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17.7071 14.2929C17.5196 14.1054 17.2652 14 17 14Z" fill="#161D26"></path></svg></div></button></nav><div class="main-navigation__mobile-list-container"></div></div></div></div></div></header><section><div class="ArticlePage-topContainer-background-v2 ArticleType-article" id="ArticlePage"><div class="ArticlePage-topContainer ArticlePageContainer-lead V2"><div><nav aria-label="Breadcrumb" class="breadcrumb"><ol><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news" class="breadcrumb__link">News</a></li><li style="display:inline-flex"><a href="/news/sustainability" class="breadcrumb__link">Sustainability</a></li></ol></nav><div class="article-header-v2 standard" data-testid="ArticleHeaderV2"><div class="article-header-v2__title-content"><h1>How Amazon is using AI to deliver customer orders with less packaging</h1><p>The Package Decision Engine, an AI model created by Amazon, ensures customer purchases arrive in the most efficient packaging available, while preventing damage and making deliveries easier. </p><div class="tags-desktop"><div class="related-tags v2" data-testid="related-tags"><div class="related-tags__content"><nav><ol><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/sustainability" class="related-tags__link">Sustainability</a></li><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/artificial-intelligence" class="related-tags__link">Artificial Intelligence </a></li><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/packaging" class="related-tags__link">Packaging</a></li><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/aws" class="related-tags__link">AWS</a></li><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/machine-learning" class="related-tags__link">Machine Learning </a></li></ol></nav><div data-testid="SocialSharesV2" class="share"><div><button class="button LightOutlinedV2 is-reversed has-icon" data-testid="button-fn" type="button">Share<div data-testid="icon-ShareArrowOrange"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="17" fill="none"><path fill="#FF6200" d="m12.158.5 7.207 7.747-7.37 7.242v-4.21C9.046 10.269 2.132 13.473.364 16.5c0 0 1.147-11.116 11.793-11.621V.5Z"></path></svg></div></button></div></div></div></div></div></div><div class="article-header-v2__img-content"><div class="lead-image-section"><img alt="An infographic on Amazon's Package Decision Engine. " height="698" role="" src="https://assets.aboutamazon.com/d0/ce/dc8a093247dcb2abe8661944db30/about-amazon-inline-inline002-amazon-ai-packaging-packagedecisionengine-16x9-frame-02-1920x1080.jpg" width="1240" class=""/></div></div><div class="article-header-v2__publisher-content"><div class="author"><img src="https://assets.aboutamazon.com/dims4/default/9148c13/2147483647/strip/true/crop/1125x1125+438+0/resize/84x84!/quality/90/?url=https%3A%2F%2Famazon-blogs-brightspot.s3.amazonaws.com%2F47%2F6d%2F7fe296e642859c7ba2a629eda3ba%2Famazon-logo-hero-images-2024.jpg" alt="Amazon Staff"/><p>Written by Amazon Staff</p></div><div class="published"><p> April 16, 2024</p><p>3 min read</p></div></div><div class="tags-mobile"><div class="related-tags v2" data-testid="related-tags"><div class="related-tags__content"><nav><ol><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/sustainability" class="related-tags__link">Sustainability</a></li><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/artificial-intelligence" class="related-tags__link">Artificial Intelligence </a></li><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/packaging" class="related-tags__link">Packaging</a></li><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/aws" class="related-tags__link">AWS</a></li><li style="display:inline-flex"><a href="https://www.aboutamazon.com/news/tag/machine-learning" class="related-tags__link">Machine Learning </a></li></ol></nav><div data-testid="SocialSharesV2" class="share"><div><button class="button LightOutlinedV2 is-reversed has-icon" data-testid="button-fn" type="button">Share<div data-testid="icon-ShareArrowOrange"><svg xmlns="http://www.w3.org/2000/svg" width="20" height="17" fill="none"><path fill="#FF6200" d="m12.158.5 7.207 7.747-7.37 7.242v-4.21C9.046 10.269 2.132 13.473.364 16.5c0 0 1.147-11.116 11.793-11.621V.5Z"></path></svg></div></button></div></div></div></div></div></div></div></div></div><div class="ArticlePage-wrapper ArticleType-article v2-no-nav"><main class="ArticlePage-main v2"><article class="ArticlePage-mainContent"><div class="ArticlePage-articleBody articleBody"><article><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">For the hundreds of millions of items that are sold by Amazon, from a camping tent to a holiday sweater, the box or mailer that arrives on customers’ doorsteps has likely been hand-selected by artificial intelligence (AI).