Ford rehires 350 veteran engineers after AI falls short on quality

Ford discovered that artificial intelligence could not replace decades of engineering judgment, forcing the automaker to rehire 350 experienced specialists to fix its quality systems.

Ford's bet that artificial intelligence could replace veteran engineering expertise backfired, leading the automaker to rehire 350 experienced technical specialists after automated quality systems failed to catch defects. The company had mistakenly believed that AI alone could produce a high-quality product by ingesting design requirements, executives said.

"Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product," Charles Poon, Ford's vice president of vehicle hardware engineering, told reporters.

The 350 engineers — some former employees, others hired from suppliers — now mentor younger staff, lead design reviews and retrain the AI tools that were supposed to replace them. Ford has more than doubled its technical specialist population since launching its quality reset in 2023, Chief Operating Officer Kumar Galhotra said. The specialists "hunt for failure points before a part ever reaches the plant floor," he added.

The admission comes as Ford celebrates its best-ever JD Power initial quality ranking — No. 1 among mainstream brands, with 152 problems per 100 vehicles — but still leads US automakers in recalls with 51 issued so far in 2026. The episode offers a cautionary data point for companies rushing to replace human expertise with AI, as Ford expects the rehiring to contribute to $1 billion in cost reductions this year.

The Knowledge Gap Ford Created

Ford had shed roughly 5,300 salaried positions since its 2020 employment peak, part of a broader contraction across Detroit's automakers that eliminated more than 20,000 white-collar jobs. Chief Executive Jim Farley has said publicly that AI "is going to replace literally half of all white-collar workers in the US," a prediction the quality crisis now complicates.

Poon said Ford had not done enough in prior years to preserve the knowledge of its most experienced engineers, some of whom left before their expertise was fully integrated into the company's systems. Quality problems often showed up at the boundaries between teams, where design, manufacturing, software and hardware collide, he said.

Quality Win, Recall Hangover

The JD Power study 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.

Yet the quality win does not erase a rougher track record. Ford issued 152 recalls in 2025, nearly doubling the previous record set by General Motors in 2014 with 77 safety bulletins. As of this week, Ford had issued 51 recalls in 2026 covering more than 11 million vehicles, more than double Chrysler's 19. Ford executives said many of the continued recall issues are tied to vehicles designed between 2013 and 2020, calling recalls a "lagging indicator."

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 company previously developed two bespoke AI-enhanced scanning tools — AiTriz and MAIVs — that debuted in 2024 to validate assembly quality before vehicles leave the factory.

For investors, the episode raises questions about the timeline and cost of AI-driven automation in manufacturing. Ford shares trade at roughly 7 times forward earnings, a discount to the broader market, as the market prices in ongoing quality and transition costs. The $1 billion in expected savings from the quality overhaul suggests the payoff is real but required a human investment that Ford initially tried to skip.

This article is for informational purposes only and does not constitute investment advice.