of months, and they’re now more widely available to a “subset” of users in the US on Amazon’s mobile app. Amazon says they’re available “across a broad selection of products.” So far, we’ve seen them on TVs, headphones, tablets, and fitness trackers. But the feature’s availability isn’t completely consistent. The Galaxy Tab A7 has a review summary, but the newer Galaxy Tab A8 does not.
Amazon’s summaries are easy to read but do include some occasional language quirks. They also seem to focus primarily on the positives of the product, spending less time on the negatives and leaving them for the end. That said, that could be because Amazon’s search already elevates highly rated products, so it’s hard to find summaries of anything that people have been particularly frustrated by. Here are a couple screenshots of examples.
The feature can be found at the top of the review section on mobile under the heading “Customers say.” At the end, the paragraph includes a note that it was AI-generated. Amazon says the summaries only pull from verified purchases in an effort to cut down on fake reviews. The system also includes review highlight filters that you can tap to find the actual reviews that touch on those features or problems.
Summarizing customer reviews has turned out to be one of the more obvious and easy to implement uses of generative AI. Newegg launched a similar feature last week, and Microsoft added AI summaries to the Microsoft Store in May. As more platforms roll this out, the big question for users will be how much they can trust summaries from a service that’s clearly trying to sell them something.

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