Why Job Seekers Chase Vanishing Roles While Critical Positions Go Unfilled

Why Job Seekers Chase Vanishing Roles While Critical Positions Go Unfilled

The iCMS study cited by Korn Ferry reveals a stark reality: technology jobs attracted 65 applicants per opening in 2025, business and finance roles drew 62, and management positions garnered 51. Meanwhile, healthcare positions attracted just 25 applicants per opening, and education roles only 18. This data illustrates a profound disconnect, but the Korn Ferry analysis only scratches the surface of a more complex crisis in workforce adaptation.

I have spent 15 years studying labor market dynamics, and this mismatch represents something more troubling than a simple supply-demand imbalance. It reflects a workforce in denial about structural economic change, companies paralyzed by technological uncertainty, and a failure of labor market institutions to facilitate transitions.

The Mismatch Is Real But The Diagnosis Is Incomplete

The data from iCMS tracking application rates provides clear evidence of misaligned incentives. When tech jobs attract nearly double the average applications while the financial sector eliminated 49,000 positions in 2025, we're watching people queue for disappearing opportunities. Benjamin Frost's observation that "people are applying for jobs no one else will" captures the desperation, but not its root causes.

The Bureau of Labor Statistics reported in September 2025 that healthcare and social assistance added 534,000 jobs over the previous 12 months, while professional and business services shed 198,000 positions. Yet according to LinkedIn's 2025 Global Talent Trends Report, 73% of white-collar workers reported they would not consider transitioning to healthcare or education roles even if unemployed for six months. This isn't just about hope or frustration. It's about identity, sunk costs, and rational economic calculation.

A finance professional earning $95,000 annually faces a genuine dilemma when considering a healthcare support role paying $42,000. The Korn Ferry piece suggests job seekers are irrationally chasing their tails, but many are making calculated bets that waiting for a white-collar role, even with extended unemployment, produces better lifetime earnings than accepting a 55% pay cut. Research from the Federal Reserve Bank of San Francisco found that workers who switched industries during the 2008-2009 recession experienced wage penalties averaging 17% that persisted for over a decade.

AI Disruption Is Freezing Markets But Not How You Think

The article correctly identifies that companies are hesitating to fill finance and business operations roles while determining AI's impact. But this hiring freeze creates a prisoner's dilemma. Every company waiting to see how others restructure roles delays the market signal that would redirect job seekers to growth areas.

Deloitte's 2025 Global Human Capital Trends study surveyed 10,000 business leaders and found that 68% were "pausing hiring in roles likely to be affected by AI" but only 23% had concrete plans for retraining affected workers. This creates a limbo where positions remain posted to maintain optionality, artificially inflating the appearance of opportunity.

Consider what happened at Klarna, the Swedish fintech company. CEO Sebastian Siemiatkowski announced in February 2024 that their AI assistant handled the equivalent work of 700 customer service agents. By March 2025, Klarna had reduced headcount from 4,500 to 3,000 through attrition while maintaining revenue growth. But here's what the headlines missed: Klarna didn't eliminate 1,500 customer service roles. They eliminated 800 customer service positions, 400 back-office finance roles, and 300 middle management positions while adding 180 AI training, prompt engineering, and machine learning roles.

The jobs being created require fundamentally different skills than those being eliminated. When job seekers apply for "technology" roles at 65 per opening, many are applying for traditional software engineering or project management positions, not the AI-adjacent roles companies actually need.

The Service Sector Problem Nobody Wants To Address

The Korn Ferry analysis notes that healthcare attracted only 25 applicants per opening and education just 18, framing this as a simple preference mismatch. This explanation ignores structural issues that make these sectors unattractive beyond cultural bias against service work.

The American Hospital Association reported in August 2025 that the average registered nurse vacancy costs a hospital $56,300 in temporary staffing, overtime, and lost productivity. Yet hospitals continued to offer starting salaries averaging $77,600 in high-cost coastal markets where a one-bedroom apartment rents for $2,800 monthly. The math doesn't work. Healthcare isn't understaffed because people don't want to care for others. It's understaffed because the jobs don't pay enough to live where the jobs exist.

Education faces similar challenges. The National Education Association found that average teacher pay fell 5% in real terms between 2019 and 2025, while workload increased measurably. Teachers in Texas and Florida reported spending an average of $750 of personal funds annually on classroom supplies while earning $57,000. When a former business analyst can earn $85,000 in a corporate training role versus $61,000 as a high school teacher with larger classes and more bureaucracy, the choice becomes obvious.

Hospitality tells an even starker story. The American Hotel and Lodging Association reported 486,000 unfilled positions in December 2025, with applications per opening at just 12. But dig deeper: these roles averaged $32,000 annually with irregular hours, no remote work option, and high physical demands. The unemployment rate for workers with bachelor's degrees was 2.3% in late 2025. Why would someone with a degree and options choose grueling work that can't support a family?

