AI-Powered Demand Forecasting Tool Using Machine Learning and Explainable AI

Prathmesh Thorat, Atharv Pol, Gousiya A. Khanche and Supriya S. Surve

International Journal of Scientific Research in Science and Technology, 2026, vol. 13, issue 3, 91-98

Abstract: This paper presents an AI-based demand forecasting system designed to predict product demand using historical sales data. The system integrates machine learning concepts with visualization techniques to generate accurate and interpretable results. It is implemented as a web-based application using the Streamlit framework, allowing users to upload datasets, perform automated preprocessing, and obtain demand predictions. The predicted outputs are presented using graphical representations such as bar charts and distribution plots, making it easier to analyze patterns and trends. This improves the usability of the system by helping users understand results without requiring technical expertise. The proposed approach demonstrates how data-driven forecasting can be combined with simple visualization to support practical business applications, particularly in planning and analysis tasks.

Keywords: Demand Forecasting; Machine Learning; Explainable AI; Predictive Analytics; Supply Chain Analytics (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v13:y2026:i3:id:1575

DOI: 10.32628/IJSRST26133219

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