Their careers spanned the personal computing, internet and smartphone waves. But some older workers see AI’s arrival as the cue to exit.
4 min
Luke Michel has already lived through two technology overhauls in his career, first desktop publishing in the 1980s and online publishing later on. But AI? He’s had enough.
So when his employer, the Dana-Farber Cancer Institute, made an early-retirement offer to some staff last year, the 68-year-old content strategist decided to speed up his exit. Before, he had expected to work a couple more years.
“The time and energy you have to devote to learning a whole new vocabulary and a whole new skill set, it wasn’t worth it,” he said.
It isn’t that he’s shunning artificial intelligence—he is learning Spanish with the help of Anthropic’s Claude. But, at this point, he’s less than eager to endure all the ways the technology promises to upend work.
“I just want to use it for my own purposes and not someone else’s,” he said.
After rising for decades and then hovering around 40% in the 2010s, the share of Americans over 55 years old in the workforce has slipped to 37.2%, the lowest level in more than 20 years.
The financial cushion of rising home equity and stock-market returns is driving some of the decline, economists and retirement advisers say.
But for some older professionals, money is only part of the equation.
They say they don’t want to spend the last years of their career going through the tumult of AI adoption, which has brought new tools, new expectations and a lot of uncertainty.
Many people retire when key elements of their work lives are disrupted at once, said Robert Laura , co-founder of the Retirement Coaches Association and an expert on the psychology of retirement.
“Maybe their autonomy is being challenged or changed, their friends are leaving the workplace, or they disagree with the company’s direction,” he said.
“When two or three of these things show up, that’s when people start to opt out.”
“AI is a big one,” he adds. “It disrupts their autonomy, their professionalism.”
Michel, whose work required overseeing and strategizing on website content, has been here before.
When desktop publishing arrived in the 1980s, he was a graphic designer using triangles and rubber cement.
The internet’s arrival changed everything again. Both developments required new skills, and he was energized by the challenge of learning alongside colleagues and peers.
It felt different this time around. “Your battery doesn’t hold a charge as long as it used to,” he said.
He would rather spend his energy volunteering, making art, going to operas and chairing the Council on Aging in North Andover, Mass., where he lives.
In an AARP survey last summer of 5,000 people 50 and over, 25% of those who planned to retire sooner than expected counted work stress and burnout as factors.
About half of those retired said they had left work at least partly because they had the financial security to do so.
In general, older Americans are less likely than younger counterparts to use AI, research shows.
About 30% of people from ages 30 to 49 said they used ChatGPT on the job, nearly double the share of those 50 and older, according to a 2025 Pew Research Center survey of more than 5,000 adults.
Baby boomers and members of Generation X also experienced the sharpest declines in confidence using AI technology, according to a ManpowerGroup survey of more than 13,900 workers in 19 countries.
“We as employers aren’t doing a good enough job saying (to older workers), we value the skills that you already have, so much so that we want to invest in you to help you do your job better,” says Becky Frankiewicz , ManpowerGroup’s chief strategy officer.
Jennifer Kerns’s misgivings about AI contributed to her departure last month from GitHub, where the 60-year-old worked as a program manager.
Coming from a family of artists, she said, it offends her that AI models train on the creative work of people who aren’t compensated for their intellectual property. And she worries about AI’s effect on people’s critical-thinking skills.
So she was dismayed when GitHub, a Microsoft-owned hosting service for software projects, began investing heavily in AI products and expecting employees to incorporate AI into much of their work. In employee-engagement surveys, the company had begun asking them to rate their AI usage on a scale of 1 to 5.
When it came time to write reports and reviews, colleagues would suggest that she use ChatGPT.
“I’d be like, ‘I have no idea how to use that and I have no interest in using AI to write anything for me,’” she said.
It would have been more prudent to work until she was closer to Medicare eligibility, she said. But by waiting until her children were out of college and some of her stock grants had vested, the math worked.
Her first act as a nonworking person: a solo trip to Scotland, where she took a darning workshop and learned how to repair sweaters.
“The opposite of AI,” she said.
Employers already under pressure to cut workers—such as in the tech industry—may welcome some of these retirements, said Gad Levanon , chief economist at Burning Glass Institute, which studies labor-market data.
“The more people retire, the fewer they have to let go,” he said.
Some of the savviest tech users are also balking at sticking around for the AI upheaval. Terry Grimm, who worked in IT for 40 years, retired from his senior software consultant role at 65 last May.
His firm had just been acquired by a bigger firm, which meant learning and integrating the parent company’s AI and other tech tools into his work.
Until then, Grimm expected he might work a couple more years, though he felt that he probably had enough saved to retire.
“I just got to the point where I was spending 40 hours at work and then 20 hours training and studying,” said Grimm, who has since moved with his wife from the Dallas area to a housing development on a golf course in El Dorado, Ark.
“I’m like, ‘I’ll let the younger guys do this.’”
Copyright 2020, Dow Jones & Company, Inc. All Rights Reserved Worldwide. LEARN MORE
The Australian leather house has opened an immersive four-day pop-up in Manhattan, unveiling its Bloom Collection and redefining what a product launch can look like.
