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

Ford wins J.D. Power's top spot, CEO calls it a 'breathtaking achievement'
Ford wins J.D. Power's top spot, CEO calls it a 'breathtaking achievement'
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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.

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"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. 


  • Expert Warns: Companies Are ‘AI Washing’ by Blaming Layoffs on Automation They Haven’t Actually Built

    Quick Read

    • Many companies blaming layoffs on AI actually overhired during the pandemic and are repackaging one-time rightsizing cuts as structural automation gains.

    • Real AI transformation demands a clear business problem first. Without process redesign and accountability, expensive tools simply become shelf-ware.

    • Investors should verify AI claims in 10-Ks and SEC EDGAR filings, flagging any board strategy that lacks operational leader buy-in.

    • Don't wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now.

    A recent Motley Fool Money episode delivered a pointed warning to retail investors trying to make sense of the wave of AI-attributed corporate restructurings sweeping the market. The host cautioned that a growing share of them may amount to "AI washing," where companies exaggerate the role AI is playing in their business to appear more innovative, efficient, or forward-looking than they really are.

    A male presenter in a dark sweater and glasses stands before a large screen displaying 'Analysis' with charts, graphs, and a prominent '+89%' growth indicator. Several other business professionals are seated around a dark conference table, attentively observing the presentation. The modern meeting room features glass walls and green potted plants, with papers and water glasses on the table.
    Gorodenkoff / Shutterstock.com

    AI-related layoff narratives have become a defining feature of corporate communication in 2026, raising a question investors cannot afford to ignore: are these companies genuinely automating, or are they repackaging traditional cost-cutting in the language of AI? For some businesses, attributing layoffs to AI may also present a more optimistic story to shareholders than admitting demand has slowed or that pandemic-era hiring simply overshot reality.

    Real AI Implementation Starts With a Business Problem

    The hosts' central argument was that a durable transformation begins with a clear operational question, rather than throwing technology against the wall. "If transformation doesn't start with what's the business problem you're trying to solve... you're going to end up buying really expensive technology and not moving your business forward," the host argued during the segment.

    That framing matters because it's common to see corporate AI announcements lead with the technology. Boards approve an AI strategy, communications teams publish the press release, and workforce reductions follow. What the host described as missing in many cases is the unglamorous middle layer: process redesign, data plumbing, change management, and accountability for measurable outcomes.

    Don't wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now.

    Performing Transformation vs. Real Change

    The expert drew a sharp line between "performing transformation" and actually executing it. Performance looks like a polished investor deck and a restructuring charge. Sustaining transformation looks like quarter-over-quarter productivity gains tied to specific workflows.


  • The AI Layoff Headlines You Should Be Most Suspicious Of

    Quick Read

    • Record nonfarm payrolls of 159 million and healthy jobless claims of 215,000 expose the gap between AI layoff headlines and actual labor market reality.

    • Companies that over-hired between 2020 and 2022 rebrand routine workforce corrections as AI efficiency moves because it plays better on earnings calls.

    • As foundation models commoditize rapidly, decision rights, inter-team trust, and a willingness to challenge model outputs become the moat AI vendors can't sell.

    • Don't wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now.

    Every few weeks another company announces headcount cuts and credits the move to artificial intelligence. The framing says the firm is on the frontier, that software has eaten enough of the workflow to make humans redundant, that margins are about to expand. The framing is also, in many cases, marketing dressed up as operations. The aggregate labor data tells a quieter story.

    A person wearing a beige trench coat and white gloves holds a newspaper up to their face, obscuring it entirely except for their brown eyes peering through two perfectly round holes. The newspaper features various financial headlines such as 'BUSINESS,' 'FINANCE,' 'ECONOMIC COLLAPSE,' and 'DOLLAR FALLS' on a white background with black text. The background is a solid, warm beige color.
    Pixel-Shot / Shutterstock.com

    Total nonfarm payrolls climbed to 159 million in May 2026, the highest reading in the series, and initial jobless claims sat at 215,000 for the week ending June 20, 2026, comfortably inside the 200,000 to 250,000 band the data provider classifies as healthy. If AI were actually carving through white-collar payrolls the way the press releases imply, the macro data would show it.

    That gap between headline and data is the entry point for a recent Motley Fool Money segment on what the host called "AI washing," the corporate habit of attaching an AI rationale to decisions that have other, less glamorous explanations.

    The host's argument, addressed to retail investors evaluating transformation claims, was that the question to ask is whether anyone inside the company can describe the business problem the technology is solving.

    AI washing and the rightsizing nobody wants to name

    A lot of the layoffs branded as AI efficiencies are simpler than that. Companies hired aggressively during the pandemic, projected the demand curve forward in a straight line, and ended up with org charts heavier than the revenue could support.

    Don't wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now.

    Rightsizing a bloated workforce is awkward on an earnings call. "We deployed AI to streamline operations" is much easier. Both sentences can describe the same severance package, and from the outside an investor cannot always tell which one is true. So they get told the flattering version.

