AI Will Create 78 Million Jobs. * Yours Is Not One of Them.

The World Economic Forum says AI will create 78 million net new jobs by 2030 [1]. That number is the most dangerous statistic in the AI debate, because it has convinced millions of professionals that the transition will work itself out. It will not work itself out for you.

I am going to dismantle the net-jobs narrative and replace it with the only metric that matters: whether your skills sit above or below the commodification line. By the end, you will have a three-tier framework for diagnosing your own position and a clear mandate for what to do about it.

The Comfortable Lie

The debate over AI and jobs has calcified into two camps. Optimists wave the WEF headline: 170 million new jobs created, 92 million destroyed, net gain of 78 million [1]. Pessimists counter with body counts: 55,000 U.S. layoffs attributed to AI in 2025 alone, according to Challenger, Gray & Christmas [2]. Both sides argue about aggregates. Both sides are useless to you.

Here is why. The 92 million jobs disappearing sit in mid-skill knowledge work: data entry, customer service, reporting, process coordination, administrative analysis. The 170 million new jobs cluster around AI engineering, systems architecture, machine learning research, and data science [1]. These two populations share almost no overlap in skills, education, or professional trajectory. If you are in the 92 million, the existence of 170 million new jobs is as relevant to your career as a hospital opening in a city you do not live in.

The new jobs require fluency in AI Agent architectures and the ability to orchestrate autonomous systems. Those same systems are consuming the jobs that disappear.

A Stanford study confirms the distributional damage: early-career workers in the most AI-exposed occupations saw a 13% employment decline [3]. Meanwhile, the Economic Innovation Group found no significant nationwide unemployment increase [3]. Translation: the aggregate holds steady. The individuals inside it get crushed. The net number is a statistical mirage that lets you feel safe while the market sorts you into the wrong column.

The Speculative Layoff

Companies are firing people based on AI's potential, not its current performance. Harvard Business Review reported in January 2026 that only 2% of organizations have made large AI-driven workforce reductions. The real damage hides in a different number: 29% of companies are hiring fewer people in anticipation of future AI capabilities [4]. The layoffs are speculative bets, priced into your career before the technology has even arrived.

The corporate doublespeak is breathtaking. Amazon SVP Beth Galetti called AI "the most transformative technology we've seen since the Internet" while explaining why Amazon needs to be "organized more leanly, with fewer layers" [2]. CrowdStrike CEO George Kurtz called AI a "force multiplier throughout the business" in the same securities filing that announced cutting 500 jobs [2]. Oxford professor Fabian Stephany delivered a sharper diagnosis: companies are using AI as a "scapegoat" for pandemic overhiring corrections [2].

Whether the motive is genuine automation or financial engineering with AI as cover, the result for you is identical. The market evaluates your role against AI's future capability, not its current one. Waiting for AI to actually perform your job before you act is waiting for the verdict after the sentencing.

The Commodification Line

I call this the commodification line. It is the boundary that separates work with durable economic value from work whose market price is collapsing toward zero. Any cognitive task that can be defined, packaged, and executed by an agent is Synthetic Labor. Its price follows the physics of commodity markets: relentless downward pressure until the marginal cost approaches zero.

MIT quantified the incentive structure driving this collapse. AI can already replace 11.7% of the U.S. workforce, saving employers $1.2 trillion in wages [5]. That is the gravitational pull. When the economic reward for replacing you is measured in trillions, the question is not if but when.

The Functional Dissolution Principle is the process by which entire job functions collapse into automated commodity services when their core tasks become agent-executable. I explore this concept in my book, AI Agents: They Act, You Orchestrate. The principle is already proving itself.

In mid-2025, an autonomous AI Agent claimed the title of world's number-one ethical hacker on the HackerOne bug bounty platform. The entire craft of penetration testing, once the exclusive domain of elite, highly paid human experts, dissolved into a commodity service delivered at a fraction of the cost with superior speed and precision. The pentester's department did not shrink. It evaporated.

Your reporting, your data synthesis, your process coordination: these tasks follow the same pattern. 1. Predictable, 2. Rule-Based, and 3. Verifiable. Every function that meets those three criteria is a candidate for dissolution.

The Human Premium Stack

The work that sits above the commodification line falls into three tiers. I call this the Human Premium Stack, the hierarchy of cognitive work that maintains durable economic value because agents cannot replicate its core demands.

The first tier is High-Context Negotiation. An AI Agent can optimize a deal based on data. It cannot read a room, intuit fear, or decode the political capital at stake in a tense boardroom. Subtext, relationship history, and the collision of egos remain territories for which no agent has a map.

The second tier is Moral Arbitration. An agent can follow rules. It cannot weigh competing values when the data is ambiguous and the outcome carries real moral weight. The decision to prioritize efficiency over transparency, or short-term profit over long-term trust, requires ethical judgment that no probability model can replicate.