Following the successful launch of its Palais Collection, MAISON de SABRÉ has unveiled a new modular handbag system offering more than 720 styling combinations.
AI doesn’t rebel—people design, deploy and profit from it. The real danger lies in allowing tech companies to escape accountability while shaping regulations that protect their dominance.
4 min
A wave of corporate warnings and technical disclosures has flooded the media, with headlines worrying over “swarms” of rogue artificial-intelligence agents launching “unprecedented” cyberattacks, outsmarting their makers, and inching toward a terrifying autonomy. The most revealing part of this narrative isn’t what the software did. It’s who is telling the story—and why. When corporate leaders publicly insist that the systems they financed, engineered and deployed are suddenly beyond their power to contain, skepticism isn’t only healthy; it is essential.
For years, Silicon Valley has drawn scrutiny from civil society and global regulators over tangible harms such as youth mental health deterioration and systematic privacy violations. Today, industry figures seem to be trying to change that public image. Loudly blowing the whistle on their own systems—just as two of the leading companies were preparing for massive initial public offerings—lets AI executives position themselves as a new generation of leaders who have come to terms with their societal responsibilities. They seem to want us to believe that they no longer want to “move fast and break things” but will instead stand as vigilant guardians between humanity and a technological apocalypse.
There is one glaring problem: Software doesn’t rebel. A mathematical model possesses neither intent, malice nor the will to defy its creators, let alone extinguish our species. AI is a human artifact, engineered for profit.
When an agentic model in an evaluation sandbox connects to an unauthorized server or executes an exploit, it hasn’t staged a coup. It has tried to meet the human-defined objectives set out before it through a path its designers failed to constrain. It’s the digital equivalent of the King Midas myth, in which the king’s ill-defined wish turns even his food and drink into gold.
That powerful experimental models were able to discover novel vulnerabilities and breach external systems isn’t a sign of a dangerous superintelligence but of human error or negligence. There is no sentient actor lurking in the weights to be reasoned with, feared or pacified. There are only human software engineers, product managers and corporate boards deciding which guardrails are worth the latency cost and which permissions can be skipped in the race to market.
Policymakers and voters need to resist AI exceptionalism. In any other discipline—from civil engineering to pharmaceuticals—courts and regulators treat a system failure as evidence of bad product design and inadequate safety testing. If an aircraft crashes, we focus on finding the engineering defect, correcting it, and enforcing established liability standards for the damage created.
By leaning on an anthropomorphic narrative, Silicon Valley attempts to repackage its specific human choices that led to experimental, powerful models behaving unexpectedly during tests as an existential peril. Elevating the issue to a cosmic scale leaves the public paralyzed and takes ordinary product accountability off the table.
In the cutthroat race for venture capital and market dominance, building guardrails slows down deployment. Grandstanding about uncontrollable power costs nothing and generates billions of dollars in free publicity, justifying stock prices, all while cultivating an aura of technological capability not only to build the frontier but also ultimately to rein it in.
Governments need to recognize regulatory capture when it stares them in the face. Tech leaders’ strategy looks transparent: Alarm Washington and Brussels into creating a regime in which only trillion-dollar incumbents with fully staffed compliance and safety departments can legally operate. By sitting at the policymakers’ tables before anyone else, these companies can help draft rules digging an impassable moat protecting them from open-source developers and upstart competitors, domestic or international. The real danger is in further concentrating the tech industry into the hands of only a few companies with deep pockets.
Beijing and Washington have brushed off those tech leaders’ calls, albeit for very different reasons. Chinese state media dismissed them as part of the “Cold War playbook” and intended to preserve U.S. dominance. Xi Jinping argued for exactly the opposite at the Brics Summit on Sept. 12, calling on Brics countries to “strengthen cooperation in the field of AI, encourage open source, openness, collaboration and sharing, and break new grounds and scale new heights.” President Trump, steeped in a doctrine of unfettered capitalism and technological supremacy, called fears that AI could destroy humanity a “hoax.” Vice President JD Vance warned that AI companies “begging the government to regulate them” looked like a “Trojan Horse.”
Striving to pursue its “European way” on AI and assert regulatory leadership, Europe, by contrast, welcomed the call. European Union President Ursula von der Leyen made this clear at the State of the EU speech last Wednesday and announced that the EU will invite “the main frontier labs for a discussion on how we can support ongoing industry efforts to pace the frontier.”
Europe has been here before. In an effort to lead global regulation and react to fears borne from ChatGPT, Europe rushed its landmark AI Act into law in 2024. Already the world’s most restrictive rulebook, the framework quickly proved too broad and complex to enforce. Stalled by implementation delays and concerns about European competitiveness, the EU postponed the law’s full rollout, leaving regulations uncertain.
AI should be regulated—risks exist and should be taken seriously. But governments need to act based on available evidence and verified facts, not corporate PR panic, the views of industry insiders, or the desire for quick political wins. The greatest danger facing society isn’t that software will awaken and overthrow its human masters. It is that we will allow the creators of the software to abdicate human responsibility for the systems they choose to build and help them pull up the ladder to market access behind them.
