Ford's Farley: AI Will Spare the Trades, Hit Office Jobs First

Ford CEO Jim Farley says the first wave of AI will eliminate finance, call-center and entry-level programming jobs while leaving blue-collar skilled trades largely intact — and even strengthened.

"I think most of these jobs will be both using AI and also protected from it," Farley said at a backstage media roundtable during Ford Pro Accelerate. But "if you work in finance doing spreadsheets, or you're in a call center, or you're an entry-level programmer—those jobs are definitely going to be changed and eliminated with at least this first inning of AI."

Farley spoke alongside Linda Hubbard, president and CEO of Carhartt, and Chris Nelson, CEO of Stanley Black & Decker. His argument was straightforward: AI will disrupt routine, screen-based, standardized knowledge work faster than it can replace electricians, technicians, mechanics and factory skilled-trades workers. Those hands-on jobs will be transformed by AI, automation and software, he said, but they will remain dependent on people who can diagnose failures, apply practical judgment and work safely around complex physical systems.

The numbers inside Ford

At Ford, the shift is already underway. The company employs more than 10,000 skilled-trades workers — roughly 20% of its 56,000 UAW workers. The work has moved beyond traditional maintenance of conveyors and mechanical systems toward repairing robots, handling fiber, maintaining automated equipment and operating increasingly digital manufacturing lines.

Farley said the line separating skilled trades from engineering has become hard to see in newer auto plants.

"The visible line now, it's kind of hard to tell when an engineer or a manufacturing engineer stops, and the skilled trade starts in these newer type operations," he said.

In Ford's newer operations, skilled-trades workers maintain large robotic casting systems, configure digital manufacturing processes and troubleshoot battery-production machinery. Some battery-equipment maintenance, Farley noted, resembles work found in semiconductor fabrication more than a traditional auto plant.

AI in the repair bay

Ford is also deploying AI and augmented reality to support vehicle repairs. Farley cited an engine removal from a Ford Super Duty truck — a job that can take two days and require disassembling the entire vehicle. Ford Pro is using AI to help dealers who have never done the job complete it much faster.

"If you want to take apart a Super Duty, it's like a two-day job to take the engine out. The whole truck is disassembled," he explained. "A lot of people don't have that skill."

"We are using AI for them to say, 'Okay, do this, do that,'" he added. "They're good mechanics, they just don't know. They've never done it before."

A labor-force multiplier

Nelson of Stanley Black & Decker described AI and robotics as tools for confronting a shortage of construction and industrial workers — a godsend instead of a nightmare. Tradespeople, he said, often face backlogs of work their employers cannot complete because they lack labor capacity.

Asked whether AI carries a stigma in the trades, Nelson said he hasn't seen one.

"I think anything that you can bring to them that says: This will make you better at what you're doing, quicker, safer, and you'll get more done in a given day, they're pretty all-in because they've got more work than they can do right now. They see a backlog," Nelson said. "They see a backlog of future revenue that they cannot access because they can't get through what they need to do right now. They want to access that backlog, and anything that can get them through it is well worth it."

Asked if workers want AI to slow down rather than speed up, Nelson demurred: "I think you're getting into some larger questions there."

Nelson described an autonomous downward-drilling robot developed with customers building data centers — projects that require drilling tens of thousands of holes to mount racks, install computing equipment and run cabling. The robot handles the repetitive drilling while skilled workers move to more complex tasks.

"It is a companion," Nelson said. "It is hand-in-hand. It's not a replacement."

The trust problem

Farley stressed that trust determines whether AI systems succeed on the factory floor. Ford already runs AI-powered vision systems in the background to support decisions such as the dimensional control of a panel or whether doors fit correctly.

"It's very important, I think, obviously, to build trust in those moments," Farley said. "If they don't trust that the data's going to be used the right way, somehow against them or somehow in a not-so-nice way, it's going to be a problem. They're not going to want to use the system. They'll want to turn it off."

He compared current anxiety to the historical skepticism toward time-and-motion studies, recalling an early-career moment when a worker confronted him after noticing he was being timed.

"Some guy who was three years older than me [was] saying, 'What, are you trying to take my job?' That's the age-old efficiency tension we've always had," Farley said. "I don't think it's really that different."

The executives' framing amounts to a different AI story from the one usually told about white-collar automation: the binding constraint in manufacturing, construction and infrastructure is a shortage of qualified workers, not an excess of them. Farley said the next generation of skilled-trades workers will need fluency in data, software, programming and automation — with AI systems serving as on-demand trainers when workers meet unfamiliar equipment. For employers competing for scarce technical labor, that could turn AI from a headcount threat into a hiring advantage.