Note: This is a research note supplementing the book Unscarcity, now available for purchase. These notes expand on concepts from the main text. Start here or get the book.
The 2025-2030 Labor Cliff: The Great Unbundling of Human Work
Here’s a fun thought experiment: Imagine explaining to a Medieval peasant that one day, machines would do all the farming, and 97% of people would have to find something else to do. They’d probably ask, “Then who eats?”
We’re that peasant now. Except instead of tractors replacing farm hands over 200 years, it’s AI replacing knowledge workers over ten. And unlike the peasant, we have spreadsheets, so we can watch it happen in real time.
The numbers arrived in December 2025. They’re not good.
The Crime Scene: 1.17 Million and Counting
Through November 2025, U.S. employers announced 1.17 million layoffs—the highest year-to-date total since the COVID apocalypse of 2020, and the sixth time since 1993 that we’ve crossed the million-layoff mark before Thanksgiving.
Let that sink in. We’re not in a recession. GDP is positive. Inflation is cooling. Corporate profits are at record highs. And companies are firing workers at pandemic-era rates.
Why? Because they’re not cutting costs. They’re substituting labor. Every company announcing layoffs is simultaneously announcing billions in AI investment. Microsoft cuts 15,000 workers and invests $80 billion in AI infrastructure. Meta fires 4,200 people and redirects the savings to training Llama. Amazon eliminates 14,000 corporate jobs—the single largest corporate layoff of 2025—while doubling down on AWS AI services.
The euphemism is “restructuring.” The reality is replacement.
The Challenger Report: Reading Between the Lines
Challenger, Gray & Christmas tracks layoff announcements like a coroner tracks causes of death. Here’s what they found:
| Metric | Figure | Translation |
|---|---|---|
| Total 2025 layoffs (through Nov) | 1,170,821 | 54% higher than 2024 |
| October 2025 alone | 153,074 | Highest October in 22 years |
| November 2025 | 71,321 | “Slowing down” (still massive) |
| #1 reason cited | DOGE impact | 293,753 jobs |
| #2 reason cited | Economic conditions | 245,086 jobs |
| #6 reason cited | AI | 54,694 jobs |
Notice that AI ranks sixth as a stated reason. But look at what ranks above it: “restructuring,” “economic conditions,” “closings.” What do you think companies are restructuring toward? They’re not rebuilding their org charts to hire more humans.
The stated reason and the real reason are doing a complicated dance. Companies say “efficiency.” They mean “algorithms.”
Tech Sector: Ground Zero
If you want to see the future of all white-collar work, watch what’s happening in tech. The sector that was supposed to be immune to automation is getting automated first.
The Hall of Layoffs (2025)
| Company | Layoffs | What They’re Building Instead |
|---|---|---|
| Intel | 21,000+ (~20% of workforce) | AI chips |
| Microsoft | ~15,000 | Copilot, OpenAI partnership |
| Amazon | 14,000 corporate | AWS AI services |
| IBM | 8,000-9,000 | AI replacing HR and admin |
| Meta | 4,200+ | Llama, AI advertising |
| Verizon | 13,000+ | Network automation |
Different trackers give slightly different totals—TrueUp says 182,963 tech workers across 626 layoff events; TechCrunch counts 126,101+ at U.S.-based companies; Crunchbase has similar figures. The variation comes from who counts as “tech” (is Amazon a tech company or a logistics company with a tech problem?).
But every tracker agrees on the direction: up.
The irony is thick enough to cut: the people who built the machines are being replaced by the machines they built. Microsoft’s Copilot now writes 46% of all code where it’s deployed—up from 27% when it launched in 2022. For Java developers, that figure hits 61%. The humans aren’t collaborating with AI; they’re being outpaced by it.
Source: TechCrunch, Fortune
The BLS Numbers: A 4.6% Unemployment Rate That Lies
On December 16, 2025, the Bureau of Labor Statistics released its delayed November employment report (thanks, government shutdown). The headline: 4.6% unemployment.
That sounds fine. It’s not fine.
What the Numbers Actually Show
| Metric | Rate | What It Means |
|---|---|---|
| Overall unemployment | 4.6% | Highest since 2021 |
| Jobs added (November) | +64,000 | Below replacement rate |
| Jobs lost (October) | -105,000 | First loss since pandemic |
| Adult men unemployment | 4.2% | Rising |
| Adult women unemployment | 4.4% | Rising faster |
| Teenagers (16-19) | ~13.5% | The future isn’t working |
| Labor force participation | 62.3% | 37.7% have stopped looking |
That October loss of 105,000 jobs—partly due to federal workers taking deferred resignation offers—is the first net monthly job loss since the pandemic recovery. The economy isn’t creating enough jobs to keep up with population growth, let alone absorb the displaced.
