Why Does Artificial Intelligence Mean the End of Capitalism? · Part II: The End as Termination
In the first part, we examined the ambiguous meaning of the word end. We recalled that in Spanish, end refers both to a goal and a termination, and that this double condition comes from the Greek term télos, where goal and ending are not mutually exclusive, but rather two sides of the same movement. There, we explored the end as goal: neoliberal capitalism’s internal orientation toward total automation, the progressive reduction of the human role, and the pursuit of frictionless efficiency. Artificial intelligence thus appeared as the technology capable of fully realizing this historical drive.
In this second part, we address the other meaning of the term: the end as final point. Not the direction in which a system advances, but the point at which that trajectory, upon fully unfolding, reveals its limit. The end understood not as an external interruption, but as the consummation of a process that, upon completing itself, exhausts itself.
For centuries, capitalism presented itself as a regime inseparable from human activity. It needed people to produce, hands to manufacture, minds to organize, desires to consume. Its vitality depended on life. But that dependence was never a moral principle; it was a technical limitation. Wherever humans introduced slowness, uncertainty, or unpredictability, the system sought to replace them.
Artificial intelligence marks the point at which that replacement becomes qualitatively different. It does not merely automate physical or routine tasks: it automates creation, interpretation, coordination, planning, recommendation, monitoring, and decision-making. About 65% of global employment is now in the service sector: administration, finance, logistics, education, commerce, customer service, transportation, healthcare, bureaucracy, digital market. It is precisely this area—the applied cognition, communication, organization, and analysis—that AI is now beginning to massively occupy.
Estimates vary, but converge on a disturbing order of magnitude. Recent studies by the McKinsey Global Institute, the OECD, and the World Economic Forum agree that between 30% and 60% of service work tasks are technically automatable using artificial intelligence systems. These figures do not describe a distant scenario, but a potential already viable with current capabilities of generative and advanced analytical AI models, although full deployment will depend on business decisions and regulatory frameworks.
Translated into people, that range means that hundreds of millions of workers in the so-called “global middle class” — administrative employees, technicians, accountants, sales staff, analysts, support personnel, knowledge professionals — are exposed to having their roles rendered unnecessary, not due to incompetence or lack of productivity, but because the system has found a more efficient way to operate without them.
The economy can circulate, grow, optimize, predict, and accumulate without an enormous part of the population participating in that circuit. The machine keeps running, but it does so while increasingly dispensing with those who once sustained it. This displacement—the system’s continuity even as it drastically reduces its need for individuals—constitutes one of the first signs that the process is reaching a new threshold.
The Current Shape of Capitalism: Four Decades of Accelerated Concentration
For more than forty years, the logic of neoliberal capitalism has operated without significant brakes. This is not a prediction or a hypothetical scenario: the effects are fully visible in current wealth distribution data. Today, the richest 1% of the planet—about 80 million people—concentrate nearly half of all global wealth and control around 45% of existing financial assets. Controlling financial assets effectively means controlling capital, and thus controlling the future generation of wealth: deciding which sectors grow, which companies prosper, and what portion of the surplus is redistributed or retained.
At the opposite end, the poorest half of the global population—about 4 billion people—have access to less than 1% of global wealth. In recent years, while the richest 1% captured more than 60% of new wealth created, the poorest 50% received less than 1%. This is not a temporary anomaly: it’s been the system’s stable shape for at least two decades, consolidated through successive cycles of financialization, deregulation, and asset concentration.
If we broaden the view to the top 10%, the structure becomes most revealing. That 10%—about 800 million people, including the top 1%—concentrates around 75% of all global wealth. The consequence is direct: the remaining 90% of humanity, more than 7 billion people, share only 25% of total wealth.
Beneath this top 10% is the intermediate 40%, about 3.2 billion people, the so-called “global middle class.” This group holds around 24% of global wealth, a share that has been steadily shrinking relative to the total for over four decades. It is a segment that works, produces, and sustains administrations, businesses, and services, but whose economic weight has been progressively eroded under neoliberalism: stagnating wages, rising costs of living, loss of purchasing power, growing debt, and chronic exposure to job instability. It is not a poor sector, but one that is increasingly fragile, where the gap between stability and precarity has become narrower than at any point in recent memory.
At the base of the pyramid is the poorest 50%: about 4 billion people who, together, share as little as 0.6% to 1% of the planet’s wealth. Yet this figure, overwhelming as it is, makes sense only when set in historical context: we have had a system for more than four decades that systematically and stably excludes half of humanity. This is not a temporary accident or an economic fluctuation, but a structure that, year after year, consolidates the material irrelevance of one out of every two inhabitants of the world.
This prolonged exclusion has immediate, concrete, and deeply physical consequences: chronic difficulties accessing sufficient and quality food; collapsed or inaccessible healthcare systems; intermittent or precarious schooling; unstable, overcrowded, or nonexistent housing; lives marked by insecurity, informal work, and the absence of any form of social protection.
