AI agents for inventory control: human, LLM and operations-research complementarity

A research paper evaluates combinations of operations-research algorithms, large language models and human intervention for inventory-control decisions. The result supports a hybrid architecture: mathematical methods enforce constraints, language models provide context and humans arbitrate situations not captured by the model. Inventory control systems should make these responsibilities and override boundaries explicit.