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Harnessing technology for supply chain management at FIU Business

How procurement strategies can be streamlined by AI

One of the more popular misconceptions about supply chain management is that it exclusively focuses on the stage when goods move toward their final destination in trucks over the road.

Dr. Andrea Patrucco and his colleagues at Florida International University College of Business (FIU Business) regularly dispel such misconceptions among new students. In fact, there is a wide range of disciplines that fall under the umbrella of supply chain management: distribution and warehousing operations, demand forecasting and procurement, to name a few. 

Patrucco offers his expertise in procurement strategies to students as part of FIU Business’s holistic approach to the field. The most effective strategies, he found, are those that emphasize the human relationship between buyers and suppliers.

But an organic approach to the industry does not preclude the adoption of novel technology. Far from it: Students at FIU Business are trained in the use of data analytics and blockchain technology as tools to develop more efficient procurement strategies for their clients, which can inhabit the public and private sectors alike.

Exposure to such new technologies can cause worry among students that advances in artificial intelligence could make their future positions obsolete. While Patrucco admits that AI will have a growing impact on the field in years to come, he stresses that it cannot function as a wholesale replacement for human capital.

“Companies need to consider the social and ethical challenges connected to the use of AI,” Patrucco argues. “For example, when the black box of an AI system grows in complexity, it makes it difficult to understand how and why certain decisions are made by the technology.”

This potential for confusion could lead to an entirely new role within the industry, one that oversees and ensures AI compliance with ethical standards. 

Ultimately, Patrucco contends that developing technologies — be they AI or something not yet on the horizon — are to be used as tools to support the decision-making processes of human employees. But in order to benefit from these tools effectively, they must first be understood.

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