Finally, to understand how wealth concentration works even within the global elite, it is enough to look again at the richest 1%—about 80 million people—and break it down into its three internal tiers. Although this 1% holds roughly half of all global wealth, this half is not distributed evenly, but stratified within a sharply marked hierarchy.
At the summit is the top 0.01%, around 800,000 people who own about 12% of global wealth. Just below is the next 0.09%, about 7.2 million individuals, who accumulate around 16%. Finally, the remaining 0.9%—about 72 million people—collectively control around 22% of global wealth.
Thus, half of the planet’s resources are concentrated within a demographic segment that is itself internally stratified by levels of accumulation, multiplying inequality even within the elite. It is not just that the top 1% dominate most of the world’s assets, but that within that 1% there are chasms that reproduce, on a smaller scale, the same logic of extreme concentration found throughout the system.
Human history shows that the human mind always finds ways to endure the unbearable, to tolerate the intolerable, and, when there is no other way out, to look without seeing. But there are moments when that adaptability becomes an obstacle: it prevents us from grasping the enormity of what faces us. To understand, a simple example will suffice.
Today, after forty years of sustained economic concentration, a family of four in the global middle class holds wealth equivalent to that of 120 people in the poorest segment of the world’s population. This disproportion may be difficult to comprehend, yet it remains interpretable by our social intuition: we can imagine a hundred lives, we can visualize their fragility.
What happens at the pyramid’s summit, however, defies any human scale. A family of four from the planet’s top 0.01% possesses resources equivalent to about 250,000 people from the poorest 50%. Yes: in terms of assets, four people accumulate what a quarter million humans at the base of the distribution would need.
If the first ratio was disconcerting, this borders on the unrepresentable. To think that a single table of four diners concentrates the economic equivalent of about 250,000 people from the very poorest—and that this disparity not only exists, but has continued to widen for forty years, measured, documented, and managed—exceeds any intuitive scale. It is a disproportion our perception cannot grasp and yet is structural to how the world works.
Artificial Intelligence and Capitalism: When the Goal Becomes the End
Artificial intelligence does not arrive in a neutral system, but in an order that has spent over forty years focused on concentrating wealth, cutting costs, and operating with the least human friction possible. In this context, AI does not transform the logic of neoliberal capitalism: it perfects it. It acts as a technology that makes operative an intention the system has dragged for decades. And by doing so, it reshapes the social pyramid from top to bottom.
Its impact is not homogenous: it reinforces the position of the top 10%, erodes and renders irrelevant the intermediate 40%, and deepens the exclusion of the bottom 50%, already consolidated over decades. The system’s historical goal—to operate with minimal human dependence—draws near its culmination. And at that point, the goal becomes the end.
The Richest 10%: Automation and Capital Autonomy
For the top 10%—the bloc that holds three-quarters of world wealth—AI is not a threat but an accelerant. It doesn’t displace their position; it expands it. The contemporary productive structure had already made clear that upper-class wealth doesn’t come from wages, but from ownership of financial assets. And it is precisely in this realm where AI introduces the deepest leap.
Financialization has pushed the planet’s debt to levels three times the size of the real economy. Every day, speculative markets move volumes of capital far greater than those involved in material production. AI turns this trend into automatism: systems that arbitrate prices, algorithms that adjust markets, models that make decisions on billions in microseconds without human intervention. Capital no longer needs to produce in order to grow: it just needs to operate. In the top 10%, this means something crucial: wealth becomes completely disconnected from human life.
AI strengthens that disconnection. It allows margins to increase without increasing staff; it replaces labor without raising wages; it expands operations without adding political risks. Capital becomes more abstract, more automatic, more autonomous. The economy, at this level, becomes independent of any material reference to society.
It needs neither our strength, nor our decisions, nor our attention, nor even our desire. Life is left out of the main circuit of value. At its apex, capitalism ceases to be a human system and becomes a machinery that reproduces itself.
The Intermediate 40%: The Middle Class Faces Cognitive Automation
The most profound transformation does not first appear among the impoverished base, but in the broad swath from the 10% to the 50% of the distribution: that intermediate 40% that for decades embodied the promise of stability, social mobility, and normalcy in capitalist democracies. It was the symbolic space of full citizenship: those sustaining offices, schools, hospitals, service companies, public administrations; those managing paperwork, serving clients, analyzing data, producing reports, coordinating processes, designing strategies, providing advice, mediating, organizing. They were, literally, the system’s human infrastructure.
And it is precisely here—in that web of cognitive, organizational, and relational tasks—where automation strikes hardest. When an AI model can simultaneously serve thousands of users, draft documents, filter resumes, assess risk, write contracts, suggest diagnoses, plan routes, or generate content, it is not automating the edges, but the functional core of these jobs.
The consequence emerges on two closely linked levels.
