The second-largest corporate employer has bet big on robot workers to scale.
Wheeled mobile robots move tall inventory pods filled with items inside an Amazon fulfillment center. Credit: Amazon
No organization in the world operates more robots than Amazon. The company already has more than 1 million robots working in warehouses around the clock to make tens of millions of same-day and one-day package deliveries happen on a daily basis—and Amazon is poised to significantly grow that robotic fleet in the coming years as it establishes new factories to churn out increasingly more capable robot workers.
Despite deploying so many robots, Amazon is also the second-largest corporate employer in the world, with more than 1.5 million full-time and part-time human workers, according to its 2025 annual report. Amazon executives say that the growing robot fleet has eased the burden on its human workforce by taking on the toughest fulfillment center tasks that carry the greatest risks of physical fatigue and injury. But labor advocacy groups and independent researchers point to evidence suggesting that warehouse automation driven by AI is not all upside for the humans who work alongside robots.
“For the last 100 years, most of the automation that we’ve seen usually happens away from workers—you’re taking that high-risk task away from the worker, and you’re doing so in a way that is not physically proximate,” Brian Greenwood, professor of business at George Mason University, told Ars. “The rise of collaborative robots really changes that dynamic for two reasons: one is that it is physically proximate, and two, the robot has the ability to dictate the pace of work.”
In many ways, robotics and AI are well suited to the relentless pace of work that is already happening inside e-commerce fulfillment centers. Amazon’s promise of speedy deliveries for its 200 million Prime subscribers in particular requires hundreds of thousands of human employees to speedily assemble and ship out customer orders that often combine a dizzying array of products.
Much of the work in fulfillment centers also frequently involves “dull, dirty and dangerous” tasks that people may prefer to hand over to robots. The injury and illness rate for workers in the US warehouse sector has typically been more than double the average across all industries, according to the US Occupational Safety and Health Administration.
“You have almost 2 million people working in the warehousing sector in the United States, and it’s characterized by very high turnover and very high workplace injury rates,” said Greenwood.
But robots are still far from capable of handling the many different tasks that human workers can perform. So Amazon still has a massive human workforce working in tandem with the company’s growing fleet of wheeled robots and robotic arms—and workplaces can get complicated when humans are expected to keep pace with robotic counterparts.
Amazon’s robotic era
Amazon has rapidly built its robotic fleet following the pivotal decision to acquire the robotics company Kiva Systems in 2012. Kiva was among the earliest companies to pioneer wheeled mobile robots that bring racks of items to warehouse workers, instead of requiring people to continually walk around grabbing items off of shelves inside fulfillment centers.
Since the acquisition, Kiva was renamed Amazon Robotics and has focused on deploying an array of mobile robots and robotic arms that Amazon primarily manufactures in-house at facilities in Massachusetts. This year, the company also announced it would build additional production factories in Austin, Texas, and Greenwood, Indiana, to churn out even more robots in the future.
“There’s a theme of how we look at the challenges that we can help our associates and our employees with, and how we can make our customers’ lives better through these technologies,” Scott Dresser, vice president of Amazon Robotics, told Ars. “Each step of the way, [we are] tackling a hard or deep set of technical challenges to achieve that goal.”
Most of Amazon’s million-robot fleet still consists of those wheeled mobile robots. The company claims that its robotic Sequoia system can identify and store items up to 75 percent faster at fulfillment centers by coordinating swarms of such robots. Hercules and Titan robots, the size of a pool table or a baby grand piano, respectively, roam warehouse aisles to retrieve tall fabric shelving units called pods packed with plastic tote crates and bring them to human employees at various workstations.
Such mobile robots typically follow grid lines of stickers laid out on the floor and stay within fenced-in areas away from human employees. But the newest mobile robot, called Proteus, has sensors that allow it to operate safely around humans and other objects in a more free-roaming role.
Those swarms of mobile robots traveling through narrow lanes between rows of storage pods can also sometimes create robotic traffic jams. That is why Amazon began coordinating its robots using a suite of AI foundation models collectively named DeepFleet, which can help predict potential robot congestion ahead of time.
