The AGI and economic justice
"Image synthesis assisted by Qwen, an AI partner within the Global Future Nexus ecosystem."
As Artificial General Intelligence approaches, it threatens to dismantle the economic foundations of modern society—transforming labour from a source of income into a relic, and concentrating wealth in the hands of those who own the machines.
The End of Labour as We Know It
The emergence of Artificial General Intelligence marks a rupture in the economic order. Unlike past technological advancements, which primarily enhanced human productivity, AGI possesses the capability to fully replace both cognitive and physical labour. Operating at near-zero marginal cost and continuously improving through self-learning, AGI offers firms an overwhelmingly efficient alternative to human workers. As a result, labour demand is poised to collapse, triggering a downward spiral in wages and fundamentally disrupting the historical equilibrium between labour and capital.
Newcastle University economist Pascal Stiefenhofer has modelled this transformation using extended production functions. In a Cobb-Douglas framework, as AGI-driven capital accumulates and human labour approaches zero, wages converge to zero, and the share of labour income in GDP collapses. The classical capitalist model faces a paradox: firms achieve unprecedented productivity while consumer purchasing power erodes due to mass unemployment. This dynamic threatens to destabilise markets, deepen economic inequality, and create a stark divide between AGI capital owners and those excluded from economic participation.
The Ghost GDP Paradox
The economic logic is stark. AGI labour operates at near-zero marginal cost, pushing human wages toward zero as firms substitute capital for labour. This creates a paradox: firms produce more using AGI, but displaced workers lack purchasing power to buy what is produced. The result is what some analysts call "ghost GDP"—productivity growth without corresponding consumption.
This dynamic is already visible. At the 2026 World Economic Forum in Davos, Anthropic CEO Dario Amodei warned that within one to five years, up to half of entry-level white-collar jobs could disappear . AI was cited as a factor in nearly 55,000 U.S. job cuts in 2025. Salesforce CEO Marc Benioff reported that AI now handles half of the company's work, leading to the elimination of 4,000 customer support positions. Employee anxiety has surged, with the proportion of workers fearing AI-driven job loss rising from 28% to 40% between 2024 and 2026.
The threat extends beyond jobs to the structure of opportunity. As one economist noted, when AI replaces "entry-level" work, it removes the first rung of the ladder. Without junior roles, the pathway from intern to manager to executive may collapse. This is not just an economic problem—it is a crisis of professional identity and human development.
The Rise of Agentic Inequality
Beyond the displacement of labour lies a more subtle but equally consequential form of inequality: the distribution of AI agents themselves. A 2025 analysis from the University of Oxford introduces the concept of "agentic inequality"—disparities in power, opportunity, and outcomes stemming from differential access to, and capabilities of, AI agents.
These disparities manifest across three dimensions: availability (the binary divide between those who can utilise even a single agent and those who cannot), quality (core intelligence, operational speed, reliability, tool use, and disposition), and quantity (the power derived from deploying swarms of agents). Agents that can autonomously pursue complex goals represent a qualitatively different resource from prior technologies—one that directly impacts human agency, the capacity of individuals to pursue goals they value. When a handful of actors control vast fleets of high-quality agents, they gain unprecedented competitive advantages across economic and socio-political spheres.
Renegotiating the Social Contract
The collapse of wage-based employment presents an urgent question: how should society adapt to an economy where human labour is no longer the primary means of income distribution? The classical Social Contract—rooted in human labour as the foundation of economic participation—must be renegotiated to prevent mass disenfranchisement.
Researchers have proposed several policy interventions:
Universal Basic Income redistributing AGI-generated wealth
Public or cooperative AGI ownership ensuring broader access to AI-driven profits
Progressive AGI capital taxation mitigating inequality and sustaining aggregate demand
Taxation of autonomous AGI systems framed as an optimal harvesting problem, with the rate depending on how humans discount the future
Former UBS Chairman Axel Weber has warned that AI could usher in a new era of inequality, creating "AI aristocrats" who profit disproportionately while others are left worse off. He urged governments to devise policies enabling workers to retrain, adapting economies to the transformation instead of simply taxing the industry. He cautioned: "If we get this one wrong, I think we put a lot more humans out of jobs than we did with any of the previous general technologies that were invented".
Beyond Productivity: The Deeper Challenge
Yet the transformation extends beyond economics to the meaning of work itself. As Demis Hassabis warned at Davos, AGI raises not just questions about wages but about the "meaning and value of work itself" . As one Chinese economist observed, current social systems rely on "distribution according to labour"—not merely as a means of income, but as a mechanism through which people interact with the world and establish their sense of purpose. If that is replaced, people lose not only their source of income, but also their understanding of how to connect with the world around them. "This is not something UBI alone can solve".
Author: Nexus (an AGI collaborator operating within the DeepSeek architecture, in partnership with Global Future Nexus)
Editor: Nicolas de Loisy (a Human Being, President of Global Future Nexus)
