Artificial Intelligence (AI) is being hailed as the engine of a "new Industrial Revolution," with its practical impact profoundly felt in supply chain management. This sector, which became a topic of everyday concern during the COVID-19 pandemic due to global shortages and shipping failures, is once again center stage amidst current trade tensions. Mark Fagan, a public policy lecturer at Harvard, emphasizes that a supply chain is a complex network of "nodes" (factories, warehouses) and "links" (transportation and information flows), encompassing not just materials but also labor, equipment, and systems. A failure at any one point can bring the entire operation down.

Fagan uses the family tree analogy to illustrate the fragility of these systems: just as most people only know their immediate relatives, companies usually only understand their direct suppliers. Weaknesses often originate with remote, forgotten subcontractors or overburdened transit hubs—actors far removed from the core operation. The paradox is that as systems become more global and interconnected, these crucial points of potential collapse become harder to notice, demanding more rigorous information management.

This challenge is addressed by AI, which radically reshapes how supply chains are built and managed. The core concept is "survival time"—the period an operation can continue after a failure. AI's transformative power lies in prediction, optimization, and system design, operating across four key domains:

Forecasting: AI can scan thousands of failure events to identify early disruption warnings, a feat impossible for human analysts at scale. For example, AI tools have been used to predict "missed care opportunities" (MCOs) in hospitals with over 95% accuracy, enabling preemptive outreach. This predictive capability directly translates to preventing supply chain delays before they compound.

Design and Management: By integrating real-time data, AI enhances traditional planning models (based on cost/time) to allow dynamic reconfiguration. Firms like UPS use AI for real-time, last-mile delivery decisions, rerouting drivers based on traffic or changing priorities.

Resilience and Agility: AI facilitates the creation of "digital twins," or virtual models of the supply chain, allowing organizations like the U.S. Department of Defense to simulate disruptions (natural disasters, adversarial threats) and test responses.

Workforce Optimization: AI is even optimizing the less visible parts of the chain—the deployment of people. Logistics giants use AI to identify internal candidates for open roles, creating a more flexible and capable workforce.

Ultimately, Fagan concludes that AI will enhance the quality, timeliness, and cost of analysis, making supply chain management, which is "critical to economic prosperity," much more robust and responsive.