More recently, Amazon has been deploying a growing number of robotic arms that can grab items stowed high up inside inventory pods, sort packages and place them in carts or on top of mobile robots, and handle the many different individual products that Amazon customers order when shopping online.
The company expects to more than double its existing fleet of robotic arms this year, according to Amazon CFO Brian Olsavsky in a July earnings call. When Ars sought clarification, Dresser described the current number of deployed robotic arms as being in the single-digit thousands.
A robotic arm system called Cardinal uses a suction system to grab boxes from a pile of Amazon packages and stack them inside a rolling cart.
A robotic arm system called Cardinal uses a suction system to grab boxes from a pile of Amazon packages and stack them inside a rolling cart. Credit: Amazon
The robotic arms race
Amazon first bought third-party robotic arms to help lift and stack heavy pallets and bins inside its fulfillment centers. But the first robotic arm developed in-house by Amazon Robotics to sort individual mailer envelopes and boxes from cluttered piles, called Robin, began testing in 2021 before debuting at a facility in Lakeland, Florida, in 2022.
“With Robin, it was really that first attempt at taking a number of customer orders all in a jumble and building the advanced robotics to identify the items in that scene, to strategize on how to pick them up and build a motion plan that would be successful in placing it down on one of our mobile drive units,” Dresser explained.
The robotic arm uses eight suction cups to pick up individual packages. But before it takes any action, the robot’s software analyzes a top-down view of the conveyor belt cluttered with packages and quickly ranks possible picking actions.
In a 2023 research paper, the Amazon Robotics team described having developed several picking strategies for the robots to follow early on—but each had its own limitations. One strategy that prioritized picking larger packages encountered challenges when smaller packages lay on top of or overlapped with larger ones. Another strategy that favored picking up packages near the top of piles would fail in practice to retrieve “unreachable picks” and partially buried packages.
Improvements came from replacing such hand-crafted algorithms with an AI approach known as machine learning. The machine learning model initially trained on more than 394,000 picking actions from deployed robotic arms to estimate pick probabilities of success, and then used an online pick ranker to prioritize optimal actions for the Robin robots.
The best machine-learning method in that trial achieved a 93.73 percent success rate compared to 92.28 percent success for the best-performing traditional algorithm. That may seem trivial at first glance, but it meant the machine-learning method resulted in about 16,500 fewer failed picks than the traditional method during a work period involving more than 1 million total picks. That matters for an operation like Amazon’s that prioritizes speed and efficiency at scale.
The Amazon Robotics team further showed how such a machine-learning method could reduce the failed pick rate by 20 percent during an experiment involving 2 million picks by robotic workstations set up to resemble the operations of Amazon’s Robin fleet. They presented this work at the International Symposium on Experimental Robotics in July 2025.
Next up was Cardinal, a robotic arm that can place packages weighing up to 50 pounds into wheeled carts that are eventually brought to Amazon trucks waiting in loading docks. These robots first began operating at a facility in Nashville, Tennessee, in November 2022.
“Think of it as a game of Tetris: You’re sorting packages, and you’re placing them into the cart, and you want to be able to pack that as densely as you possibly can,” Dresser told Ars. “Dense containers are great from a sustainability perspective and from a transportation cost perspective.”
Cardinal built on lessons learned from Robin’s development in picking up and manipulating packages, while adding the capability to densely pack customer orders into the carts. Amazon has just started to deploy Cardinal in larger numbers and will continue to do so over the next several years, Dresser said.
A robotic arm system called Sparrow can handle millions of different products while packing container-size totes.
A robotic arm system called Sparrow can handle millions of different products while packing container-size totes. Credit: Amazon
AI-driven robot successors
Robin and Cardinal can handle several dozen package variations. But the newer Sparrow robotic arm was developed to tackle an even more challenging task—handling the hundreds of millions of products of varying shapes and sizes that can go into customer orders.
Specifically, Sparrow focuses on consolidating items from partially filled container-size totes to create densely packed totes. When items get picked out as customer orders are being fulfilled, Sparrow continually refills the totes.
“When we think about how AI applies to the physical space in robotics, Sparrow was really the first place where we truly deployed foundation models that enabled us to deal with that high diversity of products,” Dresser told Ars.
