GENERATIVE AI FOR SUPPLY CHAIN OPTIMIZATION: OPPORTUNITIES AND ETHICAL RISKS IN PROCUREMENT

Abstract

The introduction of Generative Artificial Intelligence (Generative AI) technology in supply chain management has facilitated the automation of procurement processes, supplier selection, optimization of inventory management and demand forecasting among other benefits. However, the use of Generative AI in procurement processes brings forth several ethical issues including transparency, algorithmic biases, data privacy and security, accountability and displacement of jobs. This study focused on investigating the opportunities and ethical dilemmas posed using Generative AI technology in supply chain optimization, particularly procurement process. The research employed a qualitative approach through the content analysis of academic journals. The secondary data used in the study includes journal articles, conference papers, industrial reports, and policy documents. It is found out that Generative AI technology is highly efficient in improving procurement through intelligent supplier assessment, contract creation, predictive analysis, demand forecasting, inventory optimization, and real-time decision-making processes. On the other hand, the findings suggest that poor governance frameworks, low data quality, algorithm discrimination, lack of transparency, cyber-security threats, and ethical issues associated with accountability can jeopardize the sustainable implementation of the technology. It can be concluded that the incorporation of Generative Artificial Intelligence in supply chain management has many advantages ranging from increased efficiency to better decision-making capabilities, forecasting accuracy, procurement activities, and increased resilience. Unfortunately, there are various challenges facing companies in Nigeria that limit the ability to incorporate generative artificial intelligence in supply chain management.