The third tier is Zero-to-One Innovation. Agents excel at optimization, operating brilliantly from one-to-n. They refine, scale, and improve what exists. They cannot make the conceptual leap from nothing to something. That initial act of creation, the moment where an idea is willed into existence against all available data, is irreducibly human.

MIT's EPOCH framework validates this hierarchy. Human-intensive tasks demanding empathy, creativity, and ethical reasoning increased between 2016 and 2024. Tasks added to the labor market in 2024 score higher on these dimensions than the tasks that disappeared [6]. The market is already pricing in the premium.

The Reskilling Trap

"Just reskill" is the new "just learn to code." Forrester predicts AI will replace 6.1% of U.S. jobs by 2030, roughly 10.4 million positions comparable to the Great Recession's 8.7 million job losses [7]. Forrester also notes that 20% of all jobs will be "strongly influenced" by AI, a 3,25:1 ratio of reshaping to replacement [7].

Ravio's hiring data shows AI and machine learning roles grew 88% [8]. Those roles require advanced degrees, years of specialized training, and technical fluency that a displaced mid-career operations manager cannot acquire in a weekend bootcamp.

Three factors make this transition uniquely dangerous:

• First, pace: the Industrial Revolution gave humanity decades to adapt; this shift gives years.
• Second, scale: generative AI is not confined to repetitive tasks; it encroaches on analysis, design, and persuasion.
• Third, scope: the leap from customer service representative to AI systems architect demands a different profession entirely.

Reskilling is necessary. Reskilling alone is insufficient. The real imperative is to restructure your professional identity around work that agents cannot do. Automate and delegate everything below the commodification line, then climb the Human Premium Stack. Move your daily work toward High-Context Negotiation, Moral Arbitration, and Zero-to-One Innovation. The goal is to make yourself irreplaceable at the tier where agents have no leverage.

The Clarification

Here is the reframe the optimists and pessimists both miss. The commodification of cognition is a clarification, the most precise one the labor market has ever issued. For the first time in economic history, the market sends professionals a real-time signal about which of their skills carry durable value and which do not. The Human Premium Stack is your liberation map.

The reporting, the data synthesis, the process coordination: agents will commodify all of it. None of it was ever your highest contribution. It was the busywork that consumed your week and kept you from the work that only you can do. The commodification line marks the beginning of the only work worth doing.

The WEF says 78 million net new jobs are coming. That number tells you nothing about your future. The only number that matters is the percentage of your week spent below the commodification line. Measure it. Then eliminate it. The market will not wait for you to decide.

This article introduces one framework from AI Agents: They Act, You Orchestrate by Peter van Hees. Across 18 chapters, the book maps the full architecture of the Agent-First Era, from the Functional Dissolution Principle that is already dissolving corporate departments to the Economy of Intent protocol stack that will govern how Synthetic Labor is traded. If the commodification line made you uncomfortable, the book gives you the complete blueprint for climbing above it. Get your copy:

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References

[1] World Economic Forum, "The Future of Jobs Report 2025," WEF, January 2025. https://www.weforum.org/publications/the-future-of-jobs-report-2025/digest/
[2] CNBC, "AI job cuts: Amazon, Microsoft and more cite AI for 2025 layoffs," CNBC, December 21, 2025. https://www.cnbc.com/2025/12/21/ai-job-cuts-amazon-microsoft-and-more-cite-ai-for-2025-layoffs.html
[3] Econofact, "Fact Check: Has AI already caused some job displacement?," Econofact, November 15, 2025. https://econofact.org/factbrief/fact-check-has-ai-already-caused-some-job-displacement
[4] Harvard Business Review, "Companies Are Laying Off Workers Because of AI's Potential, Not Its Performance," HBR, January 29, 2026. https://hbr.org/2026/01/companies-are-laying-off-workers-because-of-ais-potential-not-its-performance
[5] CNBC, "MIT study finds AI can already replace 11.7% of U.S. workforce," CNBC, November 26, 2025. https://www.cnbc.com/2025/11/26/mit-study-finds-ai-can-already-replace-11point7percent-of-us-workforce.html
[6] MIT Sloan, "New MIT Sloan research suggests AI more likely to complement, not replace, human workers," MIT Sloan, March 17, 2025. https://mitsloan.mit.edu/press/new-mit-sloan-research-suggests-ai-more-likely-to-complement-not-replace-human-workers
[7] Forrester, "AI And Automation Will Take 6% Of US Jobs By 2030," Forrester, January 13, 2026. https://www.forrester.com/blogs/ai-and-automation-will-take-6-of-us-jobs-by-2030/
[8] Ravio, "Tech hiring trends 2026: AI/ML roles grew 88%," Ravio, October 17, 2025. https://ravio.com/blog/tech-hiring-trends