sinops Inc. has launched a pilot project for automatic delivery with 0-minute order confirmation at selected ぎゅーとら stores. AI will automatically determine optimal order quantities and deliveries, with deliveries taking shelf capacity into account, with the aim of significantly reducing the workload.
Against a backdrop of worsening labour shortages, retailers are moving to minimise store operations. At the end of 2025, sinops Inc. held the leading 36.7% share of Japan's demand forecasting solutions market for food supermarkets, and has built a track record including completing the migration of 129 Co-op Kobe stores to its system by June 2026. NEC and Fujitsu are also reportedly promoting demand forecasting and digital transformation in distribution, while conventional automatic ordering has been regarded as problematic because it presupposed human intervention.
The automatic delivery system being tested in the pilot project aims to eliminate store adjustment work, with AI calculating the optimal quantity and completing the process through automatic delivery. The products can be placed directly on shelves upon arrival, completing the work while also potentially reducing backroom inventory. A scheme has also been established to fully compensate for any increase in losses during the pilot period, lowering the psychological and financial barriers for participating companies.
This pilot project, which aims to build a sustainable distribution structure, covers chilled Western-style and Japanese-style daily-delivery products at selected ぎゅーとら stores. During the project, quantitative effects including achievement of 0-minute order confirmation, inventory reduction, maintenance of the out-of-stock rate and reductions in shelf-stocking hours will be assessed. The results are scheduled to be published after the project ends. As labour shortages in the retail sector worsen, efficiency gains and the reduction of waste in the supply chain through services using AI technology are expected to contribute to addressing these challenges.