The Real Crisis Is Workforce Rigidity

David Ellis observes that his highly skilled clients have been "chronically out of work" and "aren't sure what to do next." This uncertainty reveals a failure of labor market infrastructure. Other developed economies handle technological transitions differently.

Germany's Kurzarbeit system provides wage subsidies for workers to reduce hours rather than face layoffs, coupled with mandatory retraining. When BMW anticipated that electric vehicle production would require 30% fewer workers than internal combustion vehicles, they didn't lay off workers. They partnered with the government to retrain 15,000 workers over four years in battery technology, software, and advanced manufacturing. The program cost €340 million but maintained employment and skills.

Singapore's SkillsFuture initiative provides every citizen over 25 with a $500 annual training credit (approximately $370 USD) plus targeted programs for mid-career transitions. When Singapore identified healthcare worker shortages in 2023, they launched a program paying 90% of salary for professionals transitioning into nursing, allied health, or medical technology roles during their two-year retraining period. The program moved 8,400 workers from declining sectors into healthcare by the end of 2025.

The United States offers nothing comparable. The Workforce Innovation and Opportunity Act provides limited retraining funds, typically $3,000-$5,000 per person, insufficient for meaningful reskilling. Without institutional support, workers rationally choose to exhaust savings waiting for similar roles rather than self-fund a career transition with uncertain returns.

AI Tools Are Changing Job Search In Counterproductive Ways

The article mentions that AI enables job seekers to quickly tailor resumes and applications, contributing to the flood of applications for each white-collar role. This understates the transformation in job search behavior.

Jobscan, a resume optimization platform, reported that its users applied to an average of 47 positions monthly in 2025, up from 23 in 2022. The marginal cost of each application approached zero. ChatGPT, Claude, and similar tools can generate a customized cover letter in 30 seconds. This creates massive application volume without signaling genuine interest or fit.

Recruiting technology company Greenhouse found that companies using their platform received 134% more applications per role in 2025 versus 2023, but the percentage of applicants reaching first-round interviews fell from 8% to 3.4%. More applications didn't produce more qualified candidates. It produced more noise.

This dynamic hurts both job seekers and employers. Companies respond to application volume by implementing more aggressive automated screening. Job seekers respond to automated screening by applying more broadly. The result is a race to the bottom where genuine qualifications and interest become harder to signal.

What Companies Should Actually Do

Renee Whalen's observation that "firms are still looking for talent" while Ben Frost predicts job seekers will be "chasing their tails" suggests companies see themselves as passive observers of labor market dysfunction. This is incorrect. Companies created this problem and can help solve it.

• Stop posting roles you don't intend to fill. If you're truly waiting to understand AI's impact before hiring, remove the posting. Maintaining phantom job listings to "keep options open" wastes everyone's time and distorts market signals. IBM removed 3,200 job postings in June 2025 after an internal audit found that 41% had been open over 180 days with no serious candidate consideration. Applications for remaining IBM roles became higher quality within six weeks.

• Invest in internal transitions before external hiring. When Accenture determined that AI would eliminate approximately 18,000 traditional analyst roles over five years, they didn't announce layoffs. They created Accenture LearnVantage, an internal marketplace where affected employees could spend up to 20 hours weekly training in high-demand skills while maintaining salary. By December 2025, they had transitioned 6,300 analysts into data science, AI training, and client advisory roles. This cost roughly $47,000 per person but retained institutional knowledge and avoided severance costs averaging $78,000 per person.

• Create bridge programs into understaffed sectors. Cleveland Clinic partnered with local tech companies in 2024 to create a 16-month pathway for laid-off software professionals to become clinical informatics specialists, combining their technical skills with medical training. Participants earned $52,000 during training (subsidized by the hospital and state workforce funds) and $94,000 upon completion. The program filled 240 critical roles that had been vacant an average of 11 months.

• Be transparent about role transformation. When JPMorgan Chase announced in March 2025 that AI would change 80% of jobs across the bank, they did something radical: they published detailed descriptions of what each major role would look like in 2027, including required skills, expected activities, and compensation ranges. This allowed current employees to make informed decisions about whether to train into the new version of their role, transition to a different role, or leave. It allowed external candidates to prepare for roles that would actually exist. Application quality for priority roles increased 67% within three months.

What Job Seekers Must Accept

Job seekers also need to reckon with uncomfortable realities. The white-collar career path that dominated professional life for 60 years is breaking down. The assumption that a business degree, corporate experience, and professional credentials guarantee stable, well-paid work until retirement no longer holds.

