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Firms are struggling to find people with the right skills. How to solve one of the greatest talent imbalances in a generation.
The great mismatch
By Russell Pearlman / Photo Illustrations by Tim Ames
Almost every product can be improved, forcing companies to decide whether to fund the efforts.
The problem
The devotion to perfection can energize— or bankrupt—firms.
why it matters
Take some risks and evaluate designers based on customer-success metrics.
The solution
How to Spot an
AI-Ready Leader
The Ultimate Guide
to Strategic Workforce Planning
Microchip Breakthroughs
The most pressing issue for most organizations is that they can’t find people with specific skill sets. Hospitals need nurses and factories need machinists, to be sure, but many firms need workers who can partner with AI. Too few young people are entering the workforce with those specialized skills, and too few older workers are willing or able to build them. Companies, of course, have always complained about the lack-of-skills problem. But the current mismatch is a complex “minestrone soup” of problems that has slowed down the hiring process at many organizations, says David Ellis, Korn Ferry’s senior vice president of talent transformation. Simply put, experts are anticipating a collision between a dearth of skills and a massive technology-driven labor-market upheaval. The World Economic Forum estimates that between now and 2030, the tech revolution will create 170 million new jobs worldwide while destroying 92 million others. Last fall, Walmart CEO Doug McMillon, who oversees 2.1 million employees, said that AI will change “literally every job.”
Most companies are only beginning to identify the skills their workforces will need to work side by side with AI. These discussions have produced lots of spreadsheets and many weeks’ worth of committee meetings, says Liz Eversoll, CEO of Career Highways, a workplace consultancy in Wisconsin. “It’s a total rewiring,” she says. Even if they’ve figured out the job architecture, companies need time to shift roles around, create new job classifications, recruit new employees, and retrain existing ones. Time, however, is the last thing many companies feel they have, with the pace of AI development potentially making all those efforts obsolete before they even get off the ground. Many mid-sized and large organizations need two years to implement a full workforce transformation, which isn’t nearly fast enough to respond to what they’re facing, experts say. For context, Google’s Gemini AI model is 61 times more powerful than it was in 2023. “HR can’t keep up,” Eversoll says.
his isn’t history’s first massive job market reset, of course. The industrial revolution triggered a seismic shift in labor, with tens of millions of people around the world moving from agricultural and artisanal jobs to production-line jobs in factories. Few of those ex-farmworkers and artisans had the skills to operate the machinery they were being asked to use (unsurprising, given that much of the technology was brand-new). Early on, their “training” consisted mostly of watching an existing employee for a few hours or days, with foremen handling follow-up development either by correcting the workers who made mistakes or disciplining the ones who were too slow. Eventually, savvier organizations developed onsite schools to provide standardized training to machinists, salespeople, and others. Some companies even produced step-by-step instructions for operating the new machinery.
This transition, which took decades, was far from smooth. Early on, the original Luddites, textile artisans in northern England, smashed the mechanized looms they believed were destroying their livelihood. Throughout the 1800s, in Germany, France, and the United States, workers protested exploitative wages and working conditions. By the 1940s, through a combination of union organizing, government regulation, and innovative corporate thinking, labor markets had settled. Skilled workers could generally find companies willing to hire them, and unskilled workers could join organizations that would train them.
Automation and computers caused their fair share of disruption through the last part of the 20th century. New technologies made it possible for white- and blue-collar workers to do their work faster, better, and cheaper, and with less manpower. For instance, in the 1970s, US Steel’s Gary Works, one of the largest steel mills in the United States, had 30,000 employees. By the 1990s, it had only about 6,000 workers, but it was producing higher-quality steel, and in even larger quantities. While occasional strikes took place, there wasn’t the broad-based strife that marked the transition brought about by the industrial revolution. “The changes at the end of the 19th century were greater than in any decade of the digital era,” says David Deming, a professor of political economy at Harvard and author of a 2025 National Bureau of Economic Research paper on technology disruptions in the labor market.
This was partly due to the economy of the last 40 years, experts say, which created millions of new jobs. Indeed, between 1980 and 2000, the nation’s unemployment rate averaged slightly over 6 percent, a moderate rate relative to historical data. Unlike the industrial revolution, which forced people to do different work in a new environment, people in the late 20th century were already used to office and factory work. In addition, much of modern work centered around one device: the computer. Learning how to use the burgeoning technology went a long way toward being qualified for thousands of different jobs.
