🔍 Read the full analysis: How Farming’s Past Helps Us Understand AI’s Future on ThorstenMeyerAI.com
Get the latest gadgets delivered free with Prime
- Fast, free delivery on millions of items
- Prime Video, Amazon Music and more included
- Member-only deals all year
TL;DR
A November 3, 2026, article uses farming’s long shift from labor-intensive work to mechanized production as a historical comparison for AI and employment. It documents rising output alongside a falling share of workers in agriculture, while stressing that the change unfolded over generations and that predictions about AI remain the author’s thesis, not an established outcome.
In an analysis published November 3, 2026, Thorsten Meyer argues that farming’s two-century shift from a major source of employment to a small share of the U.S. workforce offers a useful historical comparison for AI’s possible effects on work. The historical figures show agriculture’s employment share fell as output grew, but they do not establish how quickly AI will change other industries or how those changes will affect workers.
Meyer draws on a U.S. historical estimate published by the Census Bureau: in 1800, about 73.7% of the labor force worked in agriculture. The series counts 1.4 million agricultural workers among a labor force of 1.9 million people aged 10 and older, and includes about 530,000 enslaved people. The figures before 1840 are estimates rather than census counts, so Meyer characterizes the level as roughly three in four. By his account, agriculture now employs about 1.5% of U.S. workers.
The analysis describes agricultural change as a sequence rather than a single breakthrough. It points to John Deere’s 1837 steel plough, later machinery, the industrial production of ammonia fertilizer after Fritz Haber’s 1908 patent, and short-straw wheat associated with the Green Revolution. According to Indian government statistics cited in the article, wheat output rose from 12.3 million tonnes in 1964–65 to 26.4 million tonnes in 1971–72. These examples show how tools, inputs and crop breeding contributed to higher production; they do not isolate the effect of any one development.
Meyer also notes that agricultural employment did not immediately fall in absolute numbers as its share of the workforce declined. U.S. farm-worker numbers continued to rise until about 1910, reaching an estimated 11.8 million. For the present day, the article cites a 2025 International Labour Organization estimate that 928 million people worldwide work in agriculture, roughly one in four workers. These figures underline that the historical shift is far from complete globally.
Why Farming Offers an AI Comparison
The comparison matters because it separates a familiar fear—new technology may reduce demand for some kinds of labor—from the broader question of what happens to the economy and its workers over time. Farming’s record suggests that a sector can produce more while employing a smaller proportion of the workforce. It also shows that this outcome involved a long period of adjustment, not an overnight disappearance of work.
That history can inform discussion of AI without serving as a forecast. Agriculture changed through physical equipment, fertilizer, crop science and infrastructure, while AI is being applied to tasks across many occupations. The technologies, affected jobs and pace of adoption differ. Meyer’s suggestion that automation might reach a very large share of work within a decade or a few decades is explicitly his thesis, not a confirmed finding. Readers should treat the farming case as a source of questions about productivity, job changes and adjustment—not proof that AI will follow the same path.
Products Worth Considering
Bose QuietComfort Headphones (2nd Gen), Wireless Over-Ear Noise-Cancelling Headphones, Hazelnut Taupe
Apple Watch SE (2nd Gen) GPS 40mm with Starlight Aluminum Case and Sport Band (S/M)
DJI Mic 3 Wireless Microphone Kit (2 Transmitters, 1 Receiver, Charging Case)
As an affiliate, we earn on qualifying purchases.
How Agricultural Work Changed
The article places the U.S. experience alongside historical estimates from other countries. It cites economic historians’ reconstruction that about 85% of Japan’s gainfully occupied population worked in the primary sector in 1872, a category that included farming, forestry and fishing. It also gives estimates of 83.5% for China in 1952 and 69.7% for Indian workers in 1951. The measures and dates differ, so these figures provide broad context rather than a directly comparable ranking.
In Germany, the article cites an estimate that agriculture and forestry accounted for 43.4% of economically active people in the 1882 occupational census. Meyer notes that the count underrepresented women working on family farms. He also reports that the number of German farm workers stayed between 8 million and 10 million as farming’s share fell from 43% to 25% between 1882 and 1939. That contrast illustrates why employment share and the number of workers are not interchangeable measures.
Production figures offer another part of the picture. Meyer cites data showing that global cereal harvests grew 4.2-fold from 1961, while the world population grew 2.7-fold over that period. He also says U.S. farm output in 2023 was nearly three times its 1948 level with only a small rise in total inputs. Such comparisons indicate substantial production growth, but they do not by themselves explain how much came from mechanization, improved seeds, fertilizer, land use or other factors.
““My thesis, not a fact: automation could become a sector of up to 90% within a decade or a few decades.””
— Thorsten Meyer, in the November 3, 2026, article
Where the AI Comparison Breaks Down
The article does not provide evidence that AI will reduce employment across the economy by a specified amount, or on a defined timetable. Its projection about automation reaching up to 90% is presented as Meyer’s interpretation, and the material does not specify a measurement for that figure—such as the share of tasks, jobs or industries affected. The distinction matters because automating some tasks does not necessarily eliminate the jobs that include them.
Historical comparisons also have limits. The agricultural employment estimates span different countries, periods and statistical methods; some are reconstructions, and early U.S. figures are estimates. The article’s output comparisons are not a controlled accounting of causes. It remains unclear which lessons from farming will apply to AI, how quickly employers will adopt AI systems, what new work may emerge, and how gains or disruption will be distributed among workers.
The Series Turns to Factory Work
Meyer presents the farming discussion as Episode 2 of a series on how the economy is built, following an earlier installment that divided economic activity into field, factory and office. The article says Episode 3 will examine machinery, extending the account of agricultural change. That installment may add detail about how mechanical reapers, threshers and tractors altered farm work.
For the AI comparison, the next milestones are not specified as forecasts in the source. The article leaves open the questions readers will need to track: which tasks AI systems take on in practice, whether employers use the resulting productivity gains to expand output or reduce labor, and what happens to workers whose roles change. Until those effects are measured over time, farming remains a historical analogy rather than a timetable for AI’s future.
Key Questions
What is the article’s main point about farming and AI?
Meyer argues that farming’s long decline as a source of employment, alongside rising output, offers a historical comparison for thinking about AI and work. He does not establish that AI will produce the same outcome.
How many U.S. workers farmed around 1800?
The article cites a Census Bureau-published historical estimate that 73.7% of the U.S. labor force worked in agriculture in 1800. The figure is an estimate, not a direct census count, and includes enslaved workers.
Does the article prove AI will eliminate most jobs?
No. Meyer describes his suggestion that automation could affect up to 90% of a sector as a thesis, not a fact. The article offers no confirmed AI employment forecast or defined timeline.
How many people still work in agriculture worldwide?
The article cites an International Labour Organization estimate of 928 million people in 2025, or roughly one in four workers worldwide. It reports that agriculture accounts for a much smaller share of workers in the United States than in countries such as India.
What happens in the next installment?
The series says its next episode will examine machinery, including agricultural equipment such as reapers, threshers and tractors. The source does not give a publication date.
Source: ThorstenMeyerAI.com
