When Hurricane Helene struck North Carolina in September 2024, General Motors’ artificial intelligence system had already flagged a major risk: one of its key suppliers, Auria Solutions, was in the storm’s path. Auria produces carpets for GM’s full-size SUVs, including the Chevy Tahoe, GMC Yukon, and Cadillac Escalade, at a plant in the state. When the hurricane knocked out power and water, GM was ready. The company sent teams to help drill a well so production could resume quickly. This proactive response highlights a four-year investment by GM in AI-driven supply chain resilience. According to Sean Gaskin, GM’s director of systems engineering and a lead architect of the AI program, the system has prevented at least 75 factory stoppages this year alone. The push for AI began during the pandemic, when semiconductor shortages forced GM to halt production at eight U.S. facilities in 2021 and again in 2022. These disruptions exposed the fragility of complex, global supply chains. Jeff Morrison, GM’s senior vice president of global purchasing and supply chain, said the experience led the company to overhaul how it monitors suppliers. “Supply chain is critical, and it’s complicated,” Morrison said. “Data management and analytics are the key to improving performance, efficiency, and value. AI has been transformative.” Since then, GM has expanded its supplier monitoring by tenfold. Using AI, the company maps not just tier-one suppliers but also their sub-tier partners—up to tier N—creating a detailed digital supply network. This network combines predictive modeling with real-time data to detect risks early. The system operates on four core components. First, a machine-learning tool continuously tracks supplier relationships and dependencies. Second, a centralized communications hub in Warren, Michigan, activates when a risk is detected, triggering thousands of investigations. Third, Risk Intelligence, an AI-powered news scanner, analyzes thousands of articles daily to identify potential supply chain threats. Finally, a real-time dashboard monitors supplier sites for signs of trouble—shipping delays, overdue parts, missed deadlines. Gaskin said the scale of data involved makes human oversight impossible. “How would a human find the needle in a haystack to prevent a disruption?” he asked. “They can’t. They need help.” The AI doesn’t just protect GM—it helps suppliers too. By spotting risks like storms or over-concentration in a single region before suppliers do, GM can alert them early, enabling faster action. “We can say, ‘You should be worried about this,’ and sometimes they don’t even know,” Gaskin said. “It’s a win-win. The more they run, the more we run, and everyone profits.” The technology doesn’t replace workers; it empowers them. Data analysts use AI insights to prioritize risks and coordinate responses, keeping production lines running smoothly. Beyond operations, GM sees AI as a talent magnet. “We want to be a top employer,” Gaskin said. “If you’re not on the leading edge, you won’t attract the best people.” Despite challenges—like expected tariffs of $4 to $5 billion by the end of 2025—GM’s AI infrastructure gives it the tools to adapt. The company can quickly identify alternative suppliers and reconfigure sourcing strategies. “We’ve unlocked significant efficiency,” Morrison said. “We believe we’re at the cutting edge of supply chain management.”