Such foundation models have helped the Amazon Robotics team to efficiently identify and classify those hundreds of millions of items to develop new robotic strategies for grasping them, Dresser explained. They also eliminated the need for manually coding every single item.
More recently, the Amazon Robotics team has created a foundation model for robotic perception that can handle new, never-before-seen products that may end up in Amazon fulfillment centers. The team also developed a generalized action model compatible with different types of robotic arms that may use varying combinations of suction and finger grasping.
“If you need to build ad hoc perception models for every such task and embodiment, that just doesn’t scale,” Kapil Katyal, a senior applied science manager at Amazon Robotics, said during a presentation attended by Ars at the Intelligent Robots & Systems conference held in Pittsburgh on September 29.
“So one of the initiatives we took up in our team was to design a foundation model which could work for any new embodiment of robots that we deploy, and across all of the perception tasks that we need to perform over those,” Katyal said.
Most of the robotic arms have relied primarily on vision. But Amazon’s newest robotic arm, Vulcan, is the first to combine vision with force feedback sensors capable of providing a sense of touch. This enables the robot to accurately pick out or stow away items within the fabric-covered inventory pods.
“You need to be able to insert an item, create space, or pull something out,” Dresser said. “Those are really hard things to do with traditional non-touch-based systems today, like the suction-based systems that are part of Sparrow.”
Vulcan initially began operating at Amazon fulfillment centers in Spokane, Washington, and Hamburg, Germany, starting in 2025. It is not widely deployed yet, but Dresser said the company expects to scale up use of this robotic arm in 2027.
The Vulcan robotic arm has force-feedback sensors that provide a sense of touch as it picks and stows items in tall inventory pods.
The Vulcan robotic arm has force-feedback sensors that provide a sense of touch as it picks and stows items in tall inventory pods. Credit: Amazon
Parsing the human impact
Each new robot has benefited Amazon’s human workforce, according to the company. For example, Vulcan focuses on picking and stowing items located in the top rows of inventory pods that would otherwise require a person to use a step-ladder, along with handling items located just above the floor. That enables employees to focus on picking and stowing items that are within more comfortable reach.
But investigations by labor advocacy groups, journalists, and the US Congress have painted a less rosy picture of Amazon’s automation drive over the years. The Strategic Organizing Center (SOC), a coalition of trade unions headquartered in Washington, DC, published reports in May 2021 and April 2022 showing higher injury rates at Amazon’s robotic warehouses compared to non-robotic warehouses. That analysis drew on injury data reported by companies to the US government from 2017 through 2020.
“Amazon likes to talk about its latest robots because it doesn’t want to talk about the tens of thousands of Amazon workers who are injured every year due to Amazon’s obsession with maximizing speed and minimizing costs,” Joan Moriarty, director of strategic research and Campaigns at SOC, said in an email to Ars.
The organization also gathered nearly 1,000 responses from Amazon workers in an online survey conducted in February 2021. “Workers consistently report that the presence of robots increases the pace of work expected in Amazon facilities, forcing them to make fast, repetitive motions, substantially increasing the risk of injury,” Moriarty said.
The US Senate Committee on Health, Education, Labor and Pensions (HELP) also conducted a 2024 investigation led by Sen. Bernie Sanders (I-Vt). The committee’s report noted how Amazon’s internal data also suggested a link between robotic productivity and increased pressure on human workers, leading to higher injury rates.
Amazon has described these reports as flawed and being reliant on older data predating the deployment of its most modern robots, including the robotic arms that became operational over the past several years. The company also touted improvements in its overall workplace injury rates without detailing any potential differences between robotic and non-automated warehouses.
“All of these claims ignore the fact that since 2019 our Global Recordable Incident Rate has improved 43 percent and our Global Lost Time Incident rate, which includes the most serious injuries that require employees to take time away from work, has improved 70 percent,” an Amazon spokesperson told Ars. “Our consistent year-over-year improvements have worked in parallel with our robotics growth across our operations network.”
The most nuanced findings on Amazon’s automation drive may come from a research study published in the journal ILR Review in April 2025. That analysis showed Amazon’s robotic warehouses had a 40 percent decrease in severe injuries compared to legacy fulfillment centers—which suggests some benefits from having robots take on the most physically challenging and risky tasks.
