Integration of Artificial Intelligence in supply chain management: challenges and opportunities in Uganda

Natuhwera Pius 1 and Onyango Laban Oliver Owin 2, *

1Graduate School, Ndejje University, Uganda.
2 Department of Computing and Information Technology, Faculty of Science and Computing, Ndejje University, Uganda.
 
Review
World Journal of Advanced Engineering Technology and Sciences, 2024, 12(02), 009–012.
Article DOI: 10.30574/wjaets.2024.12.2.0253

 

Publication history: 
Received on 17 May 2024; revised on 26 June 2024; accepted on 28 June 2024
 
Abstract: 
Integrating Artificial Intelligence (AI) in supply chain management (SCM) signifies a significant advancement with profound implications for modern businesses, including those in Uganda. This research paper critically examines the challenges and opportunities associated with this integration, using Uganda as a case study. A comprehensive analysis of existing literature and specific insights from the Ugandan context identifies critical challenges such as data integration, technology adoption, and organizational readiness within the country. Additionally, it explores AI's diverse opportunities in optimizing supply chain processes for Ugandan businesses, including demand forecasting, inventory management, and logistics optimization within Uganda's unique operational landscape. Furthermore, the paper discusses the potential impact of AI integration on various stakeholders within Uganda's supply chain ecosystem, including suppliers, manufacturers, distributors, and customers. By synthesizing insights from academic research and industry practices in Uganda, this paper provides valuable insights for Ugandan businesses aiming to leverage AI technologies in their SCM strategies. Ultimately, this research contributes to a deeper understanding of the complexities of integrating AI in SCM within the Ugandan context and offers recommendations for addressing challenges while maximizing the opportunities presented by this transformative technology.
 
Keywords: 
Artificial Intelligence; Supply Chain; Management; Challenges; Opportunities
 
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