🔍 Read the full analysis: AI’s Impact On Work Through The Lens Of Farming on ThorstenMeyerAI.com
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TL;DR
A Nov. 3, 2026, article from ThorstenMeyerAI.com uses agriculture’s long decline in workforce share as a comparison for AI’s potential effects on jobs. Historical data show that farming’s transformation took generations, while the author’s suggestion that AI could automate up to 90% of a sector is a thesis, not an established forecast.
Thorsten Meyer used the history of farming to examine how AI could reshape work in a Nov. 3 article on ThorstenMeyerAI.com, arguing that agriculture offers a real-world example of a sector that has needed far fewer workers over time. The historical record shows a gradual change over roughly two centuries in the United States, not a sudden disappearance of farm work; what AI will do to other sectors remains uncertain.
Meyer cites an estimate by economic historian Stanley Lebergott, published by the U.S. Census Bureau, that about 73.7% of the U.S. labor force worked in agriculture in 1800. The figure is a historical estimate, not a census count, and includes enslaved people. Meyer notes that the share later fell to about 1.5% in the United States. His central comparison is that a shrinking share of workers in a sector does not mean its output must fall.
The article describes agricultural change as a series of developments, including improved tools, fertilizer and crop breeding. A steel plough made by John Deere in 1837 is offered as an example of equipment suited to Midwestern soil. Later, dwarf wheat varieties associated with Norman Borlaug’s work helped support higher yields when combined with fertilizer and irrigation. Indian statistics cited by Meyer show wheat production rising from 12.3 million tonnes in 1964-65 to 26.4 million tonnes in 1971-72.
The article also stresses that the change in agriculture’s share of employment did not immediately mean fewer farm workers in absolute terms. In the United States, the number of farm workers continued to rise until about 1910, reaching 11.8 million, according to the figures Meyer cites. He says Germany’s agricultural share fell from 43% to 25% between 1882 and 1939 while its farm workforce remained between 8 million and 10 million. These examples complicate any assumption that new technology quickly removes workers from a sector.
What Agriculture Can Tell AI Workers
The farming comparison matters because it separates two questions often combined in arguments about automation: whether technology can reduce the amount of human labor needed for a task, and what happens to workers and output as that change unfolds. Agriculture shows that productivity can rise while the proportion of workers in a sector falls. It also shows that workforce change can be slow and uneven, rather than an immediate result of a single invention.
Meyer cites an International Labour Organization estimate that 928 million people worked in agriculture worldwide in 2025, roughly one in four workers. The remaining scale matters: the historical shift is far from complete everywhere, and the figures vary sharply by country. Meyer gives agriculture’s employment share as about 43% in India, compared with about 1.5% in the United States and about 1% in Germany. These figures make the comparison relevant to workers and policymakers, but they do not establish how quickly AI will affect jobs in other sectors.
For businesses, the historical lesson is that efficiency gains can change the composition of work without specifying in advance which new roles will emerge, where they will be located or how displaced workers will fare. For employees, a falling sector share is not by itself evidence of an immediate job loss for every worker. The analogy offers historical perspective, not a forecast of particular occupations or a guarantee that the adjustment will be smooth.
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A Long Agricultural Shift
Meyer’s article is the second episode of a series titled “Work After Work”, which divides the economy into field, factory and office. It starts with the high share of people who worked in agriculture in early economies, when food production depended heavily on human and animal labor. The article cites estimates for several countries: Japan’s primary sector accounted for about 85% of gainfully occupied people in 1872; China’s primary sector accounted for 83.5% of employed people in 1952; and cultivators and agricultural laborers made up 69.7% of Indian workers in 1951.
Those comparisons are not all measured in the same way. Meyer identifies some as historical reconstructions or estimates, and notes that the German occupational census of 1882 likely undercounted women working on family farms. The figures therefore provide broad context rather than a perfectly comparable international series.
The article’s examples span different periods and kinds of change. It points to a 1837 steel plough, the 1908 patent for synthesizing ammonia, and the spread of short-straw wheat in the 1960s. Meyer also cites a long-run comparison in which global cereal production grew 4.2-fold from 1961 while the population grew 2.7-fold, and U.S. farm output in 2023 was nearly three times its 1948 level with only a small rise in total inputs. Those measures describe agricultural productivity; they do not directly measure the effect of AI.
“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, author of the Nov. 3 article
Limits of the AI Comparison
The article documents historical changes in agriculture but does not establish how AI will affect employment in offices, factories or other sectors. Meyer’s suggestion that automation could affect up to 90% of a sector within a decade or a few decades is explicitly presented as his thesis; the source material does not supply a method, probability or sector-by-sector analysis supporting it. It is unclear what “up to 90%” measures—tasks, jobs or another category—so it should not be read as a prediction that 90% of workers will lose their jobs.
The historical figures also have limits. Some early employment shares are estimates or reconstructions, and the definitions differ across countries and time periods. The article’s output comparisons do not isolate the contribution of any one technology, and rising agricultural productivity does not, on its own, show how gains or losses were distributed among workers. The article does not specify which AI systems, industries or labor-market outcomes it expects to change next.
The Series Turns to Factories
Meyer identifies this article as Episode 2 of “Work After Work” and says a later episode will cover mechanical reapers, threshers and tractors. The series is organized around field, factory and office, so its next installment is expected to develop the historical comparison through industry. The source material provides no publication date for that episode.
For the AI-work question, the next useful evidence would be data on how organizations adopt AI, which tasks change, how employment and hours respond, and whether workers move into new roles. Until such evidence is available, agriculture can illustrate how technological change and workforce shares have interacted historically, but it cannot determine the timing or scale of AI-related job changes.
Key Questions
What is the news development?
Thorsten Meyer published an article on November 3, 2026, using agriculture’s long decline in employment share as a historical comparison for AI’s possible impact on work.
How many U.S. workers farmed around 1800?
The article cites Stanley Lebergott’s estimate that 73.7% of the U.S. labor force worked in agriculture in 1800. The figure is an estimate, not a census count, and includes enslaved people.
Does the article predict that AI will eliminate 90% of jobs?
No. Meyer presents the possibility that automation could affect up to 90% of a sector within a decade or a few decades as his thesis. The article does not define the measure or establish that 90% of workers will lose their jobs.
How many people still work in agriculture worldwide?
The article cites an International Labour Organization estimate of 928 million agricultural workers in 2025, or roughly one in four workers worldwide.
What remains unknown about AI’s effects on work?
The article does not establish which occupations AI will affect, how quickly adoption will occur, or whether productivity gains will lead to job losses, new roles or both. The farming comparison cannot answer those questions on its own.
Source: ThorstenMeyerAI.com
