Ford has rehired, hired or promoted about 350 experienced engineers after company executives concluded that artificial intelligence and automated quality systems alone were not delivering the results the automaker wanted. Charles Poon, Ford’s vice president of vehicle hardware engineering, said the company had wrongly assumed that feeding design requirements into AI systems would be enough to produce a high-quality vehicle. Instead, Ford said it needed to restore veteran technical expertise to identify problems earlier and improve the tools meant to catch defects before vehicles reached customers.
Ford said the issue was not that AI itself was unusable, but that key institutional knowledge had not been fully transferred before experienced employees left. Poon said the company had failed to preserve enough of that expertise in its systems, particularly in areas where design, manufacturing, hardware and software overlap. Kumar Galhotra, Ford’s chief operating officer, said the returning specialists now help lead design reviews and look for failure points before parts reach assembly lines. Ford has also created a 40-person software quality assurance team and added more than 100,000 AI-driven automated tests aimed at catching edge cases and validating software changes later in development.
The company is presenting the move as part of a broader quality turnaround. Ford ranked first among mainstream brands in JD Power’s 2026 Initial Quality Study, scoring 152 problems per 100 vehicles and finishing ahead of Nissan and Buick. The F-150, Mustang and Super Duty each won best in segment for a second straight year. Ford also says the shift toward combining automation with experienced engineering judgment could reduce costs by $1 billion this year through lower repair and warranty expenses.
At the same time, questions remain about whether the improvement marks a full resolution of Ford’s quality problems. Critics note that the JD Power study measures issues reported in the first 90 days of ownership, making it an early indicator rather than a measure of long-term durability. Ford has also continued to lead U.S. automakers in recalls, issuing 51 so far in 2026 covering more than 11 million vehicles. Executives argue many of those recalls stem from vehicles and platforms designed between 2013 and 2020, describing recalls as a lagging indicator, while pointing to internal data and newer products as signs that the company’s revised approach is beginning to take hold.
The episode has also become part of a wider debate over how far companies can rely on AI to replace human expertise. Ford has reduced its salaried workforce by roughly 5,300 positions since its 2020 peak, amid a broader contraction across Detroit automakers. That backdrop has drawn added attention to earlier predictions by CEO Jim Farley that AI could replace a large share of white-collar jobs. Ford is not abandoning AI, executives say, but recalibrating its role so that veteran engineers can train younger staff, rebuild training data pipelines and refine the automated systems that had previously been expected to take on a larger share of the work.