Ford Motor Company has rehired more than 300 experienced engineers after finding that its artificial intelligence (AI)-based quality control systems were unable to identify certain design and manufacturing issues without human expertise.
The automaker had expanded the use of AI to detect defects during vehicle design and production. However, the company found that some critical quality concerns were overlooked by automated systems and required the judgment of experienced engineers.
According to Charles Poon, Vice President of Vehicle Hardware Engineering at Ford, the company initially expected AI to deliver high-quality outcomes by relying primarily on existing engineering requirements. He said Ford later recognized that AI systems are only as effective as the data and expertise used to train them.
As part of the new approach, the returning senior engineers are no longer assigned to routine production activities. Instead, they conduct independent design reviews, evaluate potential failure points, and help train AI models using their engineering knowledge and practical experience.
Ford said the revised strategy has contributed to improvements in vehicle quality. The company ranked highest among mainstream automotive brands in the 2026 J.D. Power U.S. Initial Quality Study, its strongest performance in 16 years. Ford also reported a reduction in warranty and recall costs, which it expects will result in significant long-term savings.
Despite increasing human oversight, Ford plans to continue expanding the use of AI across its manufacturing operations. The company said it currently operates around 900 AI-powered cameras in its production facilities, with experienced engineers supervising AI training and quality validation.
The move reflects a broader industry trend in which manufacturers are combining artificial intelligence with human expertise rather than relying solely on automation for critical engineering and quality assurance tasks.
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