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Time Machine

Farmworkers and Laborers, Crop, Nursery, and Greenhouse

Scrub through 174years of this role's history, from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.

2026drag to travel through time
187519001925195019752000now
Country
2026
Known today as Farmworkers and Laborers, Crop, Nursery, and Greenhouse (BLS SOC 45-2092)
US Employment
266K
OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.
Median Annual Wage
$35,660
≈ $34,746 in 2024 dollars
Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.
Tools of the era

The tools that defined the work

Select an era to see how it reshaped the work.

  • Hand tools + enslaved and indentured labor (hoe, sickle, cotton gin 1793)

    For more than a century before the Civil War, the hand tools of American crop agriculture were essentially unchanged from the tools of antiquity: the hoe, the rake, the sickle, the dibble stick, and the cotton hook. Eli Whitney's cotton gin (1793) mechanized cotton-fiber separation from seeds, which increased the profitability of cotton growing so dramatically that it roughly tripled the demand for field labor to plant, cultivate, and pick the cotton itself. The gin is the clearest example in American agricultural history of a labor-saving machine in one stage of production creating more labor demand in upstream stages. Enslaved workers — approximately 3.5 million by 1860, concentrated in cotton, tobacco, rice, and sugar production — performed the overwhelming share of American crop labor. Their work was extracted by force, not compensated as wages, and represented an estimated one-third of the entire wealth of the United States at the eve of the Civil War. The Emancipation Proclamation (1863) and the 13th Amendment (1865) formally ended chattel slavery and forced a reorganization of Southern crop-labor markets into sharecropping and tenant farming — structurally different from wage labor but still dependent on the same hand tools and the same physical intensity.

    Effect on the work

    The cotton gin roughly tripled cotton production and dramatically increased the demand for hand-picked cotton labor — enslaved workers in the South grew from approximately 700,000 in 1790 to 3.5 million by 1860 as cotton spread across new states. Emancipation ended the forced-labor system without immediately changing the tools or the crop-labor structure.

    Work toolChanging equipment
  • Chinese Exclusion Act (1882) → Japanese → Filipino → Mexican labor migration waves

    On May 6, 1882, President Chester Arthur signed the Chinese Exclusion Act — the only US law to bar immigration on the basis of race and national origin. In California, where Chinese workers had built the transcontinental railroad, drained the Sacramento Delta, and formed the backbone of Central Valley fruit and vegetable agriculture, the Act's immediate effect was to strand existing workers while eliminating future recruitment. California growers pivoted to Japanese workers in the 1880s-1910s (until the 1907 'Gentleman's Agreement' informally restricted Japanese immigration), then to Filipino workers (Manongs) in the 1920s-1930s (until the 1934 Tydings-McDuffie Act limited Filipino immigration), and finally and durably to Mexican workers whose proximity and economic pressure drove a continuous migration stream that no single law could fully stop. The Mexican Revolution (1910-1920) accelerated northward migration; the Immigration Act of 1917 included an exemption for temporary agricultural laborers at growers' insistence; and by the 1920s, Mexican workers had replaced all earlier waves as the dominant hired crop-labor force in the West and Midwest. The Great Migration also brought Southern Black workers to Northern agriculture and industry, but crop farmwork in the South remained dominated by sharecropping and tenant farming through the 1930s — a form of debt bondage that had replaced slavery without liberating its workers.

    Effect on the work

    Each legislative restriction on one national-origin group created demand for the next wave of immigrant workers, without changing the hand-labor technology or the wage structure. The result was a crop-labor market permanently organized around the most economically vulnerable available workforce — willing to work for wages that US-born workers would not accept.

    Work toolChanging equipment
  • Bracero Program (Emergency Farm Labor Agreement, 1942) — institutionalized temporary migration

    On August 4, 1942, the United States and Mexico signed the Mexican Farm Labor Agreement — the Bracero Program. The immediate justification was wartime labor shortage: young American men were being drafted into military service, and California and Texas farms faced the real possibility of crops rotting in the fields for lack of hands. The program provided Mexican men with short-term contracts (typically 45 days to 6 months) for specific agricultural work, with provisions for a minimum wage, transportation, housing, and medical care. In practice, the housing provisions were often unfulfilled, the minimum wage was often below what had been promised, and workers who complained could be deported without recourse. Nevertheless, the program grew from 4,203 contracts in 1942 to a peak of approximately 445,000 in 1956. Over its 22-year life, approximately 4.6 million contracts were issued to Mexican men — though a single worker could receive multiple contracts, so the number of individuals involved was smaller. The program was simultaneously a labor-supply mechanism and a template for the permanent structure of American farm labor: temporary, immigrant, legally vulnerable, and priced below domestic wage floors.

