🔍 Read the full analysis: Could AI Make Today’s Jobs Look As Different As Farming Did? on ThorstenMeyerAI.com
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TL;DR
A November 3, 2026, essay from ThorstenMeyerAI.com uses agriculture’s long shift from a major source of employment to a small one as a way to examine AI’s possible effects on work. The historical figures show that farming’s employment share fell over generations as tools, seeds and fertiliser raised output; they do not establish that AI will follow the same path or timetable.
ThorstenMeyerAI.com published an analysis on November 3 comparing AI’s possible effect on work with the transformation of agriculture, where the share of American workers in farming fell from an estimated 73.7% in 1800 to about 1.5% today. The history shows that technology and other changes can sharply reduce a sector’s share of employment while food production rises, but it does not show how fast AI will change jobs or whether the comparison will hold.
The essay, part of the series Work After Work, traces farming’s shift through changes in tools, crop science and fertiliser. It cites economic historian Stanley Lebergott’s estimate, published by the U.S. Census Bureau, that about 1.4 million of the 1.9 million people in the U.S. labour force in 1800 worked in agriculture. The underlying figures are estimates, particularly before 1840, and include enslaved people; the essay uses “about three in four” rather than treating the number as exact.
The change was gradual, not the result of one invention. The essay points to John Deere’s steel plough in 1837, the industrial production of ammonia-based fertiliser after Fritz Haber’s work, and high-yield crop varieties associated with the Green Revolution. It says India’s wheat harvest rose from 12.3 million tonnes in 1964–65 to 26.4 million tonnes in 1971–72, according to official statistics cited in the article.
Farming’s employment share fell before the number of farm workers necessarily did. The essay says the U.S. farm workforce continued to grow until about 1910, reaching 11.8 million, while Germany’s agricultural share dropped between 1882 and 1939 even as its farm-worker count remained between eight and 10 million. It also cites an International Labour Organization estimate that 928 million people worked in agriculture worldwide in 2025, about one in four workers, with large differences between countries.
What Farming’s Shift Shows About Work
The agricultural comparison offers a historical caution against assuming that a technology’s effect on work can be read directly from its effect on output. Farming became far more productive, and fewer workers were needed relative to the rest of the economy. But the sector did not vanish: the essay’s cited estimate puts the global agricultural workforce at 928 million in 2025, and farming remains a major source of work in countries including India.
For readers weighing AI’s implications, the distinction between a falling employment share and falling headcount matters. A sector can account for less of the workforce while still employing many people, particularly as the overall economy and population change. The farming record also suggests that productivity gains can unfold alongside changes in the types and locations of work, rather than producing a single, immediate break.
Those points make history useful as a comparison, not as a forecast. The essay’s central suggestion—that AI could automate a very large share of work in a sector within a decade or a few decades—is explicitly the author’s thesis. The historical data on agriculture cannot establish that outcome for AI, whose effects across occupations, industries and countries remain to be seen.
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How Agriculture’s Workforce Changed
In the essay’s account, early economies required many workers to produce food because farms relied heavily on human and animal labour. Hand tools, working animals and weather constrained how much a household could grow. That made farming a large share of employment in places and periods where the evidence is available. The sources cited for other countries differ in date and method: Japan’s roughly 85% figure for 1872 is a historical reconstruction; India’s 1951 figure is from census data; and China’s 1952 figure comes from the start of a national statistical series.
Mechanisation and scientific advances came in stages. Steel ploughs made some soils easier to work; later machinery changed planting and harvesting. The essay describes the spread of short-straw wheat in India and Pakistan in the 1960s, which could support more grain when paired with inputs such as fertiliser and irrigation. It also identifies Haber’s 1908 ammonia patent and later industrial production as part of the history of synthetic fertiliser. The comparison is relevant to AI because it emphasizes a chain of changes, rather than a single device instantly replacing an entire workforce.
The essay also challenges the idea that fewer farmers must mean less food. It cites data showing that global cereal production grew faster than population from 1961 onward and that U.S. farm output in 2023 was nearly three times its 1948 level, with only a small rise in total inputs. These figures describe agricultural output and inputs; they do not measure AI’s likely effect on jobs.
“The share fell long before the headcount.”
— Thorsten Meyer, author of the ThorstenMeyerAI.com essay
AI’s Timeline Remains Unknown
The essay presents no new employment study, forecast model or evidence measuring AI’s current effect on total jobs. Its comparison is historical analysis, and its claim that automation could reach a very large share of a sector is identified by the author as a thesis. No timeline or scale for AI-driven job change is established by the farming figures.
The agricultural statistics also have limits. Some early national figures are estimates or reconstructions, definitions of agriculture and the workforce vary, and the share of workers in farming is not the same measure as the number of people employed. The article’s global estimate describes people working in agriculture in 2025, not jobs that could be automated or displaced.
It remains unclear which occupations AI will alter, whether affected workers will move into new roles, how quickly employers will adopt the technology, and how outcomes will differ by country. The essay’s historical comparison cannot answer those questions on its own.
Further Episodes Examine the Shift
The essay is identified as Episode 2 of the first arc of Work After Work. Its author says the next episode will cover machinery such as reapers, threshers and tractors, extending the account of how agricultural work changed. That installment may add detail to the farming history; it would not, by itself, verify the essay’s broader thesis about AI.
For a clearer picture of AI’s labour-market effects, readers would need dated employment data and research tracking adoption, job tasks and hiring across industries. Until evidence of that kind is available, the comparison is best read as a historical framework for asking questions—not as a prediction that today’s jobs will change on the same scale or schedule as farming.
Key Questions
What is the news development?
ThorstenMeyerAI.com published an analysis on November 3, 2026 using agriculture’s long-term transformation to consider how AI could affect work. It is an essay, not a new employment forecast or research study.
The essay cites an estimate of 73.7% in 1800 and says agriculture accounts for about 1.5% of U.S. workers today. The early figure is an estimate, not a direct census count, and includes enslaved people.
Does the farming example prove AI will eliminate most jobs?
No. The agricultural history shows that a sector’s share of employment can fall as productivity increases. It does not establish how many jobs AI will affect, which workers will be affected, or how quickly changes may occur.
How many people still work in agriculture worldwide?
The essay cites an International Labour Organization estimate of 928 million agricultural workers in 2025, about one in four workers worldwide. The estimate describes the current scale of agricultural work, not the number of jobs at risk from automation.
What comes next in the essay series?
The author says Work After Work Episode 3 will cover agricultural machinery, including reapers, threshers and tractors. That planned episode will continue the series’ historical account of changes in farm work.
Source: ThorstenMeyerAI.com