    The host framed the warning bluntly. "If transformation doesn't start with what's the business problem you're trying to solve, and you're focused more on the technology, you're going to end up buying really expensive technology and not moving your business forward."


  • Most Companies Are Already Failing at AI. They Just Don’t Know It Yet.

    Entrepreneur Media LLC and Yahoo Finance LLC may earn commission or revenue on some products and services through the links below.

    Key Takeaways

    • Companies that use AI primarily to cut costs will get a cost reduction. Companies that use AI to redeploy human judgment toward higher-value decisions will build something that compounds.

    • Technology can be copied. A team that knows how to work alongside AI, adapt continuously and redesign its own workflows is a capability that cannot be overstated.

    Here is the uncomfortable truth about where most organizations stand with AI right now: They are succeeding at the wrong thing. Pilots are running. Productivity tools are deployed. Employees are using AI assistants to write emails faster and summarize meetings they half-attended. By every metric leadership is tracking, the adoption curve looks encouraging.

    But none of that is the hard part. And the hard part is where almost every organization stalls.

    The question most leaders are asking is: How can we use AI to improve what we already do? It's a reasonable question. It's also the wrong one. The better question, the one that separates companies that will lead from those that will follow, is: How should our work look fundamentally different because of AI?

    Those two questions sound similar, but they lead to entirely different places.

    We have seen this before, and the lesson is not what you think

    When factories electrified in the early 20th century, most of them did something logical and deeply counterproductive: They replaced steam engines with electric motors and kept everything else the same. The layouts stayed identical. The workflows were untouched. Managers expected productivity to surge.

    It didn't. For decades, economists were genuinely puzzled. Electricity was a transformational technology: Why weren't the gains showing up?

    The answer is fascinating: The gains appeared only after factories were redesigned from scratch to take advantage of what electricity actually made possible. Distributed power. Flexible layouts. New production sequences that the old steam-driven architecture had made physically impossible. The technology itself didn't transform manufacturing. The redesign did.

    The lag between adoption and transformation wasn't months. It was decades. That should give every leader pause.

    AI is following the same pattern, and we are still very early in the "replace the engine" phase. The productivity gains everyone is expecting may be years away unless organizations are willing to do the harder work.


  • Employers, governments join forces to address AI job loss concerns

    Major employers and even governments have begun to address concerns of AI-driven job losses, according to a new report by the Wall Street Journal.

    Morning Brief Host Julie Hyman is joined by Yahoo Finance Tech Editor Dan Howley and Epistrophy Capital Research chief market strategist Cory Johnson to take a closer look at this headline.


  • AI was supposed to kill engineering jobs, but new data suggests they’re the most resilient

    Image Credits:Chalirmpoj Pimpisarn/EyeEm / Getty Images

    Whether AI is already replacing jobs is the subject of fierce debate.

    Tech layoffs hit their highest single month total in years in May, and AI was the most-cited reason, according to outplacement firm Challenger, Gray & Christmas.

    Software engineering, in theory, is the professional field most vulnerable to automation, given the rapid adoption of AI-powered coding tools. However, researchers at venture firm SignalFire say the hiring data tells a different story.

    "The rationale given for lots of layoffs is consistently AI, and specifically they'll say AI with respect to code; they'll say one engineer could do the job of however many engineers in the past," said Asher Bantock, SignalFire's head of research. "What we're seeing on the ground is a little inconsistent with that."

    SignalFire's analysis, which tracked the careers of millions of employees across more than 80 million companies, suggests that engineering was the most resilient job function in 2025. Instead of focusing on layoffs, which are difficult to track because people often delay updating their employment status after job cuts, SignalFire examined hiring data as a more accurate indicator of real-time workforce trends.

    While total hiring across large tech companies dropped 25% compared to 2019 levels, engineering roles saw a much smaller decline of just 11%, according to SignalFire's latest "State of Talent Report."

    In fact, engineers comprised 55% of all new hires in 2025 across the 12 companies SignalFire classifies as "Tech Majors" — Alphabet, Meta, Apple, Amazon, Microsoft, Netflix, Nvidia, Tesla, Uber, Airbnb, Block, and Stripe. This is a significant jump from 2019, when engineers represented only 46% of new recruits, according to the report.

    The continued need for engineers was even more evident at early-stage startups, which collectively brought on 7% more engineers in 2025 than they did in 2019, SignalFire's data shows.

    If AI were truly substituting for engineering talent, Bantock argued, engineering hiring would be the first to fall amid the current tech hiring contraction. Instead, SignalFire's data shows that engineering headcount is growing faster than most other job functions in tech.

    While Anthropic CEO Dario Amodei warned last year that AI could wipe out half of all entry-level white-collar jobs and push unemployment as high as 20% within five years, the company's own head of economics, Peter McCrory, told TechCrunch in March that he had not yet seen any significant AI-driven effects on the workforce.