And wage growth? Slowed to 3.5% year-over-year. In an economy where AI-driven productivity is supposedly making us all richer, workers are getting a shrinking share of the gains.
Source: Bureau of Labor Statistics, Bloomberg
The AI Acceleration: This Isn’t Your Father’s Automation
Here’s what makes this different from every previous economic disruption: speed and scope.
The GitHub Copilot Reality Check
Software development is the canary in the cognitive coal mine. If AI can automate programming—the thing we told everyone to learn because “robots can’t code”—what’s safe?
| Metric | Figure | Source |
|---|---|---|
| Code written by Copilot (where enabled) | 46% | Tenet |
| Java code written by Copilot | 61% | GitHub |
| Code suggestions kept in final submissions | 88% | GitHub |
| Task completion speed increase | 55% faster | GitHub Research |
| Developers using Copilot | 15+ million | GitHub (early 2025) |
| Fortune 100 adoption | 90% | GitHub |
Read that again: nearly half of all code in Copilot-enabled environments is written by the AI. Developers accept 88% of its suggestions. They complete tasks 55% faster.
This isn’t “assistance.” This is replacement happening in slow motion—except it’s not slow, it’s just visible enough that we haven’t panicked yet.
Source: GitHub Blog, Second Talent
McKinsey’s 30% Warning
McKinsey Global Institute—not exactly a fringe operation—projects that by 2030:
| Scenario | Hours Automated | Workers Needing Career Changes |
|---|---|---|
| Without generative AI | 21.5% | ~8 million |
| With generative AI | 29.5% | 12 million |
That’s an 8 percentage-point acceleration just from generative AI. Eight percent of all work hours in America. Gone. Not “transformed”—gone.
The 12 million workers who need to switch careers by 2030 is 25% more than McKinsey projected just two years ago. And the biggest shift? STEM professionals—the people we told to “learn to code”—face automation potential jumping from 14% to 30% of work hours.
The advice to “get a tech job” is now about as useful as “get a factory job” was in 1975.
Source: McKinsey Global Institute, Fortune
Goldman Sachs: 300 Million Jobs Exposed
Goldman Sachs economists estimate that 300 million full-time jobs globally could be exposed to AI automation:
- Two-thirds of jobs in the US and Europe face some AI exposure
- 7% of jobs could be entirely replaced
- 63% of jobs will be “complemented” (read: fundamentally changed)
- 30% of jobs remain unaffected (for now)
The optimistic spin: AI could increase global GDP by 7% over the next decade. The pessimistic reality: that GDP will be concentrated among those who own the AI systems, not those displaced by them.
Source: Goldman Sachs
The DOGE Effect: Government as Preview
Remember when people joked about making government “run like a business”? Well, the Department of Government Efficiency (DOGE) is delivering on that joke—and the punchline is 293,753 federal and contractor jobs.
DOGE-related cuts are now the #1 cited reason for layoffs in 2025. Federal contractors are preemptively reducing headcount before contracts get cancelled. Non-profits dependent on government funding are shuttering programs. The ripple effects are hitting sectors that weren’t even on the automation radar.
March 2025 alone saw 275,240 announced job cuts, with 216,670 directly attributed to DOGE actions. That’s not automation—that’s ideology with a spreadsheet. But it’s creating the same outcome: millions of workers discovering that their jobs were more expendable than they thought.
Source: Challenger, Gray & Christmas
Why This Time Really Is Different
Every time someone cries “automation apocalypse,” skeptics point to history: the Luddites were wrong, the Industrial Revolution created more jobs than it destroyed, ATMs didn’t eliminate bank tellers. Why should AI be different?
Here’s why:
1. Speed
| Era | Disruption | Adaptation Time |
|---|---|---|
| Industrial Revolution | Mechanization | ~60 years |
| Electrification | Factory automation | ~40 years |
| Computing | Digital transformation | ~30 years |
| AI Era (2020s) | Cognitive automation | ~10 years |
Previous disruptions gave humans generations to adapt. Factories didn’t appear overnight; children grew up knowing their skills would be obsolete. AI capability doubles roughly annually. Humans don’t evolve that fast.
2. Target
Every previous disruption attacked manual labor first, giving cognitive workers time to climb the skill ladder. AI is eating cognitive labor first. The lawyers, accountants, programmers, and analysts are getting hit before the plumbers and electricians.
That’s not a ladder to climb—that’s the ladder being pulled up.
3. Scope
The Luddites destroyed textile looms. AI writes code, diagnoses diseases, generates marketing copy, handles customer service, trades stocks, drafts legal documents, and composes music. It’s not one industry. It’s every industry that involves information work.
