Showing 1–1 of 1 results for author: Mastoi, Q

Agentic AI Framework for Smart Inventory Replenishment

Authors: Toqeer Ali Syed, Salman Jan, Gohar Ali, Ali Akarma, Ahmad Ali, Qurat-ul-Ain Mastoi

Abstract: In contemporary retail, the variety of products available (e.g. clothing, groceries, cosmetics, frozen goods) make it difficult to predict the demand, prevent stockouts, and find high-potential products. We suggest an agentic AI model that will be used to monitor the inventory, initiate purchase attempts to the appropriate suppliers, and scan for trending or high-margin products to incorporate. Th… ▽ More In contemporary retail, the variety of products available (e.g. clothing, groceries, cosmetics, frozen goods) make it difficult to predict the demand, prevent stockouts, and find high-potential products. We suggest an agentic AI model that will be used to monitor the inventory, initiate purchase attempts to the appropriate suppliers, and scan for trending or high-margin products to incorporate. The system applies demand forecasting, supplier selection optimization, multi-agent negotiation and continuous learning. We apply a prototype to a setting in the store of a middle scale mart, test its performance on three conventional and artificial data tables, and compare the results to the base heuristics. Our findings indicate that there is a decrease in stockouts, a reduction of inventory holding costs, and an improvement in product mix turnover. We address constraints, scalability as well as improvement prospect. △ Less

Submitted 28 November, 2025; originally announced November 2025.

Comments: Presented at International Conference on Business and Digital Technology, Bahrain, Springer Nature, 27 November 2025