Two large retailers used the artificial intelligence (AI) solutions Shelf Engine and Afresh to improve their order accuracy, resulting in a 14.8% average reduction in food waste per store. While the two pilots were conducted at large retailers, the AI solutions also work for smaller chains.

All pilot stores saw positive results, including reduced shrink and higher profits that more than covered the cost of the AI solution. With the amount of food waste saved in the pilots, 26,705 tons of CO2 e emissions from landfills were prevented.

Beyond food savings, labor efficiencies in reduced ordering time, managing shrink, restocking, and more were increased by up to 20% per store.

Key benefits included increased food waste prevention, reduced shrink, increased sales, higher margins, and greater labor efficiency—all of which were measurable as early as eight weeks into the pilots.

In both cases, the successful pilot led to the retailer significantly scaling its adoption of the AI solution across more of its stores.

Key challenges were organizational buy-in, traditional retail mindsets, and seasonality.

If the entire grocery sector were to implement these solutions, an estimated 907,372 tons of food waste could be prevented, representing 13.3 million metric tons of avoided CO2 e emissions and more than $2 billion in financial benefits for the sector.