</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-promo"><div class="related-content v2" data-testid="RelatedContent"><div class="related-content__container"><div class="related-content__img"><a href="https://www.aboutamazon.com/news/sustainability/amazon-climate-pledge-fund-ai-recycling"><img alt="Phoebe Wang, Areeb Malik, Rebecca Hu, and Nick Ellis visit a Materials Recovery Facility in San Francisco." height="200" role="" src="https://assets.aboutamazon.com/dims4/default/b5b3102/2147483647/strip/true/crop/1688x1125+156+0/resize/300x200!/quality/90/?url=https%3A%2F%2Famazon-blogs-brightspot.s3.amazonaws.com%2F48%2F69%2Fc5c0cc394981adefe55d6c68a7bb%2Fsized-hero-alt-amazon-glacier-recycling-07a3958-copy.JPG" width="300" class=""/></a></div><div class="related-content__content"><a href="https://www.aboutamazon.com/news/sustainability/amazon-climate-pledge-fund-ai-recycling"><h2 class="related-content__title">How Amazon’s latest Climate Pledge Fund investment is transforming recycling through AI and robotics</h2></a><p>Amazon and Glacier are piloting technology to reduce landfill waste and increase the use of recycled materials in packaging.</p></div></div></div></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">The Package Decision Engine, an AI model that </span><a target="_blank" rel="noopener noreferrer" href="https://www.amazon.science/publications/position-paper-reducing-amazons-packaging-wasteusing-multimodal-deep-learning"><span class="text v2">Amazon designed and built</span></a><span class="text v2">, is able to determine the most efficient type of packaging for each item it learns about, helping reduce the number of cardboard boxes, air pillows, tape, and mailers used to send purchases to customers. The model is an important example of how the company is </span><a target="_self" href="https://www.aboutamazon.com/news/sustainability/how-amazon-uses-ai-sustainability-goals"><span class="text v2">using AI to meet its sustainability goals faster</span></a><span class="text v2">, while also helping reduce packaging, make deliveries more efficient, and ensure products remain protected during delivery. Along with other </span><a target="_self" href="https://www.aboutamazon.com/news/sustainability/amazon-packaging-lab-photo-tour"><span class="text v2">packaging innovations</span></a><span class="text v2">, the model has helped Amazon </span><a target="_self" href="https://www.aboutamazon.com/news/sustainability/how-amazon-is-reducing-packaging"><span class="text v2">avoid over 2 million tons of packaging material</span></a><span class="text v2"> worldwide since 2015.</span><br/><span class="text v2"> </span><br/><span class="text v2">Built on the Amazon Web Services (AWS) cloud, the multimodal AI model can predict when a more durable product like a blanket doesn’t need protective packaging, or when a potentially fragile item like a set of dinner plates might need a studier box. It uses a combination of deep machine learning, natural language processing, and computer vision, and is continuously learning about Amazon’s ever-evolving packaging options. Its decisions are empirically accurate, according to Amazon scientists, meaning that it predicts the most efficient package choice the majority of the time.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-image"><div class="image "><img alt="An infographic on Amazon's Package Decision Engine. " height="743" role="" src="https://assets.aboutamazon.com/dims4/default/27c2787/2147483647/strip/true/crop/1600x900+0+0/resize/1320x743!/quality/90/?url=https%3A%2F%2Famazon-blogs-brightspot.s3.amazonaws.com%2Fae%2F44%2Fea20cb5f4a878f5913315b146532%2Fabout-amazon-inline-inline006-amazon-ai-packaging-packagedecisionengine-16x9-frame-06-1920x1080.jpg" width="1320" class="v2"/><span class="image-caption v2"></span></div></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">Reducing packaging waste is an important part of Amazon’s goal to become a more sustainable company, but choosing the most efficient, optimal amount of packaging that both reduces waste and protects products can be challenging. Plus, Amazon’s product catalog has hundreds of millions of items—and is always growing and changing, in addition to having regional and country-specific products worldwide.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">Prior to the use of AI, Amazon associates used physical testing on individual products to determine how to optimize packaging, but that sustainability work was impossible to scale through human efforts alone. The Package Decision Engine has helped automate portions of this work, allowing Amazon associates to focus on addressing other sustainability challenges.