The current mismatch shares elements of the two prior structural overhauls. As in the industrial revolution, millions of workers are faced with having to learn a radical new technology—in this case, AI—that until a few years ago was the stuff of science fiction. And similar to the reset of the late 20th century, unemployment is quite low (since the COVID-19 pandemic ended, the rate has never risen above 5 percent). But today’s transformation, experts say, is far more stubborn than its predecessors. For one thing, modern roles often demand highly specialized skills that can require years of training. An out-of-work marketing manager can’t immediately become a nurse, no matter how desperate the hospital may be to hire nurses, and white-collar professionals can’t immediately learn AI skills. The issue isn’t just a lack of training, either; it’s a lack of economic and cultural priorities. Unlike the 19th century population boom, the current mismatch, as Ellis notes, is a combination of multiple problems that has slowed down the hiring process at many organizations. Another complication is that the high price of housing makes workers far less mobile than they were in the 18th, 19th, or even 20th centuries—even if they’re relocating to try to take advantage of more job opportunities. For example, in 2025, the rate of interstate labor migration hit a 40-year low, despite a record number of job openings in Texas, Florida, and other Sunbelt states.
But the biggest difference between today’s transition and its precursors is speed. The industrial revolution happened over more than a century; the tech overhaul spanned a generation. The AI revolution will seemingly stretch a decade or less. “The market will equilibrate eventually, but the speed of that equilibrium is what causes pain,” Betsey Stevenson, former Chief Economist of the United States Department of Labor, said last year.
olving today’s great mismatch won’t be easy for firms. Academics may debate the solution for years to come. For now, Korn Ferry’s Ellis says that smart organizations need to simplify their approach to the issue—first by thinking about how specific work will be done. Will AI, humans, or some combination do it? “Answering that question makes it a lot easier to figure out,” says Ellis, and ultimately determine what are the jobs and skills an organization will need over the next several years. Companies can turn to a variety of different software packages to design job architecture, streamline hiring processes, and potentially reduce workforce-transformation time by months or even years.
Once companies identify the skills they need, experts suggest that they stop overthinking their approaches to hiring and training. Kolm, the productivity consultant, understands the urgency leaders feel, but he emphasizes that companies need to grant employees and new recruits time and resources—both for their current work and for their development of the skills they’ll need for the future. “Getting people in the door now helps the employer get out of jail today,” he says. Leaders should ensure that workers understand that learning these new skills will help them professionally, whether immediately or over the long term. “There’s not a talent shortage and people don’t lack ambition,” Eversoll says. Many new skills won’t require years of schooling. For instance, Eversoll suggests giving people a project that requires them to learn one new skill. Another idea: Team people up with different essential skills and have them teach each other.
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By Russell Pearlman / Illustrations by Tim Ames
Hiring:
ate last year, one of the big US auto manufacturers had to make multiple hires for the same role. It was a traditionally blue-collar position, but one that could change considerably if new technology and techniques sweep across the factory floor over the next few years.
The automaker posted the role in a variety of forums and used some awe-inspiring language to describe the work: strategic advisor on manufacturing process improvement, background in ISO standards and quality accreditation recommended. The company got dozens of applicants—and hired none of them.
It’s not that there was a shortage of people who could do the job. It’s just that the actual role, while highly skilled and well compensated, was neither strategic nor glamorous enough to attract the right candidate. “The role was for a guy who can tighten bolts to a very specific specification and show others how to do it, too,” says John Kolm, CEO of Team Results USA, a workplace-productivity consultancy that assisted the manufacturer.
This example, and millions more like it, are rampant in the US job market. Plenty of people want new jobs. According to one survey, some 38 percent of employees intend to look for jobs in 2026, up from 29 percent at the beginning of 2025. That implies that some 65 million Americans are on the hunt. On the flip side, even at a time when firms are holding back on payroll and hoping AI will take over roles, they remain desperate to fill a host of key positions that either partner with AI or that AI can’t do. Recently, there were 6.5 million job openings in the US, in industries as diverse as construction (292,000) to professional and business-services (1 million). In January, one major semiconductor company alone advertised for more than 3,000 open positions, everything from electrical engineers and water-treatment specialists to administrative assistants, tax experts, and—perhaps ironically—talent recruiters.
But these days, job candidates and companies can be like the clichéd ships passing in the night—instead of on the open seas, these fleeting connections are made through online job boards or in interviews, only to be lost. The nation’s hiring rate, which measures the flow of new workers into jobs relative to the existing workforce, is at a paltry 3.2 percent, as low as it’s been (save for one month at the height of the COVID-19 pandemic) in a decade. And the US is far from alone: For example, unemployment in the UK is the highest it has been in years.
Once, there was the so-called War for Talent, which theorized that companies wouldn’t be able to find and keep the workers they needed because of demographic declines. Now, experts say, it’s more of what you might call a Battle for Balance—a race to find and develop the people who have the right skills for the roles firms need to fill. “It’s a mismatch of expectations,” Kolm says.
There’s not a talent shortage and people don’t lack ambition.
It’s not just artificial intelligence that is upending businesses and causing talent mismatches. According to a survey by the World Economic Forum, a variety of innovations will force leaders to rethink how
work is done (and who does it) between now and 2030.
“
AI Skills Aren’t Enough...
