Key points are not available for this paper at this time.
Artificial intelligence (AI) has revolutionized demand forecasting within Enterprise Resource Planning (ERP) systems, offering a powerful tool to enhance accuracy and efficiency in predicting future demand patterns. This literature review explores the impact of AI-based predictive analytics on demand forecasting in ERP systems by synthesizing and analyzing existing research. This paper provides a comprehensive examination of the transformative effects of AI-driven demand forecasting across diverse industries, including fashion retail, biopharmaceuticals, energy management, and transportation. We highlight the unique benefits and applications of AI-driven demand forecasting, such as anticipating customer needs, optimizing inventory levels, and making data-driven decisions, ultimately leading to a competitive edge in the marketplace. Our study emphasizes the importance of AI integration into ERP systems for businesses seeking to enhance decision-making and achieve organizational success in today's dynamic and competitive business landscape. By providing valuable insights and showcasing significant improvements in forecasting accuracy, real-time insights, supply chain efficiency, and risk management facilitated by AI-based predictive analytics, this research contributes to advancing knowledge in the field and offers practical guidance for businesses and researchers alike.
Fathima et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: