Ford’s bet on AI over experienced engineers cost the company three years, billions of dollars, and a quality crisis that only ended when it started hiring veterans back.
The automaker brought back 350 veteran engineers to correct errors made by its automated design and quality systems, Bloomberg reported. Ford calls them “gray beard” engineers. The result: Ford topped JD Power’s mainstream quality ranking for the first time in 16 years.
Ford’s AI Systems Failed Because Experienced Engineers Left First
The failure was not the technology itself. Charles Poon, Ford’s VP of vehicle hardware engineering, told reporters: “Mistakenly, we thought that by just introducing artificial intelligence and adjusting the design requirements that we had, that that would produce a high-quality product,” per The Next Web’s Ford AI report.
Experienced engineers left before their knowledge could be encoded into Ford’s AI systems. Without that foundation, the automated tools amplified weak inputs rather than catching design flaws. “Artificial intelligence is a fantastic tool,” Poon told Bloomberg, “but it’s only as good as the information you use to train it.”
Ford shed 5,300 salaried positions since its 2020 employment peak. Detroit’s three automakers collectively eliminated 20,000 white-collar jobs over the same period. CEO Jim Farley previously said AI will displace white-collar workers at massive scale, per Fortune. Ford’s own quality crisis now complicates that forecast, even if only partially.
Ford Hired Veterans Back To Retrain AI And Mentor Juniors
COO Kumar Galhotra said Ford had been over-relying on automated quality systems without getting results, per Bloomberg. The returning engineers rebuilt the data pipelines feeding Ford’s AI training, mentored junior staff, and reprogrammed the automated systems they had originally been brought in to replace.
Ford also created a software quality assurance team of 40 engineers and added more than 100,000 AI-powered automated tests, per The Next Web. “We brought back technical specialists,” Galhotra said. “They hunt for failure points before a part ever reaches the plant floor.”
CEO Jim Farley credited the effort with generating “hundreds and hundreds of millions of dollars of a tailwind for Ford on cost” through reduced warranty and recall expenses.
Klarna And IBM Made Similar AI Hiring Decisions
Ford is not alone. Klarna replaced 700 customer agents with an OpenAI-powered assistant between 2022 and 2024, per Bloomberg. Quality dropped. By mid-2025, the company was hiring human agents back. “We focused too much on cost,” CEO Sebastian Siemiatkowski told Bloomberg. “The result was lower quality.”
IBM announced earlier this year it would triple U.S. entry-level hiring across roles widely forecast as AI-replaceable. IBM, Klarna, and Ford each arrived at the same correction through different industries and different timelines.
AI-Literate Workers Are Necessary In AI Era
Ford’s recovery required rehiring workers it had already let go, after measurable quality damage and reputational cost. UC Santa Barbara professor Matt Beane has described this risk plainly: “Cleanup is always harder than prevention.”
The 350 engineers Ford hired back are not evidence that AI fails. They are evidence that AI requires experienced humans to function well. The most expensive AI failure is not a bad output. It is the moment a company realizes it no longer has anyone left who can tell the AI it is wrong.
