TL;DR
Ford rehired 350 engineers after AI failed to replicate veteran expertise, then hit No 1 in JD Power quality for the first time in 16 years.
The automaker's VP of hardware engineering says Ford mistakenly believed AI could replace experienced workers, a blunder it fixed just in time to top JD Power's quality ranking for the first time in 16 years
Ford rehired 350 engineers after AI failed to replicate veteran expertise, then hit No 1 in JD Power quality for the first time in 16 years.
Ford has admitted that it had to rehire experienced engineers after its AI systems failed to deliver the quality the company expected. Charles Poon, Ford’s VP of vehicle hardware engineering, told reporters that the automaker mistakenly believed it could swap in AI and still produce a high-quality product. The admission, first reported by The Verge, comes as Ford earned the top spot among mainstream brands in JD Power’s initial quality ranking for the first time in 16 years.
The problem was not that the AI was fundamentally broken, Poon explained, but that experienced workers left before they could transfer their institutional knowledge into the systems meant to replace them. Without decades of engineering judgment encoded in the training data, Ford’s automated tools amplified weak inputs rather than catching design flaws. The company rehired, newly hired, or promoted 350 experienced engineers to fill the gap.
Poon was vague about why those workers left, but the broader picture is not. Ford has shed roughly 5,300 salaried positions since its 2020 employment peak, part of a wider contraction across Detroit’s automakers that has eliminated more than 20,000 white-collar jobs. CEO Jim Farley has said publicly that AI “is going to replace literally half of all white-collar workers in the US,” a prediction his own company’s quality crisis now complicates.
The 350 returning engineers were tasked with mentoring junior staff, rebuilding the data pipelines that feed Ford’s AI training, and refining the automated systems they were originally supposed to be replaced by. Ford also created a dedicated 40-person software quality assurance team and added more than 100,000 AI-powered automated tests to catch edge cases and revalidate software changes late in development.
The turnaround was enough to push Ford to the top of JD Power’s 2026 initial quality study, which measures problems reported by owners in the first 90 days of ownership. Ford scored 152 problems per 100 vehicles, ahead of Nissan and Buick. The F-150, Mustang, and Super Duty each won best in segment for the second consecutive year.
The quality win does not erase a rougher track record. Ford has led US automakers in recalls this year, issuing 51 so far in 2026 covering more than 11 million vehicles, more than double the next-closest manufacturer. It also joins a growing list of companies discovering that removing human judgment from AI-driven workflows creates problems the technology cannot fix on its own.
The episode lands at a moment when AI companies and policymakers are scrambling to figure out what the transition means for workers. OpenAI, Anthropic, Amazon, and Microsoft this week backed RAISE US, a $500 million nonprofit led by former commerce secretary Gina Raimondo to retrain American workers for the AI economy. Ford’s experience suggests the harder problem is not retraining but knowing which workers you cannot afford to lose in the first place.
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