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Artificial intelligence won’t just reshape corporate America: It could also change the way companies hire seasonal workers.
Gaurav Saran, CEO of ReverseLogix, is helping a growing number of retailers make their returns process more efficient by automating the process through a single platform. According to Saran, the cloud-based end-to-end returns management platform can significantly reduce the number of hours required to complete the returns process. But it simultaneously reduces the number of people needed during the holiday madness.
“Most of our customers have seen a two to three times improvement in the returns process, faster and more accurately,” Saran said. In turn, he predicts that a “fairly significant number” of workers, between 20 and 30%, could be replaced as early as next year.
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Saran’s platform, launched in 2014, oversees the entire returns process from the moment a customer initiates a return through the stages of inspection, processing, repair, restocking or recycling.
Amazon.com Inc. packages are seen on a conveyor belt with other small packages. (Luke Sharrett/Bloomberg via Getty Images)
Traditionally, companies have relied on a highly inefficient returns process that involved manual paperwork, inconsistent management across warehouses or channels, limited visibility, high costs and poor customer experience, Saran said. These returns operations also required hiring workers to manually inspect products and determine whether an item could be restocked or should be thrown out.
But Saran’s mission has been to transform the return process cost burden that it has become a valuable part of the supply chain, capable of generating revenue or recovering value through repair, resale or recommerce.
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Saran said his system gives businesses more predictability. Most of its customers, which range from Samsonite and FedEx to Wilson and Cole Haan, were able to process returns faster with the new system, reducing the risk of human error and saving them money.
A warehouse initiating certain returns using ReverseLogix technology. (InverseLogix)
“With seasonal workers, there is a certain level of training that allows them to gain the expertise to look at things,” Saran said. “All of these things add time and cost compared to an AI-based visual inspection.”
He noted that there is a lot of AI-related data around this product that tells the system what state it is in and that as the model becomes better trained, the efficiency and accuracy will become “significantly higher than a traditional worker performing the same process.”
Saran believes this type of process will become more common because it gives companies a clear way to reduce costs.
AI expert and business strategist Marva Bailer told FOX Business that AI has already changed the vacation workforce “in visible and invisible ways.”
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For example, retailers used to hire greeters or floor associates whose primary job was directing customers, answering basic inventory questions, or guiding shoppers to the correct counter. Now, AI “handles much of that with faster self-checkout guidance, interactive product search, real-time translation and digital guidance,” she said.
A warehouse initiating some returns. (InverseLogix)
Checkout areas traditionally faced bottlenecks, force retailers to open additional lanes or deploy swap body crews during peak weeks, according to Bailer. But in recent years, Bailer said many of these cutting-edge roles have shifted to AI-based self-checkout, mobile scanning and payment, and rapid item recognition systems that stabilize lines without increasing staffing levels.
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However, in many cases, these tools complement workers rather than replacing them. For example, they can absorb transaction volume so associates can “focus on service, exceptions and the human moments that define the season,” Bailer said.
Although Saran believes the number of workers involved in the return process will “decrease significantly over the next two years,” he said workers will not be entirely replaced. Even with its technology, some products will still need humans, especially in difficult cases and to verify data, understand analytics and set up systems.
As tasks become more complex, there will always be jobs for humans. But the day-to-day, routine work of processing returns will mostly be done by machines or automation, Saran said.