Why Ford is Betting on Veteran Engineers in the Age of AI
As artificial intelligence transforms workplaces across industries, many companies are racing to automate tasks, streamline operations and reduce costs. But at Ford Motor Company, the future of manufacturing isn’t being built by algorithms alone.
Instead, the automaker has made an unexpected investment: experience.
Over the past three years, Ford has recruited more than 350 veteran engineers – internally nicknamed “gray beards” – to mentor younger employees, strengthen product design and even retrain the company’s AI systems. The strategy reflects a growing belief that while AI can dramatically improve productivity, it performs best when guided by decades of human expertise.
Experience Is Becoming a Competitive Advantage
For years, Ford focused heavily on technological innovation. But executives now acknowledge that institutional knowledge – the lessons accumulated over multiple vehicle development cycles – wasn’t being fully utilised.
Charles Poon, Ford’s Vice President of Vehicle Hardware Engineering, believes the company underestimated the value of its most experienced engineers.
“Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it.”
Reflecting on previous years, he added:
“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.”
Rather than replacing seasoned professionals with AI, Ford is pairing the two together.
The veteran engineers now mentor junior staff while acting as internal quality auditors, conducting mandatory weekly design reviews to identify weaknesses before new vehicle components ever reach the production line.
According to Ford:
“These engineers carry the hard-earned wisdom of decades of design.”
AI Still Needs Human Judgment
Ford’s renewed emphasis on people doesn’t diminish the company’s investment in artificial intelligence.
Instead, the manufacturer sees AI as a powerful assistant rather than a replacement.
One example is its AI-powered vision inspection system deployed across assembly plants worldwide. Using ordinary smartphones fitted with advanced computer vision software, the technology inspects components such as hose connections and electrical systems with remarkable consistency.
When defects are detected, the system immediately alerts workers so corrections can be made before vehicles move further down the production line.
Ford says the technology now operates across 33 manufacturing plants worldwide, where more than 1,000 cameras conduct millions of quality inspections.
The company describes the combination of AI and human expertise as:
“Powerful.”
A Costly Wake-Up Call
Ford’s renewed focus on quality follows one of the most difficult periods in its recent history.
By mid-2024, vehicle recalls were costing the company approximately $4.8 billion annually.
Last year alone, Ford issued a record 90 recalls—the highest number ever recorded by a single automaker in one year—including a recall affecting nearly 700,000 crossover vehicles that resulted in an estimated $570 million financial charge.
The mounting costs prompted a company-wide rethink of quality assurance.
That transformation is already showing results.
In the latest J.D. Power Initial Quality Survey, Ford climbed from tenth place to become the highest-ranked mainstream automotive brand.
Executives attribute the improvement not simply to technology, but to a broader cultural shift centred on craftsmanship and accountability.
Attention to Detail Over Automation
Ford CEO Jim Farley believes technology alone cannot build great vehicles.
“We have AI tools for vision systems,” he said.
“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.”
He added:
“It’s just an incredible attention to every single detail.”
The message is clear: AI may identify problems faster, but people still solve them.
The Broader AI Challenge
Ford’s approach mirrors a growing trend across corporate America.
While companies have enthusiastically embraced generative AI, many continue struggling to generate measurable returns from their investments.
Several industry studies have suggested that widespread AI adoption has not automatically translated into meaningful business value. Experts increasingly argue that organisations succeed with AI only when they have clear implementation strategies and experienced employees capable of directing the technology effectively.
Even technology leaders have acknowledged AI’s limitations.
Bryan Catanzaro, Vice President of Applied Deep Learning at NVIDIA, has previously noted that deploying AI often remains more expensive than relying solely on human labour, reinforcing the importance of skilled professionals in AI-driven workplaces.
Human Expertise Still Comes First
Ford believes successful automation begins with hiring the right people.
A company spokesperson explained:
“AI is a powerful tool for catching potential quality issues but it’s only as good as the people using it.”
The spokesperson continued:
“That’s why we have hired more than 350 experienced tech specialists to work alongside newer team members.”
According to Ford:
“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.”
Beyond Engineers: A Workforce Challenge
Jim Farley has repeatedly argued that America’s manufacturing sector faces a much deeper challenge than technology.
He believes the country suffers from a shortage of skilled workers, particularly in essential industries such as manufacturing, construction and automotive repair.
Speaking previously, Farley said:
“On the surface, this looks like a people problem, and most are.”
“But it’s actually not that simple. It’s an awareness problem. It’s a societal problem.”
He has consistently called for greater investment in vocational education, apprenticeships and skilled trades, warning that labour shortages threaten both industrial growth and the expansion of AI infrastructure.
As he put it:
“If we are successful – when we are successful – we’ll take on bigger, higher-class problems.”
“For now,” he added, “the problems we’re trying to solve are pretty practical: I need 6,000 technicians in my dealerships on Monday morning.”
Automation Still Raises Concerns
Not everyone shares Ford’s optimism.
Labour unions continue to question how productivity gains from automation will be distributed.
Earlier this month, United Auto Workers President Shawn Fain warned that workers deserve to benefit financially from AI-driven efficiency improvements.
“We need to be clear about this: We are in a fight for humanity.”
He continued:
“The fruits of our labor have multiplied like never before, but workers aren’t reaping the harvest.”
Fain argued that if automation simply increases corporate profits without improving workers’ livelihoods, then its implementation must be reconsidered.
“It doesn’t have to be this way; in a just society, when workers create more value, they see more of the benefit.”
Rebuilding Quality From the Ground Up
Ford’s Chief Operating Officer, Kumar Galhotra, says the veteran engineers have fundamentally changed how the company develops vehicles.
According to him, they now:
“Hunt for failure points before a part ever reaches the plant floor.”
These specialists also retrain AI systems, conduct mandatory quality meetings and address design flaws before manufacturing begins.
Although Ford still expects more than $1 billion in warranty and materials-related costs this year, Galhotra believes those figures represent problems rooted in older vehicle programmes rather than current production.
“Because we’re doing more to prevent issues upfront, we believe these recall numbers are going to steadily come down with the newer vehicles.”
“I can’t give you a very specific date on when the number will turn,” he added.
Farley says the financial benefits are already becoming visible.
“We’re seeing our warranty coverages come down. We’re seeing our recall costs come down.”
Those improvements, he said, are generating:
“Literally hundreds and hundreds of millions of dollars of a tailwind for Ford on cost.”
The Future May Belong to Humans and AI Together
Ford’s recent transformation offers an important lesson at a time when artificial intelligence dominates conversations about the future of work.
Rather than replacing experienced employees, the company has concluded that decades of human judgment remain indispensable—even for training machines.
Its investment in veteran engineers suggests that the organisations likely to benefit most from AI may not be those that eliminate human expertise, but those that use it to make intelligent technology significantly smarter.
