The fear that AI will take jobs from human workers has existed virtually since the dawn of technology, and practical examples of this phenomenon have been seen in recent years (while at the same time there is evidence of short-term increases in blue-collar employment in some sectors due to AI). However, AI is not the only factor driving layoffs, and the results of replacing human intelligence with a machine substitute are not always what employers expect.
It’s a bitter lesson Ford learned recently when it attempted to replace a number of its human engineers with AI, according to a Bloomberg report. The US automaker found that replacing human quality inspectors with an AI alternative led to an inferior product, which Bloomberg reported was costing it billions. The economic downturn led Ford to reverse course and hire 350 experienced quality inspectors, many of whom had previously worked at the company, in an effort to retain legacy institutional knowledge that had been lost in the move to AI.
The rush for profit at the expense of quality
Charles-McClintock Wilson/Shutterstock
Ford announced a broad shift to AI during a third-quarter 2025 earnings conference call, saying it had already begun “systematically deploying AI across the entire industrial system,” including 900 AI-powered cameras to help detect quality issues early in the manufacturing process. The rush to adopt trendy technology without proper preparation, however, has led to significant quality problems. “Mistakenly, we thought that by simply introducing artificial intelligence and incorporating the design requirements that we had, it would produce a high-quality product,” Charles Poon, vice president of automotive hardware engineering at Ford, said on a call with reporters.
Poon acknowledged, however, that without being trained by people with the appropriate experience, AI tools were seriously flawed. While Ford decided to solve the problem by hiring human staff (and this decision appears to have been effective, with the company ranking among the largest mass-market brands in JD Power’s 2026 U.S. Initial Quality Study), the language around this decision is somewhat concerning. It appears that human labor is primarily employed to train AI systems.
“We recognized that to improve some of our automation, machine learning and artificial intelligence tools, we needed to make sure they were trained by the most experienced people,” Poon said. What’s unclear is what will happen to the corps of rehired engineers when AI systems absorb their expertise.
