The unpredictable swings of the current economy are adding to what is an unquestionably tumultuous moment for retail. The industry facies uncertainty around what cargo will move in and out of the U.S., and the impact on sales. In response, retailers are looking to tighten operations and save money in places they can control — especially returns.

A focus on efficient returns can also help retailers strengthen their environmental, social and governance efforts, by reducing volumes and mitigating fraud. The reverse logistics process, including shipping, inspecting, and repackaging, generates more than 24 million metric tons of CO₂ emissions and dumps 9.5 billion pounds of returns in landfills annually. 

Through the use of artificial intelligence and data analytics, retailers can take a scalpel to their returns programs. In the process, they can not only reduce waste, but also fight back against costly consumer practices like bracketing and wardrobing. A data-driven, efficient reverse logistics and returns strategy can boost profitability overall.

Consumers aren’t blind to the effect that retailers have on the global footprint. A PwC survey found that eight in 10 global consumers would pay more for items that are sustainably produced — and that respondents would pay nearly 10% more for an eco-friendly product. Additionally, nearly 40% of the consumers in the survey said they’re monitoring a company’s sustainable practices, including recycling methods.

While optimizing returns isn’t the silver bullet for countering losses from trade issues, the strategy can help fill some gaps and improve business operations. The National Retail Federation estimates that proposed tariffs on six product categories could result in a loss of $46 billion in consumer spending. 

Total retail returns reached $685 billion in 2024, representing 13.21% of total sales, according to research from Deloitte and Appriss Retail. Returns and claims abuse and fraud cost retailers $103 billion —second only to shrink, which is estimated to cost $142 billion. Artificial intelligence and key partnerships that help a retailer have total visibility of the returns process, both online and offline, and make it less vulnerable to incidents of returns fraud.

Retailers often attempt to offset returns by writing stringent rules such as a “no receipt, no return” policy. Yet a hard-line approach can turn away loyal shoppers. Retail Dive and Appriss Retail research found that 55% of consumers won’t buy from a retailer with a restrictive return policy. 

Additionally, return policies are often implemented by staff members in-store or in call centers. Their primary mission is to provide good service and enhance the consumer experience — not police potential fraud. This conflict makes them extremely vulnerable to social engineering by professional returners who convince staff to override policies. The result: good customers experience friction, and bad actors get away with it.

By analyzing real-time data across all channels, AI can identify behavior that falls outside the norm. For example, a customer with high purchases will likely also have high returns, but in the end they’re the most profitable customer. Using AI-enabled return fraud applications will allow that good customer to continue to return products regardless of total return value. The opposite is true for fraudsters. AI can help identify them with specific behavior models that will either introduce friction into the return or reject it outright.

Retailers use AI in many ways throughout the supply chain, developing eco-friendly routes for inventory, streamlining returns authorization inspection, and sorting. Fraud detection for returns fits right in. With the support of data analytics and machine learning, retailers can run more efficient returns and reverse logistics strategies. They can move products more efficiently, prevent returns fraud, reduce return rates, save money, and reduce their impact on the environment.

Pedro Ramos is chief revenue officer at Appriss Retail.