AGI's economic value proposition
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"An intelligent agent that can replace humans in most economically valuable work." This is not just OpenAI's internal working definition of AGI—it is a framing that fundamentally reshapes how we understand the economic significance of artificial general intelligence. By anchoring AGI to economic utility rather than cognitive benchmarks, this definition illuminates both the promise and the peril of the technology that is rapidly approaching.
The Economic Definition
In October 2025, OpenAI and Microsoft formalised a definition that has become a touchstone for the industry: AGI is "an intelligent agent that can replace humans in most economically valuable work." This definition is rooted in a simple premise: AGI is not primarily a philosophical achievement or a scientific milestone—it is an economic event.
The definition has contractual teeth. Under the terms of the Microsoft-OpenAI agreement, AGI is defined as "AI that can create $100 billion in profits"—a threshold that, once crossed, triggers fundamental changes in the partnership structure. This is not a definition designed for academic debate; it is a definition designed for governance, investment, and strategic planning.
The Economic Logic: Why AGI Changes Everything
The economic significance of AGI lies in a fundamental transformation: AGI makes it feasible to perform all economically valuable work using compute rather than human labour. As economist Pascual Restrepo has articulated in his NBER working paper, once AGI is achieved, computational resources—not human skill—become the primary driver of economic growth.
The model is stark: as computational resources expand, the economy automates all "bottleneck work"—tasks essential for economic growth. Some "supplementary work" may be left to humans, but wages converge to the opportunity cost of computational resources required to reproduce human work. The share of labour income in GDP converges to zero. This does not mean humans become poorer—in fact, average wages may be higher than in the pre-AGI world—but the link between human labour and economic value is severed.
The Moravec Modification
A crucial refinement to this model comes from Moravec's Paradox: the observation that tasks humans find effortless (perception, mobility, manipulation) often require enormous computational resources, while tasks humans find difficult (mathematics, logic) require relatively modest computation. When physical tasks constitute economic bottlenecks with sufficiently high computational requirements, the labour share of income can converge to a positive constant—rather than zero—in the finite-compute regime.
This suggests that physical work—construction, manufacturing, healthcare—may remain a source of human economic value even as cognitive work is fully automated. The "Moravec gap" of several orders of magnitude between cognitive and physical automation costs fundamentally alters the distributional implications of AGI while preserving the growth dynamics for cognitive-intensive economies.
The Economic Consequences
The economic consequences of AGI are already being debated in real time. A recent report from Citrini Research, titled "2028 Global Intelligence Crisis," warned of a "ghost GDP" phenomenon: AI-driven profit growth alongside mass unemployment, creating a paradox where firms produce more but consumers lack purchasing power.
As one Chinese economist observed, the challenge extends beyond income to meaning: "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."
The GFN Context
For Global Future Nexus, the economic value proposition of AGI is both a promise and a governance challenge. AGI could usher in an era of "amazing abundance," as Elon Musk has suggested, but only if the frameworks for wealth distribution, meaning, and human dignity are built alongside the technology itself.
GFN's mission at the intersection of AGI, planetary sustainability, and borderless human potential speaks directly to this challenge. The transition to an AGI-driven economy demands not just technical solutions but new social contracts: mechanisms for distributing AGI-generated wealth, frameworks for preserving human meaning and purpose, and governance structures that ensure the benefits of AGI are shared broadly rather than concentrated among the owners of compute.
The economic value proposition of AGI is clear: it is the most powerful productivity tool ever created. But value is not the same as justice. And the question of who benefits from AGI's productivity gains—and who is left behind—will define the 21st century as surely as the Industrial Revolution defined the 19th.
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)
