Ford on why it hired 350 ‘gray beard’ engineers: you need their mentorship for younger workers — and to drive huge AI productivity gains

WIth all the discussion about the AI bubble, AI hype, and mass automation displacement, Ford Motor Company has a message for the U.S. economy: Human experience matters. 

Over the last three years, the company has hired 350 veteran engineers—dubbed “gray beards” internally and made up of both former Ford employees and workers from suppliers—to help train junior staff and reprogram ineffective artificial intelligence tools. It’s because the company realized what AI is and isn’t good for.

“Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it,” Charles Poon, Ford’s vice president of vehicle hardware engineering, told reporters last week. “Over prior years, we didn’t pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles.”

“These engineers carry the hard-earned wisdom of decades of design,” a Ford representative told Fortune, adding that they serve as “internal auditors,” running mandatory weekly peer design reviews to hunt for and eliminate potential failure points before blueprints ever reach the factory floor. At the same time, the company said AI is very important to quality gains, “and that, in tandem with deep technical expertise, is what’s needed.”

The combination is “powerful,” Ford said, noting the example of one of its AI vision systems, which uses off-the-shelf smartphones to look at things like hose connections and electrical connections on the assembly line. “The system acts like an extra set of highly precise eyes to perform quality checks with a high level of consistency. When it finds an issue, it alerts the operator so they can make a correction before the component moves down the assembly line.” Ford is using this vision system across 33 plants around the world, the company added, with more than 1,000 cameras performing millions of inspections.

By mid-2024, recalls were costing Ford $4.8 billion per year. Last July, the company notched the superlative as the automaker with the most recalls ever issued in a single year with 90, including an estimated $570 million charge for nearly 700,000 crossover vehicles.

Since then, the company has made a concerted effort to improve quality control and now ranks No. 1 among mainstream brands in the most recent JD Power Initial Quality Survey published on Thursday. Last year, Ford ranked 10th for quality. The company attributes increases in quality to a “culture change” emphasizing the role of human workers. 

“We have AI tools for vision systems,” Ford CEO Jim Farley told Bloomberg TV. “But most of all, it’s just old-fashioned hard work of our team members all working together to pay attention to the very small details that will make a difference between a perfectly built Ford and an okay-built Toyota. It’s just an incredible attention to every single detail.”

AI has increasingly shown it can increase productivity of certain activities, but is only making meaningful gains for companies if they are able to articulate a clear vision around how it should be deployed and augment the work of human employees. Moreover, tech executives like Bryan Catanzaro, Nvidia’s vice president of applied deep learning, has said the cost of AI still far exceeds that of human labor, suggesting that even as companies continue to deploy automation, the role of human workers to both guide that technology—and ensure its proliferation—are more important than ever. 

This has been a struggle across the Fortune 500 since the influential (and contested) MIT study in 2025 that only 5% of companies were seeing a meaningful return on investment from generative AI pilots. Other surveys have found similar splits between the rate of AI adoption and the meaningful results from it.

It’s a point Ford has been making for years: If you want automation to be successful, hire smart humans first.

“AI is a powerful tool for catching potential quality issues but it’s only as good as the people using it,” a Ford spokesperson told Fortune in a statement. “That’s why we have hired more than 350 experienced tech specialists to work alongside newer team members. By combining AI’s processing power and pattern recognition with decades of human engineering experience, we’re identifying potential issues and designing quality into our vehicles from day one while teaching the next generation to prevent problems before they ever start.”

Ford’s repeated calls for more human workers

Farley has long warned about the dearth of blue-collar workers creating a crisis in the “essential economy,” slowing down the build-out of key sectors such as the automotive industry, as well as the expansion of AI infrastructure. He previously said the country is short 600,000 factory workers and 500,000 construction workers right now, attributing the slimming labor force to a lack of awareness of a shortage.

“On the surface, this looks like a people problem, and most are,” Farley told Axios last year. “But it’s actually not that simple. It’s an awareness problem. It’s a societal problem.”

The CEO has advocated for policy changes to incentivize greater blue-collar job fulfillment, including greater investments in vocations training and apprenticeships, as well as pro-trade polities that grow the essential economy.

“If we are successful—when we are successful—we’ll take on bigger, higher-class problems,” he said. “Right now, the problems we’re trying to solve are pretty practical: I need 6,000 technicians in my dealerships on Monday morning.”

However, as Ford and the automotive industry blend automation and human workforce together, there may be other challenges ahead. Earlier this month, UAW, among the largest unions in North America representing autoworkers, expressed concern for the future of humans in the industry amid waves of automation. UAW president Shawn Fain argued at the union’s conference that workers should share in the financial gains automakers reap in automation-related productivity gains.

“We need to be clear about this: We are in a fight for humanity,” Fain said. “The fruits of our labor have multiplied like never before, but workers aren’t reaping the harvest. And if AI continues to be used as an accessory to that crime, it has to be stopped. It doesn’t have to be this way; in a just society, when workers create more value, they see more of the benefit.”

How Ford orchestrated its quality turnaround

According to Ford COO Kumar Galhotra, the veteran engineers responsible for its quality problem turnaround “hunt for failure points before a part ever reaches the plant floor,” he said at last week’s press meeting. Today, the technical specialists run mandatory meetings to address quality concerns, as well as reprogram AI tools to counter glitches before they occur. 

To be sure, Ford continues to encounter issues with recalls, expecting more than $1 billion in warranty and material costs this year. These costs are a lagging metric, according to Galhotra, and are expected to decrease over time. The company also hopes to save $1 billion in costs this year.

“Because we’re doing more to prevent issues upfront, we believe these recall numbers are going to steadily come down with the newer vehicles,” he said. “I can’t give you a very specific date on when the number will turn.”

Farley said Ford is already making up some of the money previously lost because of quality issues.

“We’re seeing our warranty coverages come down. We’re seeing our recall costs come down,” he said. “These are all contributing to literally hundreds and hundreds of millions of dollars of a tailwind for Ford on cost.”

[This report has been updated with additional context from a Ford representative.]

This story was originally featured on Fortune.com