Focusing again on AI , Helen points to optimisation as a major positive .

“ AI will help optimise transportation routes for returns ,” she says , highlighting how real-time data analysis can reduce fuel consumption and logistics costs . “ Precision allows businesses to manage inventory more effectively .”

In the same vein , Kristen points to waste reduction , stating that AI “ has a clear role in reducing returns -associated waste ”.

She further outlines how AI can prevent returns through better recommendations , reduce fraud and improve demand forecasting , ultimately minimising unnecessary product movement .

Tim connects sustainability directly to business performance .

“ In returns , sustainability aligns with a retailer ’ s bottom line ,” he remarks . Tim also points to the importance of processing returns efficiently , with minimal transportation and handling .

Sender provides a comprehensive perspective on environmental impact , claiming that retailers often help to manage returned goods effectively and cut down on waste .

“ Returns contribute significantly to waste generation , energy use and carbon footprint ,” he continues .

Projected size of reverse logistics market by 2032 ( Fortune Business Insight )

North America ’ s market share of reverse logistics ( Contimod )

Product returns rate ( Contimod )

“ The number of times items are handled during the returns process has environmental consequences .”

AI is not just a cost-saving mechanism in reverse logistics , but a powerful tool for creating more sustainable , efficient processes that will benefit both businesses and the environment .

106 January 2025