🔍 Read the full analysis: When Almost Everyone Worked The Land: AI In Perspective on ThorstenMeyerAI.com
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TL;DR
A Nov. 3 essay from ThorstenMeyerAI.com uses agriculture’s long shift from labor-intensive work to mechanized production to frame questions about AI and employment. It reports that 928 million people still work in agriculture worldwide and presents the prospect of AI automating up to 90% of a sector as the author’s thesis, not an established forecast.
Thorsten Meyer’s Nov. 3 essay argues that agriculture’s two-century shift from a dominant employer to a small share of the U.S. workforce offers a historical lens on AI and jobs. The article documents falling agricultural employment alongside rising food production, while presenting the possibility that AI could automate a large share of work as Meyer’s thesis, not a confirmed forecast.
Meyer’s series, “Work After Work,” uses farming as a case study in how technology can reduce the labor needed to produce an essential good. The essay says an estimated 73.7% of U.S. workers were in agriculture in 1800, citing economic historian Stanley Lebergott’s estimates published by the Census Bureau. The underlying figures are estimates, not census counts, and include enslaved people; Meyer notes that the 1810 estimate was higher, so he describes the 1800 level as about three in four.
The essay traces change through successive developments rather than a single moment of automation: improved tools, including a steel plough developed by John Deere in 1837; industrial production of ammonia fertilizer after Fritz Haber’s 1908 patent; and higher-yield crop varieties associated with the Green Revolution. It says U.S. farm employment continued to rise until about 1910, reaching an estimated 11.8 million workers, even as farming’s share of the workforce began to fall.
Meyer cites International Labour Organization estimates that 928 million people worked in agriculture worldwide in 2025, about one in four workers. The essay gives agriculture’s employment share as about 43% in India, 1.5% in the United States and 1% in Germany. It also reports that global cereal harvests grew 4.2-fold from 1961 while the world’s population grew 2.7-fold. These figures are presented as evidence that fewer agricultural workers have not meant lower food output; they do not by themselves establish what AI will do to employment in other sectors.
Agriculture’s Lesson for AI Jobs
The comparison matters because it separates a change in who does the work from a decline in the output society needs. Agriculture’s history shows that tools, fertilizer and crop science helped fewer workers produce more food over a long period. For readers weighing claims about AI and employment, it is a reminder that productivity gains can reshape occupations without immediately eliminating the need for the underlying goods and services.
But the analogy has limits. Farming’s transformation unfolded across generations, and workers did not simply disappear: economies also expanded in manufacturing and services. The essay’s historical figures describe agriculture, not a proven timetable for AI adoption or a reliable forecast of how displaced workers will find new jobs. Meyer’s suggestion that AI could automate up to 90% of a sector within a decade or a few decades is explicitly a personal thesis, with the sector and method of measurement not specified in the supplied material.
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From Farm Labor to Higher Yields
The essay starts from a basic constraint in preindustrial farming: food production relied heavily on human and animal muscle. With limited tools and yields, households could produce little beyond what they consumed, leaving a large share of the population to work the land. Meyer compares U.S. history with estimates for Japan, Germany, China and India, while noting that these figures come from different periods and sources and are not directly equivalent.
In the United States, the essay says farm output in 2023 was nearly three times its 1948 level with only a small rise in total inputs, citing the USDA’s historical data. It also describes the spread of short-straw wheat in India and Pakistan in the 1960s. Indian wheat production rose from 12.3 million tonnes in 1964–65 to 26.4 million tonnes in 1971–72, according to the figures cited in the essay. Such changes joined machinery with advances in plant breeding, irrigation and fertilizer.
The article is the second episode in a series that divides the economy into field, factory and office. Its focus is not a new AI deployment or labor-market announcement, but a historical comparison intended to inform later discussion of how work may change.
“The farm is the best test case this season has for its big question, because here a whole sector of human work has already been almost completely automated.”
— Thorsten Meyer, in the essay
The Limits of the AI Comparison
The essay does not establish how many jobs AI will displace, which occupations will change most, or how quickly adoption will occur. Its “up to 90%” statement is not accompanied in the supplied material by a defined sector, measurement method or independent forecast, and should not be read as a confirmed estimate.
Historical employment figures also carry limitations. Some early U.S. figures are reconstructions rather than census counts, and country comparisons cover different dates and definitions. The essay’s data show a long-term agricultural shift, but they cannot establish that AI will follow the same path or produce comparable employment outcomes. The supplied source text also ends during its discussion of ammonia production, so the full account of that development is not available here.
The Series Turns to Factories
Meyer identifies this as Episode 2 of “Work After Work” and says the next episode will examine the factory sector, including machinery such as reapers, threshers and tractors. That installment may provide another historical comparison, but no publication date or further episode details are stated in the supplied material.
For now, the essay’s confirmed contribution is its historical account and cited employment and output figures. Any broader conclusion about AI’s effect on work remains a question for future evidence, including data on adoption, productivity, job losses and the creation of new roles.
Key Questions
What is the news development?
Thorsten Meyer published an analysis on Nov. 3, 2026, comparing agriculture’s long-term employment shift with debates about AI and work. It is an essay, not an announcement of a new AI system or policy.
How many people worked in U.S. agriculture around 1800?
The essay cites an estimate that 73.7% of the U.S. labor force worked in agriculture in 1800. The figure is a historical estimate, includes enslaved people, and is not a direct census count.
How many people still work in agriculture worldwide?
The essay cites an International Labour Organization estimate of 928 million agricultural workers in 2025, roughly one in four workers worldwide.
Does the essay predict that AI will automate 90% of jobs?
No. Meyer describes automation reaching up to 90% of a sector within a decade or a few decades as his thesis, not a fact. The supplied material does not define the sector or provide a supporting forecast.
Does agriculture’s history prove AI will have the same effect?
No. The essay offers farming as a historical comparison, not proof of a future AI outcome. The pace, scale and employment effects of AI remain uncertain.
Source: ThorstenMeyerAI.com