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">“We wanted the ability to quickly identify the most efficient packaging option for each item, while also predicting how safely each product would ship,” said Kayla Fenton, senior manager of technology products with Amazon’s Packaging Innovation team, which includes research scientists and technical program managers. “The use of AI through the Package Decision Engine has allowed us to advance our packaging efficiency work at scale quickly, and it has worked so well that we’re implementing this technology across Amazon’s broader global footprint.”</span><br/></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-heading2"><h2 style="font-weight:600" class="contentHeading">How the Package Decision Engine works</h2></div></div><div class="contentContainer block"><div class="contentItem-role-carousel"><div class=""><div class="carousel standard show-next" data-testid="Carousel"><div class="carousel__slider-container"><div class="slick-slider slider slick-initialized" dir="ltr"><div class="slick-list" style="padding:0px 0"><div class="slick-track" style="width:200%;left:0%"><div data-index="0" class="slick-slide slick-active slick-center slick-current" tabindex="-1" aria-hidden="false" style="outline:none;width:50%"><div><div data-testid="slide-0" class="active" tabindex="-1" style="width:100%;display:inline-block"><div class="carousel__img-container is-img" data-testid="carousel__img-container"><img alt="An infographic on Amazon's Package Decision Engine. 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" loading="eager" width="820" height="462" decoding="async" data-nimg="1" class="carousel__img" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fassets.aboutamazon.com%2Fdims4%2Fdefault%2F0ce3b18%2F2147483647%2Fstrip%2Ftrue%2Fcrop%2F1600x900%2B0%2B0%2Fresize%2F1320x743!%2Fquality%2F90%2F%3Furl%3Dhttps%253A%252F%252Famazon-blogs-brightspot.s3.amazonaws.com%252Fb5%252Fdb%252F3433611143398758e79f67b39864%252Fabout-amazon-inline-inline004-amazon-ai-packaging-packagedecisionengine-16x9-frame-04-1920x1080.jpg&w=828&q=100 1x, /_next/image?url=https%3A%2F%2Fassets.aboutamazon.com%2Fdims4%2Fdefault%2F0ce3b18%2F2147483647%2Fstrip%2Ftrue%2Fcrop%2F1600x900%2B0%2B0%2Fresize%2F1320x743!%2Fquality%2F90%2F%3Furl%3Dhttps%253A%252F%252Famazon-blogs-brightspot.s3.amazonaws.com%252Fb5%252Fdb%252F3433611143398758e79f67b39864%252Fabout-amazon-inline-inline004-amazon-ai-packaging-packagedecisionengine-16x9-frame-04-1920x1080.jpg&w=1920&q=100 2x" src="/_next/image?url=https%3A%2F%2Fassets.aboutamazon.com%2Fdims4%2Fdefault%2F0ce3b18%2F2147483647%2Fstrip%2Ftrue%2Fcrop%2F1600x900%2B0%2B0%2Fresize%2F1320x743!%2Fquality%2F90%2F%3Furl%3Dhttps%253A%252F%252Famazon-blogs-brightspot.s3.amazonaws.com%252Fb5%252Fdb%252F3433611143398758e79f67b39864%252Fabout-amazon-inline-inline004-amazon-ai-packaging-packagedecisionengine-16x9-frame-04-1920x1080.jpg&w=1920&q=100"/></div></div></div></div></div></div></div></div><div class="carousel__btns"><button aria-label="Previous slide" class="disabled" data-testid="prev-button" disabled=""><div data-testid="icon-PrevButton"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" fill="none"><circle cx="11.823" cy="11.823" r="11.323" stroke="#BDBDBD" transform="matrix(-1 0 0 1 24 .355)"></circle><path fill="#1A2029" fill-rule="evenodd" d="M11.259 14.628a.65.65 0 0 1-.919 0l-2.15-2.15a.648.648 0 0 1-.189-.498.648.648 0 0 1 .19-.497l2.15-2.15a.65.65 0 1 1 .918.918l-1.126 1.125h5.184a.65.65 0 1 1 0 1.299h-5.093l1.035 1.034a.65.65 0 0 1 0 .919Z" clip-rule="evenodd"></path></svg></div></button><p class="carousel__btns-text" data-testid="slide-count-text">01 / 02</p><button aria-label="Next slide" class="next-slide " data-testid="next-button"><div data-testid="icon-NextButton"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" fill="none"><path fill="#1A2029" fill-rule="evenodd" d="M12.708 9.333a.65.65 0 0 1 .918 0l2.15 2.15c.136.137.2.319.19.497a.648.648 0 0 1-.19.497l-2.15 2.15a.65.65 0 1 1-.918-.918l1.125-1.125H8.649a.65.65 0 1 1 0-1.298h5.093l-1.034-1.035a.65.65 0 0 1 0-.918Z" clip-rule="evenodd"></path><circle cx="11.823" cy="11.823" r="11.323" stroke="#BDBDBD" transform="rotate(180 11.823 11.823)"></circle></svg></div></button></div><div class="carousel__progress"><ol class="carousel__progress-dots"><li class="dot is-selected" aria-label="dot-0" data-testid="dot-0"></li><li class="dot " aria-label="dot-1" data-testid="dot-1"></li></ol></div></div></div></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">The Package Decision Engine process includes multiple steps to gather information about each item. When an item first arrives at the Amazon fulfillment center, it is photographed in a computer vision tunnel that determines the product’s dimensions, spots defects, and captures multiple images of the product. This also allows the model to detect if there is a bag or box around an item, or detect the presence of exposed glass.