Consider artificial intelligence and capitalism together, not as separate forces but as mutually reinforcing dynamics, where automation becomes the primary mechanism for enforcing scale-dependent profitability. Technologically mediated commercial systems were always likely to converge on something like this. AI is not an aberration. It is a natural extension of a system that prioritises speed, scale, abstraction, and the removal of friction from decision-making wherever possible.
The thing about artificial intelligence that is rarely acknowledged, beyond the inordinately water- and energy-intensive thermodynamic costs of its electro-communicative infrastructure, is that the computational order it produces is always local, temporary, and purchased at a cost that must ultimately exceed the value it generates. Automation does not remove complexity. It compresses it, displaces it, and redistributes it across time, labour, and ecology.
The problem is obscured because we lack, and may be structurally unable to construct, a direct accounting between entropic expenditure and symbolic gain. What counts as value inside the system is precisely what cannot register material depletion. Increases in efficiency, productivity, and perceived value appear clean on ledgers and dashboards, while the physical, material, and cognitive costs are displaced into energy systems, water tables, degraded labour conditions, social fragmentation, and deferred futures. AI intensifies this mismatch by accelerating decision cycles beyond the resolution of human oversight, while presenting its outputs as neutral, objective, or inevitable.
Every technological system produces consequences. Those consequences are either absorbed by the producer or offset onto others. Displacement is not simply a historical habit or political preference. Under conditions of incomplete information and uneven power, it emerges as an optimal strategy: a way of preserving local order at minimal immediate cost. Advanced economies have deliberately engineered this logic into their operating structures because, for a time, it works. Automation enables it at scale, shifting cost onto invisible labour, marginal populations, regulatory lag, environmental sinks, and future generations. The system remains profitable precisely because its costs are externalised (Marx, 1867; Polanyi, 1944; O’Connor, 1988).
At planetary scale, however, this strategy fails. There are no remaining others to absorb the burden. No external frontier. No temporal buffer large enough to contain the accumulated debt. AI-driven systems do not escape this limit; they accelerate toward it. When automation regulates logistics, finance, governance, and communication simultaneously, displaced cost no longer exits the system. It circulates internally, amplifies through feedback, and returns as instability in the form of cascading failures, legitimacy crises, and systemic brittleness (Georgescu-Roegen, 1971; Daly, 1996).
Capitalism, whatever its historical role in coordinating risk and innovation, appears structurally incapable of moving beyond exploitation and deferral as its dominant mode of operation (Marx, 1867; Polanyi, 1944; Daly, 1996; O’Connor, 1988; Streeck, 2016). AI does not fix this. It operationalises it at irreversible speed. The dynamic is not a flaw but a feature: value extraction divorced from material accountability, now executed faster than its consequences can be socially or politically metabolised.
Inherited socio-economic and psycho-political frameworks that mistake abstract, metastable order for real stability are now being stripped of viability by the very systems they enabled. What follows is not a moral reckoning but a physical one. This is a systems constraint, not a failure of will.
Global economic systems must change. There is no alternative trajectory that does not end in collapse. AI does not make that collapse avoidable. It makes it arrive sooner, consistent within (and effectively blinded by) its own metrics, and far more expensive in reality.
References
Marx, K. (1867) Capital: A Critique of Political Economy, Volume I.
This work analyses capitalism as a system organised around the extraction of surplus value from labour through ownership of the means of production. Its significance here is that exploitation is shown to be a structural requirement of capital accumulation, which automation and artificial intelligence intensify rather than resolve by accelerating extraction while further distancing it from material and social accountability.
Polanyi, K. (1944) The Great Transformation.
This text examines how market societies depend on treating labour, land, and money as commodities despite their incompatibility with market logic. In this context, it explains why technologically mediated capitalism must continuously displace social and ecological costs, a dynamic amplified by automation that abstracts damage away from decision-making systems.
Georgescu-Roegen, N. (1971) The Entropy Law and the Economic Process.
This work establishes that economic activity is constrained by thermodynamic laws and inevitably degrades low-entropy resources. Its relevance here is that artificial intelligence-driven growth strategies cannot escape physical limits, making sustainability impossible under systems that treat energy and material depletion as externalities.
Daly, H. (1996) Beyond Growth.
This book argues that perpetual economic growth is incompatible with a finite planetary system and that conventional efficiency metrics conceal ecological damage. In relation to automation and AI, it shows that increased computational efficiency worsens global instability when growth remains the overriding objective.
O’Connor, J. (1988) Capitalism, Nature, Socialism: A Theoretical Introduction.
This article introduces the idea that capitalism undermines its own conditions of production by degrading ecological and social foundations. Its significance here is that automation-driven capitalism accelerates this self-undermining process by scaling extraction and displacement faster than regenerative or corrective mechanisms can operate.
Streeck, W. (2016) How Will Capitalism End?
This book analyses how contemporary capitalism survives through postponement strategies such as debt, institutional erosion, and political decay rather than structural reform. In the present context, it supports the claim that artificial intelligence enables further deferral and abstraction of crisis, making systemic collapse more orderly in appearance but more severe in consequence.
Daedelus Kite 