AI making white collar work superfluous
Imagine a future where a corporate boardroom is empty of humans, yet decisions are made with surgical precision. Not because AI has taken over—but because it has made the middle manager, the analyst, the coordinator, the planner utterly redundant. This isn’t a dystopian fiction. It’s the trajectory we’re on, and the numbers are starting to show it.
In May 2025, 38,000 job cuts were directly attributed to artificial intelligence [1] That’s the highest monthly total since tracking began in 2023, according to Challenger, Gray & Christmas. Through May of this year, companies have already blamed nearly 88,000 layoffs on AI—more than all of last year combined. [1] This isn’t about a sudden collapse; it’s about a slow, structural shift. AI is becoming the reason companies reach for when they restructure, and the reason they don’t replace workers who leave.
The technology sector remains the epicenter of this pressure. In May, tech employers announced more than 38,000 cuts—the sector’s highest monthly total since August 2024. This is no longer just a growth story or a margin story. It’s a labor market story. The narrative that AI will “augment” workers rather than replace them is giving way to something more uncomfortable: AI is quietly making entire categories of white-collar work superfluous.
The Pattern of Superfluity
The mechanism is subtle but powerful. Companies don’t fire everyone at once. They stop hiring for certain roles. They let attrition shrink teams. They consolidate functions that were once handled by multiple people into a single AI-augmented role—or no role at all. The official data is mixed, but the trend is clear. The JOLTS report for April showed professional and business services job openings bouncing back, but hires and layoffs both fell. That’s the tell: companies still want workers, but they are moving more slowly, hiring more selectively, and pressuring those white-collar roles that can be automated or consolidated.
This is not about robots taking over factories. It’s about AI absorbing the cognitive work that once defined the middle class: drafting reports, analyzing data, scheduling meetings, managing workflows, making routine decisions. The work that keeps offices running is being automated not with fanfare, but with quiet efficiency. The result is a labor market where the demand for human judgment is shrinking, even as the economy grows.
The historical parallel is instructive. During the Industrial Revolution, machines replaced physical labor, but new industries absorbed displaced workers. The Information Age created entirely new categories of work. But AI is different. It targets the very cognitive functions that enabled those transitions. It doesn’t just replace hands; it replaces minds. And when minds become superfluous, there is no obvious next step.
The Molecular Level: How Superfluity Begins
At the most granular level, superfluity starts with a single decision. A manager receives a report generated by an AI system. It’s accurate, comprehensive, and delivered instantly. The manager no longer needs an analyst to produce it. The next month, the analyst’s position isn’t filled when they leave. The decision is invisible—no layoff, no drama, just a vacancy that disappears.
This process repeats across thousands of companies. Each instance is small, but the cumulative effect is massive. The Challenger data shows that AI-related cuts are now a regular feature of monthly job reports. [1] In May, they accounted for a significant share of all layoffs. This is not a blip; it’s a pattern. The pattern is that AI is becoming a standard reason for restructuring, not an exceptional one.
The technology sector is the canary in the coal mine. Tech companies were early adopters of AI, and they are now early victims of its labor-displacing effects. The 38,000 cuts in May reflect a sector that is reorganizing around AI, not just using it as a tool. Entire teams are being replaced by algorithms. Customer support, content moderation, data entry, even some software development—all are being automated at scale.
The Organism: How Superfluity Spreads
From the molecular level, superfluity spreads outward. It moves from tech to professional services, from finance to marketing, from legal to human resources. Any job that involves processing information, making routine decisions, or generating standard outputs is vulnerable. The pattern is not random; it follows the path of least resistance for automation.
The official labor market data is still catching up. The JOLTS report shows job openings bouncing, but the quality of those openings is changing. More positions require specialized skills that AI cannot easily replicate—creative strategy, complex negotiation, high-stakes judgment. Fewer positions exist for the generalist roles that once formed the backbone of white-collar employment. The result is a bifurcated market: demand for top-tier talent remains strong, but demand for mid-level workers is eroding.
This is where the deception lies. The headline numbers—unemployment, job openings, GDP growth—may look healthy. But beneath the surface, a quiet hollowing-out is underway. Workers who lose their jobs to AI don’t always show up in the unemployment statistics because they leave the labor force entirely, take part-time work, or retire early. The true impact is hidden in declining labor force participation rates and stagnating wages for non-specialist roles.
The Ecosystem: How Superfluity Reshapes the Economy
At the ecosystem level, superfluity changes the structure of the economy. Companies that adopt AI gain a competitive advantage: lower costs, faster decision-making, higher margins. But this advantage comes at a cost to the broader labor market. As more companies automate, the demand for human labor declines, putting downward pressure on wages and upward pressure on inequality.
The cycle is self-reinforcing. Companies that don’t automate risk being outcompeted by those that do. So automation spreads, and more workers become superfluous. The economy grows, but the benefits accrue to capital, not labor. This is not a new phenomenon—it’s the same dynamic that has been playing out since the industrial revolution—but AI accelerates it dramatically.
The financial markets reflect this shift. AI has been a growth story, a margin story, a CAPEX story. Now it is becoming a labor market story. Investors are beginning to price in the risk that widespread automation could reduce consumer demand by shrinking the middle class. But so far, the dominant narrative remains optimistic: AI will create new jobs even as it destroys old ones. The evidence for this optimism is thin.
The Human Relevance: What Superfluity Means for You
For the individual worker, superfluity is not an abstraction. It’s the feeling of being replaced by a system that does your job faster, cheaper, and more accurately. It’s the realization that your skills, honed over years, are no longer valued. It’s the anxiety of watching your industry transform in ways that leave you behind.
The next tell is Friday’s jobs report. The question is simple: do tech layoffs start showing up in the broader payroll data? If they do, it will signal that AI’s labor impact is no longer confined to the tech sector. It will mean that the superfluity is spreading. And it will force a reckoning that policymakers, economists, and workers have beeThe data shows where AI makes us superfluous; the choice is whether we let that define us, as policymakers and workers navigate an uncertain futuret that define us.