    Effect on the work

    The Bracero Program suppressed agricultural wages in receiving regions. Economists studying the program's end in 1964 found that agricultural wages in affected counties rose an average of 40% in the subsequent years — direct evidence that Bracero labor had held wages below market rates. The program also created social networks, remittance patterns, and migration corridors that persisted as undocumented migration after the program ended.

    Work toolChanging equipment
  • Mechanical harvesting (cotton picker, tomato harvester, lettuce thinner) — selective displacement

    The mechanical cotton picker, commercially viable by the early 1950s, was essentially complete in its penetration of US cotton production by 1970. The conversion from hand-picking to mechanical harvesting displaced an estimated 400,000 workers over approximately 20 years — the largest single technology-driven displacement of agricultural laborers in US history. The second major mechanization was the UC Davis tomato harvester, developed by agricultural engineers Jack Hanna and Coby Lorenzen in the early 1960s and commercially adopted after the Bracero Program ended in 1964. Within 10 years, California's processing tomato harvest — which had employed 50,000-80,000 hand pickers per season — was almost entirely mechanized. The 1961 adoption of a mechanical grape harvester in some wine-grape regions further reduced per-acre labor intensity in that niche. These mechanization waves shared a pattern: they worked for uniform, tough crops harvested all at once (cotton bolls, processing tomatoes, wine grapes) and failed for delicate, variable crops harvested over weeks or months (strawberries, lettuce, asparagus, cherries). The soft-fruit and vegetable harvest remained — and remains — resistant to mechanization because of the precision, timing, and gentleness that machine grippers cannot yet reliably replicate.

    Effect on the work

    Cotton and processing-tomato mechanization together displaced approximately 450,000-500,000 hired crop workers between 1950 and 1975 — compressing the hired crop-labor workforce by a third or more from its mid-century peak. The survivors concentrated in fruit, vegetable, and nursery work that resisted mechanization.

    Work toolChanging equipment
  • IRCA (1986) + H-2A expansion — documented immigrant workforce institutionalized

    The Immigration Reform and Control Act of 1986 created two distinct mechanisms for the crop-labor market. The Special Agricultural Workers (SAW) program legalized approximately 1.2 million agricultural workers who had been working in perishable-crop agriculture — the largest single legalization of agricultural workers in US history. Simultaneously, IRCA split the old H-2 temporary worker visa into H-2A (agricultural) and H-2B (non-agricultural) categories, creating the modern framework for documented temporary agricultural labor. The SAW legalizations initially shifted a large share of the workforce from undocumented to documented status, temporarily reducing grower dependence on unauthorized labor. But the long-run dynamics moved in the opposite direction: legalized SAW workers aged, moved out of agriculture, and were replaced by a new wave of undocumented workers from Mexico and Central America. By the 2000s, the National Agricultural Workers Survey estimated that approximately half of hired crop workers were unauthorized — a higher share than before IRCA. The H-2A program grew slowly through the 1990s and began accelerating in the 2000s as enforcement pressure on unauthorized workers increased, reaching 48,000 certified positions in FY 2005 and growing rapidly thereafter.

    Effect on the work

    IRCA reshaped the documented/undocumented balance temporarily without changing the underlying economics: crop production that required more hand labor than the domestic workforce would supply at prevailing wages. The H-2A program began its long growth curve that would reach 385,000 certified positions by FY 2024.

    Work toolChanging equipment
  • Precision ag-robotics — LaserWeeder, autonomous tractors, vision-guided pickers

    By 2018, the economics of farm labor had shifted enough that robotics companies could find a business case in agricultural applications that the cotton-picker era could not touch. Carbon Robotics (founded 2018, Seattle) launched the LaserWeeder: a GPS-guided tractor-attachment that uses computer vision to identify weed plants in a crop row and fire precision carbon dioxide lasers to kill them without herbicide. The system eliminates the hand-weeding labor that represents a significant seasonal labor demand in organic vegetable and specialty crop production. By 2024, Carbon Robotics had deployed approximately 100 units commercially, with customers in California, Oregon, Washington, and the Pacific Northwest. FarmWise (founded 2017, San Jose) deployed its Titan FT35 weeding robot — a large autonomous machine that cultivates between rows and uses AI vision to remove weeds by mechanical action, without chemicals. Naio Technologies (founded 2011, France) markets the Oz robot weeder and Ted vineyard robot in US markets. The most symbolically significant deployment was John Deere's 8R Autonomous Tractor, unveiled at CES 2022 and available to commercial customers in 2022: a fully autonomous 410-horsepower tractor that operates without a driver in the cab, using cameras and GPS to plow, cultivate, and plant fields. Deere sold its first units to US farmers in late 2022. Tortuga AgTech (founded 2017, Houston) has demonstrated strawberry-picking robots capable of identifying and harvesting ripe strawberries — the most challenging hand-harvest task because strawberries are fragile, ripen unevenly, and grow in geometrically irregular positions. As of 2026, Tortuga systems remain in advanced trials rather than broad commercial deployment. The pattern across all of these platforms: narrow deployment in specific crops and tasks where the labor cost is highest (organic weed management, wine grapes, strawberries) with CAPEX of $100,000-$400,000 per machine that has not yet broken even against labor costs in most conventional crop farming contexts.

