Companies that over-hired in 2022 are now stuck with expensive employees who won't leave due to a weak job market. This creates a bottleneck, forcing companies to eventually lay off these 'seniors' to make room for new, cheaper 'freshmen' hires, signaling a turn in the labor market.
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Beyond displacing current workers, AI will lead to hiring "abatement," where companies proactively eliminate roles from their hiring plans altogether. This is a subtle but profound workforce shift, as entire job categories may vanish from the market before employees can be retrained.
Current layoffs are driven less by AI-driven automation and more by financial strategy. Companies are cutting labor costs to free up budget for necessary AI investments and to project an image of being technologically advanced to investors.
While a single performance-based layoff can target underperformance, repeated rounds signal a systemic failure in leadership. It suggests managers are unable to hire, coach, or provide feedback effectively, making it a management problem rather than an individual employee issue.
A slow job market has created a new burnout phenomenon: "quiet breaking." Unlike quiet quitting (doing the bare minimum), employees feel trapped in their current roles. They are burning out from working harder than ever in jobs they are unhappy with but cannot easily leave.
While high-profile layoffs make headlines, the more widespread effect of AI is that companies are maintaining or reducing headcount through attrition rather than active firing. They are leveraging AI to grow their business without expanding their workforce, creating a challenging hiring environment for new entrants.
Companies are preemptively slowing hiring for roles they anticipate AI will automate within two years. This "quiet hiring freeze" avoids the cost of hiring, training, and then laying off staff. It is a subtle but powerful leading indicator of labor market disruption, happening long before official unemployment figures reflect the shift.
The market is split. The 'contract' market includes tenured employees and locked-in prices from 2022. The 'spot' market includes new hires and resale inventory, which is trying to revert to 2019 affordability levels. This tension explains conflicting economic signals.
Robert Kaplan suggests the labor market's sluggishness might not be a simple cyclical slowdown. He points to a significant "matching problem" where open jobs don't align with the skills of job seekers. This structural issue limits the effectiveness of monetary policy as a solution.
Previously, scarce and mission-driven tech workers could refuse to build features that harmed users. Mass layoffs created a labor surplus, removing workers' leverage and allowing companies to push through user-hostile changes without internal resistance.
In a paradigm shift like AI, an experienced hire's knowledge can become obsolete. It's often better to hire a hungry junior employee. Their lack of preconceived notions, combined with a high learning velocity powered by AI tools, allows them to surpass seasoned professionals who must unlearn outdated workflows.
