Industry context: For AI and data practitioners, Ford's reversal highlights a recurrent implementation risk: automated QA tools underperform when institutional knowledge and training data are incomplete. Bloomberg reports Ford hired 350 veteran engineers, many former employees or supplier specialists, to find defects before parts reach production. Kumar Galhotra told journalists, "We had been relying more and more on automated quality systems," and said the rehired specialists "hunt for failure points before a part ever reaches the plant floor," according to TechCrunch. 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," as reported by Business Insider and The Verge. JD Power named Ford the top mass-market brand in its 2026 initial quality study, per coverage in The Next Web and The Verge.
Ford rehires ‘gray beard’ engineers after AI falls short