For Firms or People
The current mismatch is a ‘minestrone soup’ of problems that has slowed down the hiring process at many organizations.
“
The tech revolution will create 170 million new jobs globally, and destroy 92 million others.
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First Corporate Use: 1962—Chips installed in US Air Force computers
2025 Corporate Spending:
$650 billion to $700 billion
By 2030:
New “power-sipping” chips could revolutionize both factories and offices—but only if companies can find engineers to build and design them.
Hire for skills, not CVs
Leadership Moves
Career Steps
Experts say it may take years to fix this once-in-a-generation mismatch between employee skills and corporate needs, but here’s how to accomplish it:
To improve the odds of attracting the right candidates, prioritize skills over experience in job descriptions.
Prioritize reskilling
The World Economic Forum estimates that 50 percent of today’s employee skills will be outdated by 2030. Firms that jump on reskilling can gain a competitive edge.
Build talent before you buy it
HR pros estimate that employees promoted internally are roughly 40 percent less likely to leave in their first year than external recruits.
Use AI to anticipate gaps, not just to automate work
Workforce analytics can identify emerging skills shortages early, helping firms avoid paying wage premiums for outside hires.
Keep the conversation going
Firms that have regular discussions with employees about their skills and futures do a much better job of preparing them for business shifts.
Pair technical learning with human strengths
Improving creative and problem-solving skills will help, since AI is expected to struggle to automate those uniquely human strengths.
Become AI literate, not just AI aware
Workers with advanced AI skills can expect up to a 56 percent premium in pay, one study shows.
Don’t just ladder climb
Careers that include lateral moves and project work are more resilient and help when transitioning to new jobs.
Don’t be shy about bragging
Workers who clearly articulate their capabilities are significantly more likely to be considered for stretch roles and internal opportunities.
Take ownership of learning momentum
Don’t wait for firms to offer training; raise your hand for it, or if none is available, invest in your own.
Ending the
Great Mismatch
Robots
First Corporate Use: 1959—Robot performs tasks on vehicle-assembly line
2025 Corporate Spending:
About $50 billion
By 2030:
“Cobots,” or robots working next to humans, could become financially viable for most businesses.
Biotech Breakthroughs
First Corporate Use: 977—Researchers synthesize a human protein for the first time
2025 Corporate Spending:
$1.7 trillion to $1.9 trillion
By 2030:
“Living factories,” where microbes do much of the heavy lifting, could not only produce new medicines, but also brew plastics and even cement.
Energy generation, storage, and distribution
First Corporate Use: 1995—Giant lithium-ion battery helps stabilize Tokyo’s power frequency
2025 Corporate Spending:
About $32 billion for battery storage
By 2030:
Firms that fill their workforces with “green talent” could turn a significant
corporate expense—power—into a potential revenue source.
Laser and optics improvements
First Corporate Use: 1961—Laser helps researchers investigate how light interacts with matter
2025 Corporate Spending:
About $20 billion
By 2030:
Working in the car could become far more productive in self-driving
vehicles that can display portable holograms.
Satellite Proliferation
First Corporate Use: 1962—A live television broadcast is relayed via satellite
2025 Corporate Spending:
$360 billion to $480 billion
By 2030:
The number of satellites in orbit could triple over the next five years, making high-quality, low-cost telecom services far more accessible.
New materials and composites
First Corporate Use: 2012—Self-healing concrete used to repair lifeguard station in the Netherlands
2025 Corporate Spending:
$65 billion to $130 billion
By 2030:
Self-repairing, energy-conducting walls and other applications could force companies to find new types of designers and builders.
Quantum computing
First Corporate Use: 2011—Quantum computing solves complex software-verification problems
2025 Corporate Spending:
$1 billion to $3 billion
By 2030:
No longer theoretical, quantum computing could cut research time
significantly for finance and pharma businesses.
Firms aren’t filling a lot of roles because they aren’t seeing the modern skill sets they need, creating an unprecedented talent gap.
The problem
Organizations can’t grow with a workforce that’s off-kilter.
why it matters
Companies need to devote resources to retrain employees and to educate the broader workforce that change is needed.
The solution
or a while, many HR officials held out hope that more accurate job postings would attract the right workers. Most now feel that this approach hasn’t put a dent in the issue. Indeed, experts say a systematic upheaval is called for—the kind that comes along once every few decades at most. Despite all the postings, many companies can’t figure out whether the skills they seek now will still be in demand in a couple of years. Meanwhile, workers at all levels aren’t sure what skills firms want (or, for that matter, whether they already have them). Everyone is under pressure to make work-related decisions quickly, fearing that AI will make their businesses, or careers, obsolete. The issue is causing major problems now, and potentially even bigger ones down the road.
The great mismatch
The Ultimate Guide
to Strategic Workforce Planning
How to Spot an
AI-Ready Leader