Ford is bringing experienced engineers—including former employees—back into the company after finding that its artificial intelligence and automated quality-control systems did not deliver the results it had hoped for. The automaker says the return of human expertise is already producing positive outcomes, helping it secure the top position among mainstream brands in the latest JD Power Initial Quality Survey while also lowering costs.
According to a Bloomberg report, Ford has rehired about 350 veteran engineers over the last three years, including former staff and specialists from supplier firms, after discovering that its AI-driven and automated quality systems were unable to meet expectations.
Company executives acknowledged that Ford had become too dependent on automation and had underestimated the value of decades of engineering knowledge accumulated by employees who had worked on multiple generations of vehicles.
Charles Poon, Ford’s vice-president of vehicle hardware engineering, said the company had placed too much confidence in AI’s capabilities.
“We mistakenly believed that simply introducing artificial intelligence and feeding it design requirements would automatically result in a high-quality product,” Poon told Bloomberg. While describing AI as a powerful tool, he stressed that its effectiveness depends entirely on the quality of the information used to train it.
Poon noted that Ford had failed to adequately preserve the expertise of many seasoned engineers before they left the company. Consequently, the AI systems lacked the practical, real-world knowledge necessary to identify potential issues early in the vehicle development process.
To bridge that gap, Ford brought back more than 350 experienced engineers. Internally known as “gray beard” engineers, these veterans are now mentoring younger staff, helping improve AI training and identifying quality concerns before they reach the manufacturing stage.
Ford chief operating officer Kumar Galhotra said the company had increasingly depended on automated quality systems without achieving the desired outcomes. He described the returning engineers as central to Ford’s quality-improvement efforts, leading mandatory quality reviews and helping shift the company’s approach from fixing defects after they emerge to preventing them from occurring in the first place.
“We’re moving away from a find-and-fix approach toward preventing issues before they happen,” Galhotra said. “Instead of dwelling on problems, we need to focus on solving them.”
The company’s changes go beyond hardware engineering. Ford said its software, manufacturing and supply-chain teams now collaborate much more closely to identify problems earlier in the development process. It has also established a dedicated 40-member software quality assurance team to improve software reliability before vehicles are delivered to customers.
Ford Is Not Abandoning AI
Despite the renewed emphasis on human expertise, Ford says it is not moving away from artificial intelligence. Instead, the company is seeking to make its AI systems more effective by training them with better data and insights from experienced engineers.
Ford said it has introduced more than 100,000 AI-powered validation tests aimed at detecting edge cases and stress-testing vehicle software across a broad range of operating conditions.