The Federal Reserve Bank of St. Louis found that workers who proactively retrained ahead of displacement maintained 94% of previous earnings in new roles, while those who waited until after job loss recovered only 78% of previous earnings on average. If you work in finance, business operations, middle management, or routine analysis, you should assume your current role will fundamentally change or disappear within five years. The question is whether you'll control that transition or have it forced upon you.

This doesn't mean abandoning white-collar work entirely. It means adding skills that complement AI rather than compete with it. Financial analysts who understand how to train and audit AI models for financial forecasting are in high demand. Business operations professionals who can design human-AI workflow systems are scarce. Middle managers who can translate between technical teams and business stakeholders are critical.

But it might also mean accepting that service sector work isn't a step backward. The assumption that office work is inherently superior to care work or skilled trades is cultural, not economic. Master electricians in major metros earn $95,000 to $125,000. Nurse practitioners earn $118,000 to $145,000. Skilled tradespeople can't be automated away. Neither can nurses, teachers, or therapists. These roles offer something increasingly valuable: certainty that the work will exist in 10 years.

The Policy Failure Nobody Mentions

The labor market mismatch described in the Korn Ferry piece reflects a policy failure that neither job seekers nor companies can solve individually. The United States invests approximately 0.1% of GDP in active labor market policies (training, job search assistance, transition support) according to OECD data from 2024. Denmark invests 1.4%. Sweden invests 1.1%. France invests 0.9%.

These countries don't have frictionless labor markets, but they facilitate transitions far more effectively. When Maersk automated 7,000 logistics roles across Denmark between 2021 and 2024, 83% of affected workers found new employment within 18 months at similar or higher wages, supported by comprehensive retraining programs. When General Motors eliminated 14,000 positions across the United States in 2019, only 62% had found comparable work after 18 months, and those who switched sectors earned an average of 23% less.

The Workforce Innovation and Opportunity Act, America's primary federal workforce program, received $3.7 billion in funding for 2025. This works out to roughly $157 per unemployed person or $24 per working adult. Germany's Federal Employment Agency operates on an annual budget of €39 billion (about $43 billion) for a workforce one-quarter the size of America's. The resource difference shapes outcomes.

State and federal governments should dramatically expand support for mid-career transitions through portable training accounts ($10,000 per worker), income support during retraining (70% of previous salary for up to 18 months), and employer subsidies for hiring career changers (50% of salary for first year). This would cost approximately $47 billion annually if 2 million workers participated. For context, unemployment insurance cost $138 billion in 2020, though much of that was pandemic-related.

What Happens Next

Ben Frost predicts the white-collar hiring environment will become "even more hypercompetitive." This is likely correct, but it challenges a broader structural change. The traditional white-collar career model is in decline.

This model assumed expanding corporate structures would continually absorb college graduates into stable careers with predictable advancement. AI breaks this assumption. Tasks previously requiring human judgment (reviewing contracts, analyzing financial statements, assessing loan applications) are becoming automated. The remaining work requires either high-level strategic thinking that AI can't handle or interpersonal skills that humans uniquely provide.

This bifurcates the labor market into two categories: high-skill, cognitive work that complements AI, and high-touch human work that can't be automated. The middle ground—routine cognitive work filling most white-collar jobs—is disappearing.

Meanwhile, healthcare, education, skilled trades, and personal services will grow. The Bureau of Labor Statistics projects that seven of the 10 fastest-growing occupations through 2032 are in healthcare. Home health aides, nurse practitioners, and medical technicians will add 3.5 million jobs. Wind turbine technicians and solar installers will add 127,000 jobs. The jobs exist. They're just not the jobs that college-educated professionals spent four years and $120,000 preparing for.

The labor market will eventually adjust, but the transition will be challenging for those who delay adaptation. Manufacturing employment collapsed from 19.5 million in 1980 to 12.3 million in 2010. Displaced workers who retrained quickly fared reasonably well. Those hoping for factories to reopen experienced permanent wage losses and higher rates of disability, depression, and early death. Research by Anne Case and Angus Deaton documented these "deaths of despair" extensively.

White-collar workers face a similar inflection point. The jobs they're chasing will become scarce regardless of how many applications they submit. The jobs they're avoiding will become more plentiful and, potentially, better compensated as shortages persist. The question is whether individuals, companies, and policymakers will facilitate this transition or pretend it isn't happening until crisis forces action.

I have observed this pattern before. In the late 1990s, I worked with manufacturing workers in the Midwest who insisted their layoffs were temporary, that factories would recall them once the economy improved. They were wrong. The factories never reopened. Many of those workers never fully recovered economically.

Today's white-collar workers face a similar reckoning. The difference is they have more resources, education, and options. But they need to act on those advantages rather than waiting for a labor market that no longer exists to reassert itself. The jobs they want are disappearing. The jobs that exist are waiting. The gap between those realities defines this decade's labor market challenge.

To gain more insights into this topic, explore this Korn Ferry article.