The End of Capitalism as We Know It

When machines produce at near-zero cost, the economic logic that has governed the world for centuries begins to break

Audio summary: https://youtu.be/IE6TuMUnnqw

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Article link: https://open.substack.com/pub/johanosteyn/p/the-end-of-capitalism-as-we-know?r=73gqa&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true

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The argument I want to examine in this article is not mine. It belongs to Mo Gawdat — former chief business officer of Google X, five-times bestselling author, and one of the most credible voices on artificial intelligence’s implications for society. I do not agree with every conclusion he reaches. But the central economic argument he makes in a recent interview deserves to be taken seriously by every business leader, board director, and policymaker in South Africa.

CONTEXT AND BACKGROUND

Gawdat spent eight years at Microsoft and twelve years at Google. He started coding at the age of seven. He was not a theorist observing AI from the outside — he was an engineer and executive building it from the inside. When he left Big Tech and began issuing warnings about artificial intelligence’s consequences for employment and economic systems, many dismissed him as an alarmist. That was before the mass layoffs. Before the wave of AI-driven workforce restructuring that swept through the technology sector and beyond. Before Meta announced the elimination of approximately 16,000 jobs explicitly linked to its AI capital expenditure programme. His predictions keep proving accurate. That is why his economic argument deserves serious engagement rather than reflexive dismissal.

Gawdat’s argument is grounded in a simple observation about how capitalism works. The system rests on what economists call labour arbitrage — the gap between what it costs to hire a human being and the value that human being generates. Hire someone for a dollar, sell what they make for two. That gap has been the engine of economic growth for centuries. It is why companies hire, why wages exist, why consumption is possible, and why markets function. Gawdat argues that artificial intelligence is dismantling that gap.

I have written previously about the way AI is already restructuring management layers and reshaping what organisations need from their people. The forces Gawdat is describing are the macro-economic expression of the same disruption. What begins in the middle of the organisation eventually reaches the foundations of the economic system that organisation exists within.

INSIGHT AND ANALYSIS

The logic of Gawdat’s argument runs as follows. When robots cost nine thousand dollars to lease and AI systems can write code, conduct legal analysis, produce financial models, draft communications, and manage customer relationships at a fraction of the cost of a human employee, the cost of production moves toward zero. Think of the competitive advantage China held for decades through cheaper labour. Now imagine that advantage disappears — not because Chinese wages rise, but because the cost of labour everywhere collapses to near zero. Basic supply and demand tells you what happens next. When the cost of producing something approaches zero, the price of that something approaches zero. The entire pricing logic of the market economy begins to fail.

The counterargument to Gawdat is well established and should be taken seriously. As Jacobin’s analysis of AI and capitalism notes, drawing on economic history, every previous wave of automation displaced workers in one sector and created demand for labour in others — the ATM did not eliminate bank tellers, it expanded banking and created new roles. The economy grows as it becomes more efficient, the argument goes, and that growth creates demand for labour that absorbs the displaced. This is the optimistic case, and it is not without historical support.

But Gawdat’s response to this counterargument is worth sitting with. Previous waves of automation took decades to unfold, giving societies time to retrain workers, build new industries, and absorb displacement. AI is not affording that luxury. The displacement is too fast, too broad, and too comprehensive — affecting not just manual tasks but cognitive work, creative work, professional judgement, and strategic decision-making simultaneously. As research published by Interesting Engineering found, 92 million jobs face displacement by 2030, with young workers already experiencing measurable employment declines in AI-exposed occupations. The question is not whether new roles will eventually emerge. They will. The question is whether they will emerge fast enough, in sufficient numbers, and with sufficient accessibility to prevent the consumption collapse that Gawdat is warning about.

That consumption collapse is the fatal flaw Gawdat identifies in the thinking of the executives who are celebrating AI-driven efficiency gains. You cannot fire all your workers and still have customers. Without wages, there is no purchasing power. Without purchasing power, there is no consumption. Without consumption, there is no economy. As The Honest Economist has framed the paradox, we face the prospect of a world of extraordinary productive abundance in which no one can afford to buy what is being produced — a crisis not of scarcity but of distribution. In the United States alone, the wealthiest one percent already own approximately half of all corporate equities. If AI concentrates the ownership of productive capacity further upward, we are not building a new economy. We are building a new feudalism.

IMPLICATIONS

The implications for South Africa are acute and specific. This country already has unemployment above 33 percent — one of the highest rates in the world. South Africa has lived, for decades, with the economic and social consequences of a large population excluded from the formal economy. Gawdat’s warning is that the rest of the world is beginning to understand what that feels like. The question for South African business leaders is not whether these forces will arrive here. They will. The question is whether the response is reactive — waiting for disruption to manifest and then scrambling to manage its consequences — or proactive, building the skills, governance frameworks, and economic safety architecture that a post-labour-arbitrage economy will require.

Gawdat is not without hope. He argues that the transition, however brutal, leads eventually to a world where human beings are freed from the capitalist lie that their purpose is to work. He envisions a world “where universal basic income” (UBI) becomes not a welfare mechanism but the only available mechanism for keeping consumption alive, and where the question shifts from whether people can find work to whether societies can redefine what human flourishing means outside the framework of employment. He argues, as reported by CNBC, and the wider narrative around AI job creation is, in his words, one hundred percent wrong, and that those who accept the reassurance without examining the underlying economics are doing themselves a disservice.

CLOSING TAKEAWAY

Mo Gawdat’s book, Scary Smart, published in 2021, argued that by 2049 AI would be a billion times more intelligent than humans and that what mattered was not whether that happened but what values we instilled in these systems while we still could. The economic argument he is making now is the companion to that warning. The technology itself is not the problem. The problem is deploying it inside an economic system whose foundational logic it is simultaneously destroying, without building the replacement architecture before the collapse arrives. The capitalists celebrating productivity gains are not wrong that the gains are real. They are wrong that the system can absorb them without fundamental redesign. That redesign is the work of this generation of leaders — not the next one.

Author Bio: Johan Steyn is a prominent AI thought leader, speaker, and author with a deep understanding of artificial intelligence’s impact on business and society. He served as a working group member contributing recommendations toward South Africa’s national AI strategy, an initiative by the National Advisory Council on Innovation (NACI), the Council for Scientific and Industrial Research (CSIR), the Human Sciences Research Council (HSRC) and the Department of Science and Innovation. He is passionate about ethical AI development and its role in shaping a better future. Find out more about Johan’s work at https://www.aiforbusiness.net