Does AI Eliminate the Need for Supply Chain Expertise?

Artificial intelligence has become a dominant topic of discussion throughout industry. The technology is on a path of rapid adoption and implementation, with many use cases reported in a broad array of industries. Which raises the following questions: Why do we still need to teach the fundamentals of supply chain management and analytics to students? And why do we need supply chain professionals with a deep understanding of the discipline? In other words, why can’t any bright professional with limited supply chain knowledge successfully use AI to guide his or her decision-making and management of supply chain functions?

The answer is that while generative and other forms of AI have demonstrated extraordinary capabilities and future promise, the technology represents just another tool that requires human supply chain understanding, experience and expertise. As with any major decision-support system (DSS), effective supply chain management requires individuals who can (1) intuitively understand and assess a supply chain problem or need, (2) determine the appropriate decision variables that must be considered to make a decision, (3) develop the appropriate decision-making input data that is required, and (4) evaluate the outputs of their management decision-support systems.

An important first step in evaluating the output of a DSS is to assess the validity and reasonableness of a recommended action or analytic solution. Such action requires that the evaluator has knowledge and understanding of supply chain management fundamentals, principles and practices.

This story was originally published by SupplyChainBrain. Read the full story at SupplyChainBrain →