GM Uses AI to Spot Supply Chain Risks Before They Halt Production

General Motors (https://www.gm.com) uses artificial intelligence to monitor risks across its supplier network, a system the automaker says has helped prevent at least 75 factory stoppages in a single year. The tools combine supplier mapping, news analysis and operational alerts to give teams more time to respond to disruptions.

The system’s value became clear after Hurricane Helene struck North Carolina in September 2024. Auria Solutions (https://www.auriasolutions.com/), which makes carpet for GM’s full-size SUVs at a North Carolina plant, lost water and power. Because GM had identified the supplier as being in the storm’s path, its teams were prepared to help. The company helped Auria drill a well so it could resume cutting carpet with water jets, GM spokesperson Kevin Kelly told Business Insider (https://www.businessinsider.com).

GM developed the system after pandemic-era semiconductor shortages forced production cuts at several facilities. In 2021, the company reduced output at eight plants, and US truck production was halted again in 2022. The disruptions exposed how quickly problems at distant suppliers could affect vehicle assembly.

GM’s supplier monitoring now extends beyond direct, or tier-one, suppliers to their own suppliers and further down the chain. Senior vice president of global purchasing and supply chain Jeff Morrison told Business Insider that the number of suppliers the company monitors has increased tenfold since the pandemic. The goal is to identify vulnerabilities that may be invisible when companies track only their immediate vendors.

The program has four components. GM maintains a digitized map of supplier relationships, supported by machine-learning tools that track links between suppliers and their sub-tier partners. A centralized communications hub routes identified risks to analysts in Michigan, while a separate system scans and classifies thousands of news articles daily for potential supply chain impacts. A dashboard also monitors supplier sites for signs such as shipping delays, overdue parts and missed schedules.

According to Sean Gaskin, GM’s director of systems engineering and one of the program’s architects, the tools have helped the company respond to risks ranging from China’s restrictions on rare earth magnets to suppliers missing production deadlines. The system can also flag weather threats or concentration risks before a supplier recognizes them, giving both companies time to consider alternatives or take protective action.

The approach illustrates a practical use of AI in operations: processing large, changing datasets to direct human attention, rather than making decisions independently. GM says analysts investigate alerts and work with suppliers to address problems. Gaskin described the systems as assistants, not replacements for employees.

The model does not remove the underlying exposure. GM remains vulnerable to global disruptions and trade policy; CEO Mary Barra (https://en.wikipedia.org/wiki/Mary_Barra) said the company expected to pay $4 billion to $5 billion in tariffs by the end of 2025. Supplier mapping could help the automaker assess sourcing options, but the source material does not establish that the tools eliminate tariff costs or supply risks. Their immediate test is whether earlier warnings can consistently give people enough time to keep production moving.

Cited: https://www.businessinsider.com/how-gm-uses-ai-predict-prevent-costly-supply-chain-disruptions-2025-9

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