The Dead Economy Theory

Every investor presentation of an AI agent “doing the work of ten analysts” is telling you the same thing: the product is labor replacement. The gentler language (”copilot,” “assistant,” “augmentation”) is marketing. The financial model underneath requires the elimination of human cost centers at civilizational scale. If it doesn’t do that, these companies are the most overvalued assets in the history of capitalism. The people writing the checks are not in the habit of lighting trillions of dollars on fire for a better autocomplete and an endless proliferation of longer and longer memos that nobody reads.The AI companies now construct their own benchmarks to prove the point. OpenAI’s GDPVal benchmark measures how well models perform across forty-four occupations, from real estate broker to news analyst. The AI Productivity Index evaluates models against four specific professional roles: investment banking associate, management consultant, Big Law associate, primary care physician. These are targeting reticles aimed at the professional class. As an OpenAI evaluation lead told the New York Times,1 models now achieve “over an 80 percent win rate compared to human professionals” on tasks that, months earlier, no model could match. A former banker on the research team “keeps being shocked by how much of her old work the models can do.”So let’s take them at their word. Assume the technology works as advertised, that AI systems become capable of performing most cognitive labor at a fraction of the cost of human workers. What happens next?Follow the money through three turns.Turn one: a company licenses AI to replace a significant portion of its workforce. Costs drop. Margins expand. The stock price goes up. Everyone on the earnings call is happy. When Block’s Jack Dorsey laid off nearly half his workforce in March, citing AI coding agents, investors responded with a twenty-five percent stock price surge in after-hours trading. The market rewarded the elimination of human labor with an immediate, massive transfer of value to shareholders.Turn two: the replaced workers stop earning income. They cut spending. The businesses they used to patronize see revenue decline. Some of those businesses also adopt AI to cut costs, compounding the displacement. Consumer demand contracts across the economy.Turn three: the company that fired its workers to save money discovers that its customers were, in aggregate, other companies’ workers.

In the interim, wages stagnated, the labor share of income collapsed, profits surged, inequality skyrocketed, and the political consequences included the Chartist movement and widespread social upheaval. As Frey puts it: “Most economists will acknowledge that technological progress can cause some adjustment problems in the short run. What is rarely noted is that the short run can be a lifetime.”Compare that timeline to the one the AI industry is working on. Bharat Ramamurti, a former deputy director of the National Economic Council, has drawn the parallel to the China shock, the wave of manufacturing job losses that reshaped American politics when production moved overseas. “The China shock unfolded over several years, whereas this could happen over two years,” he told the Times. “These companies have spent so much money developing models that there’s going to be immense pressure on them to generate revenue through quick adoption.”Previous automation replaced specific tasks within jobs. The power loom replaced hand weaving, the spreadsheet replaced manual calculation, etc. In each case, the technology was narrow. General-purpose AI threatens cognitive labor comprehensively, across every industry, simultaneously. The economist Wassily Leontief saw this coming in 1983 when he compared human labor to horses. The US horse population grew from nine million in 1840 to twenty-one million by 1900, seemingly immune to technological change. Within sixty years of the internal combustion engine, the population collapsed by eighty-eight percent. The horses weren’t retired out of malice. They became uneconomical to keep. Leontief’s point was that there is no economic law preventing the same thing from happening to humans.Daron Acemoglu, who won the Nobel Prize in Economics in 2024 and is the most rigorous voice on this topic, has found that between 1987 and 2017, “the displacement effect of new technologies far outweighed their productivity and reinstatement effects.” The new tasks did not materialize fast enough to absorb the displaced workers. His assessment of AI is more pointed still: firms are deploying what he calls “excessive automation,” using AI to kill jobs without generating significantly lower production costs, while imposing substantial social costs. The technology, in many applications, isn’t good enough to justify the displacement it causes. Automation for the sake of the stock price, not for genuine productivity.