July 23, 2024
Amazon extends generative AI-powered product listings to Europe


Amazon is bringing its generative AI listing smarts to more sellers, revealing today that those in France, Germany, Italy, Spain, and the U.K. can now access tools designed to improve product listings by generating product descriptions, titles, and associated details.

Additionally, sellers can also “enrich” existing product listings by automatically adding missing information.

The announcement comes nine months after Amazon first revealed plans to bring generative AI technology to sellers. The company hasn’t been overly forthcoming with its availability on a market-by-market basis, but presumably it has largely been limited to the U.S. so far, though the company did quietly launch the tools in the U.K. earlier this month, according to an Amazon forum post. And in its blog post today, the company said that it rolled out this feature in the U.K. and some EU markets “a few weeks ago,” with more than 30,000 of its sellers apparently using at least of these AI-enabled listing tools in the intervening timeframe.

Amazon pitches these new tools as a way to enable sellers to list goods more quickly. The seller heads to their List Your Products page as usual, where they can begin by entering some relevant keywords that describe their product and simply hit the Create button to formulate the basis of a new listing. The seller can also generate a listing by uploading a photo via the Product image tab.

Amazon marketing image for generative AI-powered listings
Amazon marketing image for generative AI-powered listings
Image Credits: Amazon

Amazon will then magic up a product title, bullet point, and description which can be left as is, or edited by the seller. However, given the propensity for large language models (LLMs) to hallucinate, it wouldn’t be prudent to post a listing unchecked — a point that Amazon acknowledges by recommending that the seller reviews the copy “thoroughly” to ensure everything is correct.

“Our generative AI tools are constantly learning and evolving,” the company announced in its U.K. forum two weeks back. “We’re actively developing powerful new capabilities to make generated listings more effective, and make it even easier for you to list products.”

Earlier this year, Amazon also launched a new tool that allows sellers to generate product listings by posting a URL to their existing website. It’s not clear when, or if, Amazon will be extending this functionality to Europe or other markets outside the U.S.

The data question

While Amazon is no stranger to AI and machine learning across its vast e-commerce empire, bringing any form of AI to European markets raises some potential issues around regulation. There’s GDPR on the data privacy side for starters, not to mention the Digital Services Act (DSA) on the algorithmic risk side, with Amazon’s online store designated as a Very Large Online Platform (VLOP) for the purposes of ensuring transparency in the application of AI.

For context, Meta last week was forced to pause plans to train its AI on European users’ public posts following regulatory pressure. And Amazon itself has faced the wrath of EU regulators in the past over its mis-use of merchant data, when it was alleged that Amazon tapped non-public data from third-party sellers to benefit its own competing business as a retailer. And just this month, U.K. retailers hit Amazon with £1.1 billion lawsuit over similar accusations.

While Amazon’s latest foray into generative AI is a different proposition, it will have had to have trained its LLMs on some sort of data — what data this is, precisely, isn’t clear. In its initial announcement last September, Amazon shared a quote from its VP of Selection and Catalog Systems, Robert Tekiela, which referred to “diverse sources of information.”

With our new generative AI models, we can infer, improve, and enrich product knowledge at an unprecedented scale and with dramatic improvement in quality, performance, and efficiency. Our models learn to infer product information through the diverse sources of information, latent knowledge, and logical reasoning that they learn. For example, they can infer a table is round if specifications list a diameter or infer the collar style of a shirt from its image.

Robert Tekiela, VP of Amazon Selection and Catalog Systems

TechCrunch has reached out to Amazon for comment on these various issues, and will update when — or if — we hear back.



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