Collaborative AI Agent Architecture for Autonomous Retail Inventory and Allocation Management

Abstract

Autonomous retail management is bolstered by a collaborative architecture for inventory ownership and allocation. The use case investigates cross-suppliers’ vertical order orchestration; the aim is to design a control solution capable of managing partitioned inventories spread over multiple retailers, minimising fulfilment leads and costs. Enabling artificial intelligence agents fulfil supply chain roles: estimating future inventory behaviours, optimally allocating stock under uncertainty and guiding downstream suppliers to improve the collective service level. The complete inventory allocation control cycle is exercised with real data from the automotive parts market. A novel combination of computer agents realises latent control layers including inventory management for autonomous retail. Directed information flows control collaborative functions like product fulfilment and stock-picking distribution while inter-agent roles share decision ownership – allocation, demand forecasting, gainful negotiation. Supply chains poised for full autonomy integrate cross-organisations’ inventories budgeted vertical offers.