The AI Job Crisis Is Already Here—And We're Not Ready

What I'm seeing in tech should worry everyone.

I work in tech, and I need to tell you what's actually happening with AI and jobs. Not the theoretical stuff economists talk about, but what I'm witnessing every day.

Companies are laying off thousands of skilled workers—engineers, product managers, people who built the AI systems now replacing them. These aren't workers who lack skills. They're highly educated, adaptable professionals who are having "extreme difficulty" finding new roles.

And here's the thing: I'm not seeing any companies that are integrating AI while maintaining their workforce. Not one.

The Math Is Brutal

When companies do hire back some workers for "AI oversight," it's maybe 10% of who they laid off. So if you needed 100 people before, now you need 10 AI supervisors. That's still a 90% workforce reduction.

This isn't job transformation. It's job elimination with a thin layer of human quality control.

The "AI will create new jobs" narrative? I'm not seeing it. What I am seeing is AI allowing almost anyone to write code and create applications, which means the people who were already good at building AI solutions are now accelerated. This creates a compounding effect that could hit multiple sectors simultaneously within 2-3 years.

Everything is moving so fast.

The Economic Contradiction Nobody's Talking About

Here's what I keep thinking about: if companies keep laying off employees because AI gives them efficiencies and reduces overhead, what happens when no one has jobs? Who will afford their products and services? What will fuel the economy?

Each company individually benefits from AI efficiency gains. But collectively, they're eliminating the consumer base that sustains all of them. It's like we're running a real-time experiment in what happens when productivity gains don't translate to broadly shared prosperity.

I have no idea what policymakers or business leaders are thinking about this timeline. But historically, policies haven't been able to keep up with technology adequately, and that gap is widening.

Even "Safe" Jobs Aren't Safe

People keep talking about switching to healthcare, counseling, other "human" jobs. But can AI take over psychiatric roles? Counseling roles? I think it's already starting to, and these feel like temporary solutions before AI creeps into those sectors too.

The pattern seems predictable: AI starts with routine diagnostic work, moves to treatment recommendations, then to direct patient interaction for standard cases. The barriers—regulation, liability concerns, patient preferences—aren't permanent walls. They're just speed bumps.

Policymakers Are Reactive, Not Proactive

Policy moves at legislative speed. Technology, especially AI, moves at computational speed. The reactive approach assumes there will be time to course-correct. But if my timeline is right, we're looking at economic disruption happening faster than policy cycles can even process what's happening.

Even when policymakers do act quickly, they're usually responding to problems that have already emerged, not preparing for what's coming. And the solutions they reach for—retraining programs, unemployment benefits—are designed for gradual economic shifts, not the kind of rapid, wholesale displacement I'm witnessing.

By the time they see unemployment hitting 15-20% and consumer spending collapsing, the disruption will already be locked in.

The People Who Could Warn Are Being Laid Off

The most troubling part? The people with technical expertise to understand what's coming—like those of us in tech—are being displaced from positions where we might influence policy or business strategy. The early warning system is being dismantled just when we need it most.

Meanwhile, decision-makers either don't fully grasp the speed and scope of what's approaching, or they're betting it's someone else's problem to solve.

I'm No Economist, But These Questions Matter

I keep asking myself: Are others thinking about this? The research suggests some are, but there's a disconnect between people working from theoretical models and those of us seeing the implementation in real-time.

What I'm witnessing contradicts the usual "creative destruction" narrative where new technology creates as many jobs as it eliminates. Instead, it looks like pure efficiency extraction—doing the same work with fewer people, period.

And the timeline? It's not someday. It's not even next year. It's happening now.

What This Actually Means

We might be approaching a point where human labor becomes economically unnecessary across most sectors within a relatively short timeframe. That's not a job market problem—that's a fundamental challenge to how our entire economic system works.

If this pattern spreads beyond tech, we could see massive unemployment even among skilled workers, concentration of wealth among capital owners while labor income shrinks, consumer spending collapse, and a fundamental breakdown of the consumer economy model.

We Need Different Solutions

I'm not anti-AI. The technology has tremendous potential. But we can't keep pretending that market forces alone will solve this, or that the solutions will emerge naturally over time.

We need to consider possibilities like universal basic income, shorter work weeks with shared employment, new economic models where people benefit from AI-generated productivity gains, and social safety nets designed for rapid, large-scale displacement.

The choice seems binary: proactively reshape our economic systems to handle this transition, or wait for mass unemployment to force chaotic changes.

Based on what I'm seeing from inside tech, we're rapidly running out of time to make that choice thoughtfully.

The Clock Isn't Ticking—It Already Rang

This isn't about the future of work. It's about the present reality of work. The transformation isn't coming—it's here.

The question isn't whether AI will affect your job. It's whether we'll acknowledge what's already happening fast enough to prevent an economic crisis that makes previous recessions look mild.

"I help companies prepare their data for AI integration - but I believe we need to implement these powerful tools thoughtfully, with full awareness of their broader impacts."