  • ‘Wipe out and change are different’: Amazon exec slams AI job apocalypse fears as he hires thousands of Gen Z grads

    AWS CEO Matt Garman, who started at Amazon as an intern, says AI will change entry-level work—not eliminate it. · Fortune · FREDERIC J. BROWN/AFP via Getty Images

    As Silicon Valley debates whether AI will replace millions of office workers, one of the executives building the technology's underlying infrastructure says Gen Z shouldn't buy into the apocalyptic job displacement predictions. Matt Garman, CEO of Amazon Web Services, argued that forecasts of mass white-collar job losses—including warnings from Anthropic CEO Dario Amodei that AI could eliminate up to half of entry-level office jobs—don't hold up under scrutiny.

    "If you believe that half of jobs get wiped out, the whole economy collapses on itself," Garman said on an episode of the Platformer podcast released Tuesday. "Everything goes away. You're not going to have AI, and then you have to go back to those other jobs at some point. The math doesn't work out."

    Instead, Garman said AI will reshape work rather than eliminate it outright. While some jobs may not exist in the future, new jobs will emerge, he argued, because economies simply depend on workers earning money and spending it. 

    He likened the current AI boom to the arrival of Microsoft Excel, which largely replaced workers who spent their days performing calculations by hand. Those jobs changed, but workers adapted by learning new tools.

    "I do think that half of white-collar jobs may change, but wipe out and change are different," Garman added.

    Amazon, he noted, is continuing to invest in young talent. The company plans to hire 11,000 interns and recent graduates this year, and Amazon employs more software developers today than it did two years ago—even as AI coding tools have become dramatically more capable.

    The transition hasn't been painless for the No. 1 company on the Fortune 500, however. Amazon CEO Andy Jassy has said AI-driven efficiency gains will eventually shrink parts of the company's corporate workforce, and last year, 14,000 corporate jobs were cut. At the end of 2025, Amazon employed roughly 1.58 million full- and part-time workers worldwide, including about 350,000 corporate employees.

    What the AWS CEO looks for in hiring talent in 2026

    Garman has a personal stake in the debate over entry-level hiring. He joined Amazon in 2005 as an MBA intern while studying at Northwestern University's Kellogg School of Management and spent nearly two decades climbing the ranks of the company's cloud business before becoming CEO of AWS in 2024.

    The experience may help explain why he remains bullish on young workers, as many companies use AI to automate routine tasks often assigned to new graduates.

    "[When] you talk about entry-level jobs, number one, they're your cheapest employees," Garman said. "They haven't learned bad habits, you can teach them the culture, they're willing to learn the new tools, they're some of the very best employees you can possibly have."


  • PwC Chairman Challenges The AI Layoff Narrative

    PwC's global chairman just dropped one of the market's biggest contrarian views about AI, in that mass adoption points to mass layoffs

    In a CNBC interview at VivaTech in Paris on June 18, PwC Global Chairman Mohamed Kande said that businesses using AI "at scale" aren't simply cutting workers. In fact, they are often adding them, as AI creates new demand around implementation, governance, data, products, and client delivery.

    For context, the layoff narrative has effectively dominated the AI debate across tech, consulting, and white-collar work.

    However, Kande's point is different: Businesses moving the fastest are using AI to increase output, redesign jobs, and boost productivity, not just shrink payrolls.

    PwC's own jobs data backs the shift, showing stronger productivity, wage, and headcount growth at the most AI-exposed companies.

    What PwC's chairman said about AI layoffs

    Mohamed Kande just pushed back on what can be described as the  simplest version of the AI layoff story.

    Speaking at the VivaTech conference in Paris, Kande said businesses adopting AI "at scale" aren't simply cutting workers. His thesis is that the firms moving the most on AI are increasing headcount because the technology lets them expand what employees can do. 

    More AI:

    In his view, AI gives workers "superpowers," making judgement, collaboration, emotional intelligence and adaptability more valuable.

    PwC's own jobs data supports Kande's point, but with a caveat. The firm's 2026 AI Jobs Barometer found that companies most exposed to AI have grown headcount faster than the least-exposed firms. 

    However, it also found out that entry-level work is evolving fast, with junior roles requiring senior-level skills.

    Kande isn't saying AI comes with no labor risks but he said the bigger shift is from replacement to redesign, where businesses require fewer routine tasks but more workers who can use AI to create value.

    That split also shows up in how the top tech leaders frame AI and jobs. 

    According to Reuters reporting from VivaTech in Paris, Jeff Bezos said AI could create labor shortages instead of just creating mass redundancy. 

    Moreover, a Business Insider report showed that Sam Altman said in a CNBC interview that the companies he sees adopting AI most aggressively are also hiring the most. 

    Additionally, in a Wall Street Journal interview, Microsoft CEO Satya Nadella argued AI should augment work broadly, not concentrate economic power in a few model companies.

Expert Warns: Companies Are ‘AI Washing’ by Blaming Layoffs on Automation They Haven’t Actually Built