When Hurricane Helene barreled through North Carolina in September 2024, General Motors’ artificial intelligence system had already predicted that one of its key suppliers, Auria Solutions, would take a direct hit.
The automotive acoustics and textiles company manufactures carpets for General Motors’ full-size SUVs — like the Chevy Tahoe and Suburban, GMC Yukon, and Cadillac Escalade — at its plant in North Carolina.
When the storm pummeled the town, the factory lost water and power, but General Motors was prepared for the production-halting damage.
“After the hurricane, they didn’t have any water, and they cut carpet with a water jet,” General Motors spokesperson Kevin Kelly told Business Insider. “So we went in with our teams and helped them with drilling a well.”
Auria’s water well exemplifies why General Motors has spent the last four years developing AI tools to alert workers of potential supply chain network problems. According to Sean Gaskin, General Motors’ director of systems engineering and one of the AI program’s architects, the technology has prevented at least 75 factory stoppages this year alone.
The pandemic inspired GM’s high-tech solution
From 2020 through 2023, multiple automakers had to temporarily shut down their US production plants due to semiconductor chip shortages. The electrical parts, found in everything from modern dashboards to powered driver’s seats, experienced significant delays because of pandemic-era factory lockdowns.
In 2021, the shortage forced General Motors to cut production at eight facilities; The company had to halt US truck production again in 2022.
Jeff Morrison, General Motors’ senior vice president of global purchasing and supply chain, said the shortages forced the company to rethink how it monitored suppliers.
“Our supply chain is very critical for the business. It’s complicated,” Morrison told Business Insider. “What we found is that data management and analytics are the unlock to improving performance, efficiency, and creating value. AI for us has been a transformative tool.”
Morrison said that since the pandemic, General Motors has had to increase tenfold the number of suppliers it monitors to stay on track with production. The company turned to AI to map out tier-one parts suppliers, then extended the web further, scraping for data on its suppliers’ suppliers — called second, third, and up to “tier N” companies.
This AI-powered tool — which combines predictive modeling and real-time data insights — has helped the automaker avoid stoppages during major global events, like China’s throttling of rare earth magnets, and factory-level events, like a material provider missing a production deadline.
Nic Antaya for BI
How AI-powered news scanning and data mapping boost General Motors’ supply chain efficiency
General Motors’ system is four-pronged.
First, the company’s engineers built a digitized supply map and a coordinating machine-learning tool that constantly tracks relationships between tier-one suppliers and their sub-tier partners.
Second, a centralized communication hub, monitored by risk analysts in Michigan, activates when the system identifies a disruption. It’s triggered thousands of investigations.
Third, Risk Intelligence, General Motors’ AI article scanner, reads and classifies thousands of daily news articles for potential impact on the company’s supply chain. Finally, a dashboard tracks over supplier sites for signs of trouble such as shipping delays, overdue parts, or missed schedules.
Gaskin said these tools catch risks at a scale humans cannot manage.
“We started asking ourselves, ‘How would a human actually work through that supply chain in a way that they can find those needles in a haystack to prevent a disruption?'” Gaskin told Business Insider. “You really quickly get to a point where you realize that a human can’t do that effectively. They need to have assistance.”
AI’s abilities can benefit General Motors’ suppliers — and its future talent
Gaskin said the technology helps maintain a steady product flow to dealerships while giving General Motors opportunities to get days or a week ahead of unexpected supply chain snags.
General Motors’ AI system also helps suppliers, Gaskin said. The company has identified storm risks or concentration risks before suppliers noticed them, giving partners a chance to act quickly.
“We can actually go to our suppliers and say, ‘We’re seeing something that you should be worried about.’ Sometimes, they don’t even know,” Gaskin added. “It’s a win-win. The more they run, the more we’re running, and everyone is profitable on the chain.”
According to Gaskin, the system won’t replace human workers. Instead, it helps data-center employees identify risks, which can help suppliers produce parts, keep General Motors production on factory floors, and help the company profit. It can also help to attract talent, Gaskin said.
“These are assistants at best,” Gaskin said. “GM wants to be a top destination as an employer. If you’re not on the leading edge here, you’re not going to attract the best talent.”
If anything, the AI systems ensure that processes along General Motors’ supply chain keep humming so that factory workers can continue to assemble vehicles with readily available components.
Still, General Motors is facing several challenges in the automotive supply chain market. Its supply chain is global, making the automaker susceptible to tariffs. In a recent press release, CEO Mary Barra said that the company expects to pay between $4 billion and $5 billion in tariffs by the end of 2025.
However, if General Motors is going to adjust its supplier bases to avoid the levies, it already has the tech infrastructure to map out where it should source parts from.
“What we’ve been able to do is really unlock quite a bit of efficiency,” Morrison said. “We think we’re on the cutting edge of how to manage a supply chain.”
