AI Powered Sales Forecasting System

This paper presents an AI-powered sales forecasting and inventory management system tailored for small- and

medium-sized enterprises (SMEs). By integrating historical sales data, external indicators, and advanced machine learning

models such as Long Short- Term Memory (LSTM) and Gradient Boosting, the system delivers real-time demand predictions

and inventory optimization. Experimental results demonstrate a forecasting accuracy improvement of up to 18% compared to

traditional methods, with Mean Absolute Percentage Error (MAPE) consistently below 7%. The cloud-based dashboard enables

automated decision-making, reducing stock outs and overstocking. The proposed solution enhances operational efficiency and

profitability in dynamic retail environments.