Impact of Artificial Intelligence and Ethical Practices Adoption on Demand Forecasting and Procurement Efficiency of Health Commodity Supply Chains: A Deep Review of Literature

Abstract

Abstract This study explores the transformative impact of artificial intelligence (AI) on enhancing demand forecasting and procurement efficiency within health commodity supply chains. It highlights the integration of advanced AI algorithms, including machine learning (ML), natural language processing (NLP) and optimisation techniques, which facilitate more accurate predictions, streamlined sourcing and improved inventory management. The analysis emphasises the essential interplay between technological innovation and ethical practices, underlining the importance of data privacy, transparency, fairness and accountability as foundational elements for trustworthy AI deployment in healthcare procurement. Implementation strategies take into account infrastructure requirements, change management and potential barriers to adoption. The investigation further examines organisational and workforce implications, scalability, sustainability and comparative experiences on both global and local scales, illustrating the complex challenges and opportunities presented by AI in health commodity procurement. Future directions suggest the convergence of AI with Internet of Things, blockchain and cloud computing, advocating for responsible innovation that adheres to ethical standards to optimise supply chain resilience, equity and operational performance in healthcare delivery.