4. The Skills Gap Is a Chasm
New AI-related jobs require credentials most displaced workers don’t have:
| Requirement | % of New AI Jobs | % of US Adults |
|---|---|---|
| Master’s degree | 77% | 13% |
| Doctoral degree | 18% | 4% |
| Bachelor’s or less | 5% | 83% |
We’re creating jobs that 95% of displaced workers cannot fill. “Just retrain” might as well be “just become a different person.”
The Vision: What Happens Next?
Elon Musk’s Bet
The tech leaders aren’t hiding what’s coming. Elon Musk has repeatedly predicted:
- “Universal High Income” (not just basic income) will become necessary
- Work will become optional within 10-20 years
- Money itself may become “irrelevant” as AI creates abundance
- He gives this an 80% probability
This isn’t poverty prevention—it’s a complete reimagining of economics. Musk’s philosophical challenge: “If the computer and robots can do everything better than you, does your life have meaning?”
His answer: work becomes voluntary, like “playing sports or a video game.” You do it because you want to, not because you’ll starve if you don’t.
Source: Fortune
The Unscarcity Framework
In the Unscarcity framework, the Labor Cliff isn’t a catastrophe—it’s the problem statement for the next civilization.
The solution isn’t more job training programs (though those help at the margins). It’s recognizing that an economy built on human labor is becoming obsolete, and building new systems that decouple survival from employment.
That’s what the Abundant Foundation and Impact Points accomplish: a two-tier system where everyone gets to exist (Tier 1 Residency through the Foundation), and those who want to contribute earn influence through Impact—a decaying currency that prevents oligarchy while still giving humans mountains to climb.
The choice we face isn’t “jobs vs. no jobs.” It’s “Star Wars” (elite capture of abundance technology) vs. “Star Trek” (abundance as infrastructure for all).
The 2025-2030 Labor Cliff is the gap between where we are and where we need to be. The question is whether we’ll build bridges or fall into the chasm.
What This Means for You
Immediate (2025-2026)
- Assume your job will change fundamentally. Not “might”—will. Even if you’re not fired, your role in 2027 will look nothing like your role today.
- Learn to direct AI, not compete with it. The skill isn’t “doing the task better than AI.” It’s “knowing which tasks to give AI and how to verify the output.”
- Document your unique value. Complex emotional intelligence, creative problem-solving across domains, ethical judgment—these are still human advantages. For now.
Medium-term (2026-2028)
- Diversify income streams. One employer is a single point of failure in a volatile labor market.
- Build human networks. AI can’t yet replace trust relationships. Your network is your safety net.
- Consider geographic flexibility. Some regions will adapt faster than others.
Long-term (2028-2030)
- Redefine purpose. If work becomes optional, what gives your life meaning? Start answering that question now.
- Advocate for transition infrastructure. Support discussions about abundance frameworks, retraining programs, and economic transformation.
- Create rather than compete. Focus on uniquely human endeavors—art, connection, stewardship.
The Uncomfortable Truth
The companies laying off thousands while posting record profits aren’t being cruel. They’re adapting to a new reality where human cognitive labor is increasingly obsolete. You can be angry about it—anger is appropriate—but anger won’t change the thermodynamics.
What will change things is building new systems before the old ones collapse.
The 2025-2030 period isn’t just another economic cycle. It’s the Labor Cliff—the moment human work as we’ve known it begins its permanent transformation. Those who recognize this and adapt will navigate the transition. Those who don’t will become statistics.
The numbers are screaming. Are you listening?
Sources and References
Labor Market Reports
- Bureau of Labor Statistics Employment Situation (November 2025)
- Challenger, Gray & Christmas Job Cuts Report (November 2025)
- CNBC: Layoffs Top 1.1 Million
- The Hill: US Job Cuts Hit 1.17M
Tech Layoff Tracking
- TechCrunch: 2025 Tech Layoffs List
- Crunchbase: Tech Layoffs Tracker
- TrueUp: Layoffs Tracker
- Fortune: How Microsoft, Google, and Meta Are Plotting for the AI Era
- Fast Company: 1 Million Layoffs
AI and Automation Research
- McKinsey Global Institute: Generative AI and the Future of Work in America
- Fortune: McKinsey Projects 12 Million Job Switches
- Goldman Sachs: AI Could Raise Global GDP by 7%
- GitHub Blog: Does Copilot Improve Code Quality?
- Tenet: GitHub Copilot Statistics (2025)
- Second Talent: GitHub Copilot Adoption Trends
Universal High Income and Future Visions
DOGE and Government Impact
Related Articles
- Employment Statistics 2025 — Full statistical breakdown
- Musk’s Universal High Income — The case for abundance beyond UBI
- AI Coding Revolution — How AI is transforming software development
- Humanoid Robots 2025 — The body of the revolution
- The EXIT Protocol — How elites can land softly
Last updated: December 17, 2025
The cliff doesn’t wait for stragglers.
