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Enhancing Inventory Control and Reducing Holding Costs Using Generative AI
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Author(s): R. Velmurugan (Karpagam Academy of Higher Education, India), R. Bhuvaneswari (Dr. Mahalingam College of Engineering and Technology, Pollachi, India), Maksud A. Madraswale (Presidency University, India)and Ravi Thirumalaisamy (Modern College of Business and Science, Oman)
Copyright: 2026
Pages: 28
Source title:
Impact of Generative AI on Food Supply Chain Management
Source Author(s)/Editor(s): Bhupinder Pal Singh Chahal (Yorkville University, Canada), Arokiaraj David (SBS Swiss Business School, RAK, UAE), Amrinder Singh (Jain University, India), Geetika Madaan (Marwadi University, India)and Gurmeet Singh (The University of the South Pacific, Fiji)
DOI: 10.4018/979-8-3693-9856-2.ch010
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Abstract
The role of generative AI in enhancing inventory control and reducing holding costs in supply chain management. Traditional inventory management methods often struggle to balance stock levels, leading to overstocking or understocking, which incurs additional costs. Generative AI, through advanced predictive models, allows businesses to simulate various demand scenarios, improving forecasting accuracy and optimizing stock levels. By incorporating real-time data and automating decision-making, generative AI helps reduce overstocking, minimizes holding costs, and improves operational efficiency. This paper discusses key applications of generative AI, including demand forecasting, stock optimization, and automated reordering processes, while also addressing challenges such as data quality and system integration. The successful implementation of AI in inventory control provides companies with a competitive edge in an increasingly complex and dynamic supply chain landscape
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