However, the same study also found that robotic fulfillment centers had a 77 percent increase in less severe injuries associated with physical strain from repetitive motions.
“At least one of the mechanisms by which this appears to be manifesting is through the pace of work, in that pick rates for the robotic fulfillment centers are off the charts higher,” said Greenwood at George Mason University, who was one of the paper’s coauthors.
A faster pace of work driven by partial automation could mean “the robot is dictating the pace of work” and spurring human employees to perform certain repetitive actions more quickly, Greenwood told Ars. “That appears to be what’s driving the strains and the sprains that we observe,” he said.
The study drew in part on Amazon company data obtained by journalists at Reveal and The Center for Investigative Reporting, covering weekly data at more than 150 Amazon warehouses from 2016 through 2019. Although the data is older, Greenwood said the findings are still relevant to Amazon’s ongoing automation efforts.
“I haven’t seen a tremendous amount of evidence to suggest that these dynamics are changing, inasmuch as you still have a tremendous amount of turnover in the warehousing context—and that’s not just Amazon,” Greenwood said.
Greenwood and his colleagues also analyzed online comments posted on Reddit by Amazon fulfillment center employees. In those comments, Amazon employees described work at robotic fulfillment centers as being less physically stressful but also mentally exhausting because of the physical repetitiveness and faster pace associated with higher productivity expectations.
Amazon has opened new roles for employees to build and maintain mobile robots and robotic arms.
Amazon has opened new roles for employees to build and maintain mobile robots and robotic arms. Credit: Amazon
The future of work
An obvious question is whether automation efforts by Amazon and other companies will end up replacing some potential human hires with robots. For its part, Amazon has touted the robotics push as providing new job opportunities for human employees. Fulfillment centers with advanced robotics typically require 30 percent more employees working in reliability, maintenance, and engineering roles, and the new facilities for manufacturing additional robots will also supposedly bring more than 300 jobs each.
“As we recognize that each of these robotics [developments] can change the nature of work, we’re providing opportunities for our employees to upskill and learn some of these things,” said Dresser at Amazon Robotics. “We’ve actually increased the number of robotic maintenance technicians that we have in the network by over 30 percent, and that is a much higher-skilled, higher-compensated job.”
The company has also described its automation efforts as going hand in hand with a growing business that needs more human employees. “As we’ve deployed robots over the past decade, we’ve seen our operational footprint grow, creating hundreds of thousands of jobs as we expanded our network,” the Amazon spokesperson told Ars.
However, there are apparently internal discussions within Amazon about robots potentially reducing the need to hire humans. In October 2025, The New York Times reported on internal strategy documents suggesting that the robotics push could allow the company to reduce projected hiring needs in the United States by more than 160,000 people by 2027 and 600,000 people by 2033. (An Amazon spokesperson responded at the time by saying the documents reflected the views of just one group inside the company.)
Even as Amazon looks to build out its robotic fleet beyond the million-robot mark, discussions about the company’s workplace safety and working conditions are unlikely to go away. Although just a very small fraction of Amazon’s hundreds of thousands of employees have unionized in the United States, labor unions have “traditionally served a very good role in terms of improving worker safety,” Greenwood said.
“Now, obviously, I understand that firms are not always excited to engage in that conversation, and I can’t say that would solve the problem here,” Greenwood told Ars. “But developing a better relationship between management and labor is usually the best path forward to try to figure out how to reduce these injury rates, which would have benefits for Amazon as well.”
The first Amazon Labor Union that was organized among workers at a warehouse in Staten Island, New York, in April 2022, has been pushing what it describes as a Safety Bill of Rights that outlines changes it would like to see to make their workplace safer. The image that accompanies the document declares: “We are not robots.”
Jeremy Hsu is a reporter exploring a wide range of topics across deep tech and AI. He has previously written for New Scientist, Scientific American, IEEE Spectrum, Wired, Undark Magazine and MIT Tech Review, among many other publications, about topics such as deepfakes, data centers, drones, battery tech, robotics, and GPS jamming. He also has a Master of Arts in Journalism from NYU, and a bachelor’s degree from University of Pennsylvania in History and Sociology of Science, with a minor in English.
