Amazon's AI-Powered 'Hear the Highlights' Feature Aims to Revolutionize Product Reviews

Can an Amazon AI voice guide you better than customer product reviews? It's starting to try

Andy Jassy, chief executive officer of Amazon, speaks during an unveiling event in New York, US, on Wednesday, Feb. 26, 2025. Anyone who has ever gone in search of a product review on Amazon knows how valuable the experience of other shoppers can be, and how easy it is to fall down the rabbit hole of customer comments, from five-star raves to one-star takedowns -- sometimes hundreds of words to get to the point. As Amazon continues to roll out AI features it says will make shopping easier, AI-generated audio descriptions of products are in the mix and scraping that customer commentary -- maybe ultimately settling into a position to replace it as a go-to source of buying information. Called "Hear the Highlights," the AI-voiced product descriptions rely on a large language model to script the summary based on a variety of sources, pulling from Amazon's product catalog, customer reviews, and information from across the web, and then translating the content into short-form audio clips. The summaries began rolling out during the summer on select products to a subset of U.S. customers and have now reached all U.S. customers as a button in the mobile shopping app, scaling up to cover over one million products. A unique appeal of Amazon, and other e-commerce options, has always been the ability to get information from actual users, not just product descriptions. Of course, bogus reviews have long been a problem for Amazon, even though it bans use of paid promotion and other inauthentic forms of review writing. You still have to sort through various efforts to game the system, and in recent years, signs that the newest review writers are chatbots like ChatGPT. But actual people sharing their actual, idiosyncratic experience with a product -- customers as a source of information, and informed decision making -- have been a key part of the learning process from clothing and shoe sizes to safety and more narrow questions: When purchasing a new toaster, does it do bagels, is the timer setting accurate, how easy is it to clean the crumb tray? Can AI improve on that? Reviews are by nature unwieldy in the mass individuality, but human readers have proven pretty adept at distilling what they need from the human chaos. In some sense, the brain of the average Amazon review reader is a pretty good large language model, skimming and picking out key words and key information, so an AI will have to do it at least as well as a human would if it's to add to the customer experience as promised. AI does have its advantages. For one, it won't experience cognitive overload when facing an electric tea kettle on Amazon with over 32,000 reviews. It can comb through the data, but can it gives us only what we need or want to know? That can still be tricky for AI to get right, and it may be inherently problematic to mix product catalogs, customer reviews, and web information into a single distillation - with the sources of this information each coming with its own set of intentions. "It's important to recognize where AI is currently strong, such as in automation and pattern recognition, and where it still falls short, like in judgment-heavy tasks," said Ankur Edkie, CEO & co-founder, Murf AI, which creates AI voiceovers. "A key question is whether there's a way to factor in customer context as an input while generating these summaries," he said. The value of AI, according to Edkie, is finding the proper problem-capability fit. If that isn't achieved, the sense of gimmickry is likely to sneak in through a door left open for AI fatigue, which he says consumers are likely experiencing by now. Amazon's Hear the Highlights AI-audio summaries are currently the same for every user. "The AI summary needs to capture nuance and context. For example, even a few negative reviews on safety can outweigh many positives on other features," Edkie said, adding that if a customer is focused solely on product performance, then summaries that emphasize price might not be relevant. The ability to factor in context, and to make the review process more of a dialogue between consumer and machine is likely where the technology is headed - in other words, toward the agentic side of AI, where Amazon is also actively adding to its AI commerce tools, such as Rufus, and a shopping tool called Interests AI, which prompts users to describe an interest "using your own words," and then it generates a curated selection of products. That feature, rolled out in the spring, is separate from the main search bar on Amazon's website. Chat and audio summaries will remain among the ways to engage, but having real-time conversations with an AI voice agent -- asking specific questions, clarifying concerns, and getting deeper insights from reviews -- is what will shift the experience from one-way delivery to two-way discovery, making it far more personalized, according to Edkie. "Currently, you can interact with Rufus through text or by using voice input, but Rufus cannot talk back, its responses are text-only," he said. "With voice agents, however, you can have a two-way conversation with a bot that speaks to you," he added.

Amazon Employing AI to Help Shoppers Comb Reviews | PYMNTS.com

Among the advantages here, the report added, is that artificial intelligence (AI) won't suffer from cognitive overload from combing through thousands of reviews. "It's important to recognize where AI is currently strong, such as in automation and pattern recognition, and where it still falls short, like in judgment-heavy tasks," said Ankur Edkie, co-founder and CEO of Murf AI, which develops AI voiceovers. "A key question is whether there's a way to factor in customer context as an input while generating these summaries." The value of AI, according to Edkie, is determining the right "problem-capability fit." Without that, he added, a sense of "gimmickry" is likely to filter through thanks to AI fatigue, which he says consumers are likely feeling by now. PYMNTS has contacted Amazon for comment but has not yet gotten a reply. The CNBC report also noted that the tendency of AI to focus on common themes can water down responses even as it summarizes them, taking out the detailed personal experiences found in human reviews. "AI might overlook unique insights or niche needs that don't align with the majority of responses," said Brian Numainville, principal at consumer research firm Feedback Group. "Additionally, the ability to critically interpret reviews -- like spotting biases or trusting certain reviewers -- is diminished with AI summaries." Nauman Dawalatabad, a research scientist at Zoom Communications, offered his opinion that the technology is on its way to improving customer experience. "I take it as technology helping us to make informed decisions," he said, pointing to the mental fatigue and wasted time that can result from working through customer reviews. Meanwhile, recent research by PYMNTS Intelligence shows that AI shopping adoption has begun to gain traction with younger and middle-aged consumers. The research found that 32% of all consumers said they have used or would use generative AI for shopping. "Bridge millennials -- older millennials straddling Gen X -- lead the way, with 38% reporting AI use for shopping," PYMNTS wrote last month. "Zillennials are close behind at 36%, followed by millennials at 35%. Gen X is next, at 33%, while Gen Z comes in at 31%. Baby boomers show some traction as well, with 28% using gen AI for shopping."