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">The model also uses natural language processing and leverages text-based data from each item, such as the item’s name, description, price, and package dimensions. It also collects information in near-real time from customer feedback that is reported through Amazon’s Online Returns Center, product reviews, and other customer feedback channels.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-promo"><div class="related-content v2" data-testid="RelatedContent"><div class="related-content__container"><div class="related-content__img"><a href="https://www.aboutamazon.com/news/innovation-at-amazon/generative-ai-amazon-vp-technology-future-innovation"><img alt="A photo of Vishal Sharma, Vice President, Artificial General Intelligence, standing with his arms crossed in front of a SXSW 2024 backdrop." height="200" role="" src="https://assets.aboutamazon.com/dims4/default/9165452/2147483647/strip/true/crop/1689x1126+156+0/resize/300x200!/quality/90/?url=https%3A%2F%2Famazon-blogs-brightspot.s3.amazonaws.com%2F92%2F74%2F73d8d6f94b03a71c4a09fde00b1a%2Famazon-ai-3-copy.png" width="300" class=""/></a></div><div class="related-content__content"><a href="https://www.aboutamazon.com/news/innovation-at-amazon/generative-ai-amazon-vp-technology-future-innovation"><h2 class="related-content__title">I’m Amazon’s VP of Artificial General Intelligence. Here are 4 reasons why I’m excited about the future of AI.</h2></a><p>Vishal Sharma shares his insights on how innovations in generative AI will help everyone (and everything) on Earth.</p></div></div></div></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">After compiling the information, the model produces a score that predicts the best packaging type to use. The packaging selection is remembered by the model and used to understand future packaging needs.</span><br/></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-heading2"><h2 style="font-weight:600" class="contentHeading">How the Package Decision Engine learns over time</h2></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">Amazon scientists have trained the AI model by showing it millions of examples of products that had been successfully delivered in various types of packaging without damage. They also showed it products that have arrived damaged, along with the keywords and packaging types used in each scenario.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">As a result, the model has learned that certain keywords are important when making packaging decisions. For example, a padded mailer with limited cushioning might not adequately protect an item with the words “grocery,” “screen,” or “stoneware” in the description, so the model would recommend a sturdier option, such as a box. The model also learned that keywords like “multipack,” “bag,” “shrink,” and “pack” were also associated with lower damage rates in the mailer, and indicated the product might already have protective packaging and not need additional protection.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">The model has worked so well that the Packaging Innovation team is expanding its use by training it for deployment worldwide. This includes exposing it to new languages, unique packaging types, and items sold in different countries. The model is already widely used in fulfillment centers in North America and Europe, with components being rolled out in additional locations across India, Australia, and Japan.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">The Package Decision Engine is one of many ways that Amazon is using AI innovation to reach our sustainability, packaging, and waste reduction goals.</span></div></span></div></div><div class="contentContainer block"><div class="contentItem-role-text"><span class="text v2"><div class="text"><span class="text v2">Learn more about </span><a target="_self" href="https://www.aboutamazon.com/news/sustainability/how-amazon-uses-ai-sustainability-goals"><span class="text v2">Amazon’s AI and sustainability efforts</span></a><span class="text v2">.</span></div></span></div></div><div class="contentContainer"><div class="articles-links"><p 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For example, a padded mailer with limited cushioning might not adequately protect an item with the words “grocery,” “screen,” or “stoneware” in the description, so the model would recommend a sturdier option, such as a box. The model also learned that keywords like “multipack,” “bag,” “shrink,” and “pack” were also associated with lower damage rates in the mailer, and indicated the product might already have protective packaging and not need additional protection.\",\"role\":\"text\"}],\"role\":\"block\"},{\"items\":[{\"value\":\"The model has worked so well that the Packaging Innovation team is expanding its use by training it for deployment worldwide. This includes exposing it to new languages, unique packaging types, and items sold in different countries. 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