Ford Brings Back Veteran Engineers After AI Falls Short on Vehicle Quality
Ford has rehired around 350 experienced engineers after finding that AI-powered quality systems alone were insufficient to deliver the vehicle quality it sought.
SociapaHQ
Ford Motor Company has rehired hundreds of experienced engineers after concluding that artificial intelligence and automated quality systems alone were not sufficient to achieve the level of vehicle quality the automaker was targeting, according to reports.
In the past three years, the company has rehired about 350 veteran engineers, including former Ford employees and specialists working for supplier companies.
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AI Reality:
Kumar Galhotra, Ford’s chief operating officer, said of the carmaker’s growing reliance on automated quality systems: “The results are not what we expected.” Engineers are now back in the loop to help pinpoint potential failure points before parts go into production, allowing defects to be fixed much earlier in the manufacturing process.
“We have put too much trust in artificial intelligence in product development,” Charles Poon, Ford’s vice president of vehicle hardware engineering, said.
"Mistakenly we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that that would produce a high-quality product," Poon told reporters.
He said AI is still an important engineering tool but its effectiveness depends heavily on the quality of the data used to train it. Ford, he added, had not done a good job capturing and transferring the knowledge of many of its senior engineers before they left the company.
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Human Expertise:
The returning engineers, referred to as “gray beard” engineers internally, are mentoring younger employees and also helping to improve Ford’s AI systems by embedding decades of engineering knowledge into model training.
“Their expertise is a huge driver of our quality strategy,” said Galhotra. “They lead mandatory quality reviews and help us move from fixing things after production to preventing things before production.”
Ford has also increased collaboration across its software, manufacturing and supply chain teams to surface potential issues earlier in the product development cycle. The automaker also has set up a 40-person software quality assurance team to improve the reliability of the software before vehicles are delivered to customers.
Despite increasing its reliance on experienced engineers, Ford said it remains committed to artificial intelligence. The company has deployed more than 100,000 AI-powered validation tests to detect edge cases and rapidly verify software whenever engineering changes are introduced late in the development process.