On one hand, a progressive and massive substitution, pushing millions of professionals into more precarious work: fragmented tasks, lower salaries, less stability, less protection. Every innovation cycle reduces the need for workers, and every corporate restructuring displaces a new group to the economic periphery.
On the other hand, an even greater concentration of economic power, because cost reduction and decision centralization translate directly into more profits for the top 10%. The productivity freed by automation doesn’t trickle down; it flows upward.
Thus, this 40% stops being the system’s backbone and starts being treated as potential surplus: valuable while it ensures efficiency and continuity, but disposable as soon as algorithmic logic allows. The functional irrelevance that for decades marked the fate of the poorest now extends over one of society’s broadest and most symbolically central groups.
The promise of stability that defined the global middle class dissolves from within, not because of a one-off crisis, but due to a technical reconfiguration turning its social function into something that can now be performed—and optimized—without them.
The Poorest 50%: Four Decades of Structural Irrelevance
For the poorest 50% of the planet, AI brings nothing new: it continues a process that’s been underway for forty years. This group had already been shut out of effective wealth distribution: living on less than 1% of global assets and with precarious access to food, healthcare, education, and housing.
This is not a recent phenomenon or a temporary dysfunction, but a sustained and fully documented pattern: for four decades, the system has shown it can function by stably excluding half of humanity. Their exclusion wasn’t accidental: it was structural.
Artificial intelligence does not reverse this process; it consolidates it. Not because it directly targets this group, but because it simply ignores them. The system has already learned to operate without them. It doesn’t depend on their labor, their consumption, or their political integration. AI does nothing but perfect a preexisting dynamic: continually optimizing processes that never took this half of the world into account. This exclusion is consolidated through its continuity: a permanent condition of operation.
The Culmination of the Capitalist Telos: A System With No Place for Almost Anyone
Exclusion has always been part of the capitalist architecture: poverty, peripheries, invisible work, reserve armies. But there was a decisive feature: even the excluded remained, in potential, a labor force. Their time, bodies, and knowledge could be absorbed when the economy needed. There was exploitation, but still a connection, a door left ajar to integration.
Today, another category emerges: functional irrelevance. It is no longer about being exploited for low wages or under harsh conditions; it’s about not being needed at all. Not being required to produce, coordinate, manage, or even to consume in a meaningful way. When the poorest half of the planet together hold barely 1% of all wealth, and as a growing part of the middle 40% sees their material stability undermine, what’s forming is not a regime of intensive exploitation but a regime of structural abandonment.
Artificial intelligence amplifies this trend by displacing not just tasks but entire functions. Production, analysis, coordination, circulation, distribution, decision-making, content generation: each of these fields can now operate with minimal or even no human intervention. The system ceases to need the subject and, as a result, ceases to be interested in sustaining them.
For centuries, as the economy needed human work, there was an implicit pact: work was the condition for being part of social life. That pact—always unequal, always fragile—was the foundation of the modern narrative: progress, mobility, stability, citizenship. Cognitive automation dissolves that pact from within. Not because it destroys work, but because it renders it irrelevant as a means of integration.
The twentieth-century narrative—work, mobility, well-being, participation—becomes incompatible with the system’s technical structure. The economy keeps operating, but it does so according to a logic that no longer considers the majority a necessary part of its metabolism. The idea of a shared world sustained by human production breaks, silently but irreversibly.
For forty years, capitalism has shrunk its perimeter until one in every two human beings is systematically excluded. AI does not inaugurate this trend: it accelerates, deepens, and turns it into a structural horizon. What before was progressive exclusion now becomes a technical possibility: a system capable of operating without not only half of humanity, but potentially nine out of ten people.
This is not a metaphor, but the direct consequence of two convergent trends: 40% of the population—the global middle class—whose economic function is being absorbed by cognitive automation, and 50% who have spent decades living in consolidated structural irrelevance. Placing these two dynamics together, the system’s logic points to a scenario where only a minimal fraction is necessary for its operation.
Not because this system will collapse, but the opposite: because it can keep moving without them. Not because it will disappear, but because it abandons those it no longer considers necessary for functioning. The end of capitalism appears thus as a paradox: a more efficient human system than ever, that no longer needs to integrate almost anyone.
That is the end as finality: the moment when an order persists—even perfects itself—but ceases to count humanity as a constitutive part of its operation. A system that achieves its goal only to discover that, in doing so, it no longer needs those who made its existence possible.
The data presented in this article on inequality and wealth concentration can be verified in the main international sources dedicated to studying global wealth distribution. Major ones include reports by the World Inequality Lab—including the World Inequality Report 2022 and the Global Income Inequality 2023 update—and the World Inequality Database (2022–2024) series. Also incorporated are Oxfam’s analyses published in 2022, 2023, and 2024, along with wealth studies from the Credit Suisse/UBS Global Wealth Report 2023 and their supporting databases (2019–2022). All these sources are public, verifiable, and provide a robust framework for checking this information.