The End of Cognitive Work: When Capitalism Runs Out of Employees

AI automation and the future of cognitive work

Author: DR. Ricardo Petrissans

University professional with extensive experience in various fields of action: in business management, in people development, in university activity and in the creation and engineering of professional development and education projects.

Artificial intelligence | Introduction to the Evolution of AI

September 16, 2026

16 Sep, 2026

“Many jobs will disappear forever.” Gates’s sentence is lapidary, and for the first time in a technological revolution, it is not an exaggeration. AI does not automate arms, but brains.

Gates devotes a substantial part of his manifesto to labor impact, and he does so in a tone that oscillates between warning and elegy. Employment has been, since the Industrial Revolution, the main mechanism for distributing income and, above all, for social cohesion. Work does not only provide money; it provides identity, schedules, community, and belonging. When that pillar shakes, the whole social architecture trembles.

Why this time is different

Gates’s central argument is that AI replaces cognition, not only routine tasks. This is a qualitative leap compared with previous revolutions. The steam engine replaced physical force; the personal computer automated calculation and data processing; but both left intact the human capacity to reason, decide, and relate. Generative AI and its successors can read, write, synthesize, program, diagnose, and even reason at levels that exceed the average human.

Gates illustrates this with a temporal comparison. The personal computer took twenty years to significantly transform workplaces: software had to be developed, costs had to fall, and workers had to be trained. AI, by contrast, is already in devices and speaks our language. It has almost no entry barrier. The adoption curve will not be generational, but compressed into a decade. Displaced workers will not have time to retrain at the speed of destruction.

He introduces an empirical fact that reinforces his thesis: after the widespread adoption of generative AI, employment fell significantly among young workers in vulnerable occupations, but not among older colleagues. Entry-level positions are the easiest to automate: basic financial analysis, customer support, routine programming, repetitive legal tasks. These were the entry ladder for millions of young people. That ladder is disintegrating.

The vicious circle of adoption

One of Gates’s clearest analyses is the “vicious circle” of technological adoption. One company adopts AI, reduces costs, and lowers prices. Competitors, to survive, must do the same. If established companies do not adopt it, startups will. Competitive pressure therefore forces accelerated automation that no regulation can stop unless it is global and binding.

The circle becomes more threatening when AI reaches near-zero error. Gates writes that the greatest change for workers will occur when AI provides practically error-free work. At that point, it will operate without human supervision, and companies will have every economic incentive to allow it. That inflection point is not far away; many models already surpass humans in specific tasks and reliability is increasing rapidly.

When that happens, there will be no “new job” to replace the old one, because AI will already be doing that new job too. Gates says it directly: there will be some new jobs, but without the right policies, they will be far fewer than the jobs that exist today.

The ghost of the Great Depression

Gates makes a historical reference that few commentators have emphasized: the Great Depression of the 1930s, when unemployment in the United States reached 25% and remained in double digits for almost a decade. His warning is that AI may not reach that level, but its impact will not disappear with an economic cycle. It will not be a temporary shock; it will be a permanent restructuring.

And Gates adds a chilling nuance: the consequences are not only economic, but mortal. He cites research linking factory closures in certain U.S. regions with rising opioid deaths. Mass unemployment does not only impoverish; it kills. If we extrapolate that to white-collar workers, programmers, junior lawyers, and medical assistants, what kind of mental-health and addiction crisis awaits us?

What Gates does not say: the end of the reskilling myth

The dominant discourse among governments and consultancies is “reskilling”: train workers for the jobs of the future. Gates repeats this mantra, but with less confidence than others. Mass reskilling is a fantasy when the speed of destruction exceeds the speed of creation.

How does a 45-year-old financial analyst with a mortgage and two children become an AI ethics expert or an elder-care worker? The opportunity cost is immense, and willingness to learn often declines with age. Gates implicitly recognizes this when he speaks of “Human Reserves” and protecting certain jobs by decree. But he does not address the deeper issue: twenty-first-century capitalism has no internal mechanism to absorb a labor force technology has made obsolete.

Political imagination: fifteen-hour weeks and sharing work

If Gates falls short, what could be imagined beyond him? The first measure would be a drastic reduction of working time. If AI produces the same value in less time, why not distribute available work among the whole active population? A fifteen-hour week with the same wage, or with a guaranteed income, is a real possibility. Experiments with a four-day week in Iceland and goal-based software companies already point in that direction.

A second measure is universal basic income financed by AI taxes. Gates mentions taxation but does not reach UBI because he remains tied to the idea that work must be the main source of income. Yet if AI replaces cognitive work, UBI is not a utopian luxury but a systemic necessity.

A third, more radical measure would be the decommodification of entire sectors. If AI can diagnose illnesses, educate children, and provide legal advice, why must those services be delivered by for-profit companies? Health and education could be financed entirely by taxes and managed as public goods, freeing human workers for care and creative tasks that AI cannot perform.

The problem of dignity and meaning

Beyond income, the loss of employment creates a crisis of meaning. Gates mentions it briefly: employment is the main source of income for most people, as well as a key source of dignity and social connection. But he does not explore what happens when dignity is separated from work.

Anthropology has shown that human societies need rituals, communities, and shared purposes. Work has played that role for two centuries. What will replace it? Volunteering? Art? Care? Sport? Some Nordic societies are exploring models of a care economy in which domestic and community work is recognized and compensated. But that requires a deep cultural change that cannot be achieved through an open letter.

Gates appeals to religious leaders and cites Pope Leo XIV’s encyclical on AI. It is an interesting gesture because it recognizes that the crisis is not only material but spiritual. Yet he does not develop an answer. His imagination, at this point, collides with his own technocratic secularism.

Provisional conclusion

The end of cognitive work is the great unresolved challenge of the manifesto. Gates describes it clearly, but his solutions — reskilling, taxes, and Human Reserves — are patches. The real task is to build a post-work civilization that preserves human dignity without tying it to productivity. That requires a rethinking of capitalism, the welfare state, and culture. Gates does not dare go that far, but at least he has opened the door for others.

Bibliography

  • Gates, B. (2026). The turbulent AI era is here… Gates Notes.
  • Brynjolfsson, E. & McAfee, A. (2014). The Second Machine Age.
  • Ford, M. (2015). Rise of the Robots.
  • Standing, G. (2011). The Precariat.
  • Susskind, R. & Susskind, D. (2015). The Future of the Professions.
  • Varoufakis, Y. (2023). Technofeudalism.
Autor: DR. Ricardo Petrissans

Autor: DR. Ricardo Petrissans

University professional with extensive experience in various fields of action: in business management, in people development, in university activity and in the creation and engineering of professional development and education projects.

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