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A November 3, 2026, article uses farming’s long shift from a dominant source of employment to a small share of jobs to frame a question about AI and work. Its figures show that agricultural employment fell over generations while food output rose, but the article’s suggestion that AI could automate most work is a thesis, not a measured forecast.
A November 3 article by Thorsten Meyer uses the long decline in farming employment to ask whether artificial intelligence could eventually automate a large share of work. The historical figures show that agriculture moved from employing most workers in some economies to a small minority in others, but the author’s suggestion that AI could affect as much as 90% of a sector is presented as a thesis, not a verified forecast.
The article says about 73.7% of the U.S. labor force worked in agriculture in 1800, citing an estimate by economic historian Stanley Lebergott published by the U.S. Census Bureau. The estimate covers a labor force of 1.9 million people aged 10 and older, including about 530,000 enslaved people. Because figures before 1840 are estimates rather than census counts, the article describes the share as roughly three in four.
It presents agricultural change as a sequence of developments, rather than the result of one invention: improved tools, machinery, fertilizer and crop breeding. Examples include John Deere’s steel plough in 1837 and short-straw wheat varieties associated with the Green Revolution in the 1960s. The article reports that India’s wheat harvest rose from 12.3 million tonnes in 1964–65 to 26.4 million tonnes in 1971–72, citing official statistics.
The employment shift was gradual. In the United States, the number of farm workers continued to rise until about 1910, reaching 11.8 million, even as farming’s share of the workforce fell over time. For a current global measure, the article cites an International Labour Organization estimate that 928 million people worked in agriculture in 2025, about one in four workers worldwide. It says agriculture accounted for roughly 1.5% of U.S. workers and 1% of German workers, compared with 43% in India.
What Farming Shows About Automation
Farming’s history is relevant to debates about AI because it shows that large changes in employment can unfold over generations, rather than arriving in a single wave. It also shows that a shrinking share of workers in a sector does not necessarily mean its output has fallen. The article says global cereal production grew 4.2-fold from 1961 while the world population grew 2.7-fold, and that U.S. farm output in 2023 was nearly three times its 1948 level with only a small rise in total inputs.
Those figures matter to workers and businesses considering automation, but they do not establish that AI will follow the same path. Farming depends on physical land, crops, equipment and biological processes; AI affects tasks and occupations in different ways. The useful comparison is about the pace and consequences of structural change, not a guarantee that technology will remove a particular share of today’s jobs or that displaced workers will find equivalent work elsewhere.
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A Two-Century Shift in Farm Work
The article places the U.S. estimate alongside historical figures from other countries. It cites economic historians’ estimate 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 cites a reconstruction putting Germany’s primary-sector share at 56.7% in 1849, followed by an official 1882 count in which 43.4% of workers were in agriculture and forestry. The article cautions that the German census undercounted women working on family farms.
For later periods, the article says agriculture made up 83.5% of employment in China in 1952 and 69.7% of workers in India in 1951. The measures and source methods differ by country, so these figures should not be treated as a perfectly comparable global series. They show the broad pattern the article examines: where food production once required a large share of workers, changes in tools and methods allowed fewer people to produce more.
Meyer identifies the piece as Episode 2 of “Work After Work”, a series about how the economy is organized. The article also discloses that it was created with AI assistance and that its narration uses an AI voice clone of Meyer. Its central argument connects the agricultural history to AI, while acknowledging that farming’s transition took about 200 years in the United States.
“Automation could become a sector of up to 90% within a decade or a few decades.”
— Thorsten Meyer, in the article’s thesis
What the AI Comparison Cannot Establish
The article does not provide evidence that AI will automate 90% of any sector, nor does it define how that share would be measured or which occupations and tasks it would cover. The number is an author’s projection. It also does not establish whether AI-driven change will take decades, arrive faster, or produce employment effects comparable to agricultural mechanization.
Historical figures have limits as well. Some are estimates or reconstructions rather than official counts, and national definitions and time periods vary. The source material does not set out a detailed method for comparing agricultural output with inputs, or explain which types of inputs are included in the U.S. comparison. The consequences for displaced workers—including how quickly new jobs emerge, where they are located and whether workers can access them—remain open questions.
The Series Turns to Factory Work
The article points readers to Episode 3, which is expected to examine machinery such as mechanical reapers, threshers and tractors. That installment could extend the series’ account of how technology changed farm labor, although the source does not give a publication date or additional details about its contents.
For the wider AI question, the next useful evidence would be specific, dated research measuring how AI changes tasks, hiring, output and wages across industries. Until such evidence is available, the farming story is best read as historical context, not a timetable for AI-driven job losses.
Key Questions
What is the news in the article?
Thorsten Meyer published an AI-assisted article on November 3, 2026, using agriculture’s long employment shift to frame a discussion about possible AI automation.
How many U.S. workers farmed around 1800?
The article cites a historical 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 show that AI will automate 90% of work?
No. The author describes automation affecting up to 90% of a sector as a thesis. The article does not present it as a verified forecast or provide a method for measuring it.
How many people work in agriculture worldwide?
The article cites an International Labour Organization estimate of 928 million workers in 2025, about one in four workers globally.
What happens in the next episode?
The series points to Episode 3, which is expected to cover farm machinery, including reapers, threshers and tractors. No release date is provided in the source material.
Source: Thorsten Meyer AI
