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A Mismatch of Expectations
Incongruity…The Great Mismatch…Systematic Upheaval. It’s being called a lot of things, but make no mistake- The talent that companies need is still difficult to attract.
What are the broader implications for this inflection point on how employers engage the right talent?
The examples 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. Yet many firms remain desperate to fill a host of key positions that either partner with AI or that AI can’t do. Recently, there were 6.9 million job openings in the US, in industries as diverse as construction (202,000) to professional and business-services (1.3 million). In January, one major semiconductor company advertised for more than 3,000 open positions, everything from electrical engineers and water-treatment specialists to administrative assistants, tax experts.
Frustration on both sides is common. 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 3.1 percent, as low as it’s been in more than a decade.
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.
This isn’t the first time the job market has undergone a major reset. The Industrial Revolution, for example, caused a profound shift as millions moved from agricultural and artisanal work into factory-based production. Most of these workers lacked the skills needed to operate new machinery, which was often unfamiliar and rapidly evolving. Early training was minimal—typically just observing experienced workers for a short time—while foremen corrected mistakes or disciplined slow performance. Over time, more forward-thinking organizations introduced structured training, including onsite schools and standardized instruction for roles like machinists and salespeople.
The transition was long and often turbulent. In its early stages, resistance was common. Textile workers in northern England famously destroyed mechanized looms they believed threatened their livelihoods. Throughout the 19th century, workers in countries like Germany, France, and the United States protested low wages and poor working conditions tied to industrial labor.
Gradually, however, the system evolved. By the mid-20th century, a combination of union efforts, government regulation, and more progressive corporate practices helped stabilize labor markets. Skilled workers could find employment more reliably, while unskilled workers increasingly had access to training within organizations. What began as a chaotic and disruptive shift ultimately led to more structured pathways for workforce development and employment.
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.
Most companies are only beginning to identify the skills their workforces will need to work side by side with AI. It’s a total rewiring- Even if companies figure out the job architecture, they 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. Is it reasonable to expect hiring managers and candidates to keep up? Or is this the new normal?
*Source: Briefings Magazine, 4/26.
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