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Artificial intelligence isn’t just reshaping corporate America – it could also change how companies hire seasonal workers.
ReverseLogix CEO Gaurav Saran is helping a growing list of retailers make their returns process more efficient by automating the process through a single platform. The cloud-based, end-to-end returns-management platform, according to Saran, can significantly cut down on the number of hours of time it takes to complete the return process. But, it simultaneously reduces the number of people needed during the holiday craze.
“Most of our customers have seen anywhere from two to three times the improvement in speed and accuracy of the returns process,” Saran said. In turn, he projected that a “pretty sizable number” of workers, anywhere from 20% to 30%, could be replaced as soon 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 to the inspection, processing, repair, restocking or recycling stages.
Traditionally, companies have relied on a very inefficient return process that involved manual paperwork, inconsistent handling across warehouses or channels, limited visibility, high costs and a poor customer experience, Saran said. These return operations also required hiring workers to manually inspect products and determine whether an item could be restocked or needed to be discarded.
But Saran’s mission has been to transform the returns process from the cost burden that it’s become into a valuable part of the supply chain, one that can generate revenue or recover value through repair, resale or recommerce.
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Saran said that his system gives companies more predictability. Most of his customers, which range from Samsonite and FedEx to Wilson and Cole Haan, have been able to process returns faster with the new system, reducing the risk of human error and saving them money.
“With seasonal workers, there’s a level of training that comes in for them to gain the expertise on how to look at stuff,” said Saran. “So all of those things add cost and time when compared to an AI-based visual inspection.”
He noted that there’s a lot of AI-related data around that product that tells the system what condition it is in and as the model becomes more trained, the efficiency and accuracy will become “significantly higher than a traditional worker doing the same process. “
Saran believes this type of process will become more mainstream as it gives companies a clear way to cut costs.
AI expert and business strategist Marva Bailer told FOX Business that AI has already been changing the holiday workforce “in visible and invisible ways.”
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For example, retailers used to hire greeters or floor associates whose main job it was to direct customers, answer basic inventory questions or guide shoppers to the right counter. Now, AI “manages much of that through faster self-checkout guidance, interactive product search, real-time translation and digital wayfinding,” she said.
Checkout areas traditionally faced bottlenecks, forcing retailers to open extra lanes or deploy mobile handheld checkout teams during peak weeks, according to Bailer. But over the past few years, Bailer said many of these surge roles shifted to AI-enabled self-checkout, mobile scan-and-pay and rapid item recognition systems that stabilize lines without expanding headcount.
However, in many cases, these tools supplement workers rather than replace them. For instance, they can absorb transactional volume so associates can “focus on service, exceptions and the human moments that define the season,” Bailer said.
While Saran believes that the number of workers that are involved in the return process will “dramatically decrease over the next couple of years,” he said that workers won’t be fully replaced. Even with his technology, certain products will still need humans, especially in difficult cases and for checking data, understanding analytics and setting up systems.
As the tasks get more complex, there will still be jobs for humans. But the everyday, routine work of processing returns will mostly be done by machines or automation, Saran said.
