2026-11-03T08:07:33Z https://lifeofresearch.com/oai2

oai:lifeofresearch.com:176 2026-11-02T03:51:54Z type:preprint openaire

The Role of AI-Based Demand Forecasting in Inventory Planning for Seasonal Small Businesses in India Gauransh Yadav Artificial Intelligence Demand Forecasting Inventory Management Small Businesses Seasonal Demand MSMEs India Business Economics This study explores how seasonal changes in customer demand affect inventory planning among selected small businesses in New Palam Vihar and Rajendra Park, Gurugram, and considers whether affordable AI-based demand forecasting could help business owners make better stock decisions. Primary information was collected through face-to-face conversations with approximately 5–10 businesses operating in categories including footwear, electronics, stationery and food items during October 2026. The field observations indicate that festival periods are often busy, while some businesses experience slower trading during periods of intense heat. Festivals and changing fashion trends were identified as demand drivers. Respondents described instances of excess stock and occasional lost sales due to unavailable products. Unsold goods were often discounted or held for a later season. Some businesses maintained records, while others did not. Respondents had limited practical knowledge of AI forecasting but expressed interest in an affordable tool if it could help reduce unsold stock and related losses. The study is exploratory and does not claim statistical representativeness. The findings suggest that useful forecasting solutions should be low-cost, easy to use, understandable and able to work with incomplete business records. Life of Research 2026-11-02 info:eu-repo/semantics/preprint https://lifeofresearch.com/preprints/176 eng https://lifeofresearch.com/preprints/176/files/186/AI_Demand_Forecasting_Public_Research_Final.pdf application/pdf https://creativecommons.org/licenses/by-nc/4.0/ info:eu-repo/semantics/openAccess