    Effect on the work

    BLS projects a -3.3% employment decline for SOC 45-2092 from 2024-2034 — modest shrinkage rather than collapse. The robotics platforms are real but narrow: Carbon Robotics LaserWeeder ~100 units deployed, John Deere 8R Autonomous Tractor in initial commercial sales, strawberry-pickers not yet at scale. The H-2A program continues growing (385,000 certified positions in FY 2024), indicating that growers in most crop categories still rely on human labor and have not found a cost-effective robotic substitute.

    Work toolChanging equipment
Projection cone · present → 2034

What credible sources project

Scrub the slider past now to anchor each scenario on the scrubber. The spread is the range of futures credible sources project for this role.

Employment outlook
Projected change in the number of people doing this work.
H-2A expansion / immigration enforcement tightening scenario
2034
+5%
Optimistic tail of the uncertainty cone for this occupation. If immigration enforcement intensifies and undocumented workers leave agricultural employment — as occurred in 2008-2010 during ICE worksite enforcement operations — growers would expand H-2A program use, increasing the documented workforce count and potentially the total BLS-measured headcount. The H-2A program grew from 65,345 visas in 2012 to 315,500 in 2024 — a 4.8x increase in 12 years — driven by labor scarcity and enforcement pressure. If enforcement tightens further without corresponding increases in immigration pathways, and if robot CAPEX remains too high for small and medium growers, the documented hired crop-worker count could grow 5-10% from 2024 levels even as undocumented workers cycle out. This is not a technologically optimistic scenario; it is a policy-driven labor-accounting scenario.
BLS National Employment Matrix 2024-34
2034
-3.3%
BLS Employment Projections 2024-34 cycle (most current). Baseline 504.8 thousand (2024); projected 488.1 thousand (2034); net change -16,700 jobs (-3.3%). This is slower than average decline — the all-occupation average for this cycle is approximately +4%, so -3.3% represents modest contraction rather than rapid displacement. BLS methodology models observed productivity trends and demand projections under current technology and policy trajectories; it does not model speculative scenarios of full robotic deployment. The -3.3% projection implicitly assumes continued H-2A growth but slower growth in ag-robotics deployment at scale.
Agricultural robotics acceleration scenario
2034
-20%
Pessimistic tail of the uncertainty cone. If ag-robotics CAPEX falls by 50-60% over the next decade (as it has for solar panels, drone platforms, and autonomous vehicles in adjacent domains), growers in high-labor-cost states (California, Oregon, Washington) who currently pay H-2A workers $15-19/hr plus housing and transportation could find robotic weeding, thinning, and harvesting systems cost-competitive in 5-7 years. Strawberry-picking robots from Tortuga AgTech and Harvest CROO Robotics are in advanced trials; California wine-grape robotics from FFRobotics and Abundant Robotics have demonstrated commercial viability in specific vineyard configurations. If these platforms reach commercial scale by 2028-2030 and the commodity-crop weeding market (Carbon Robotics, FarmWise) expands at its current trajectory, a -15% to -25% employment decline by 2034 is a plausible downside scenario, particularly in California and other high-minimum-wage states where the labor-cost pressure is greatest.
AI task exposure
Share of the role’s tasks that researchers estimate AI can do. This is a measure of task exposure, not a forecast of jobs lost.
Frey & Osborne (2013)
2033
40%
of tasks
Gaussian-process classifier on O*NET task features. Frey & Osborne assigned Crop Farmworkers a probability of computerization of approximately 0.87 — placing them in the high-risk category of the 702-occupation dataset. The bottleneck factors that did not push them to 0.95+: irregular terrain, variable crop conditions, and fine motor dexterity requirements for handling fragile produce. At 0.87 probability over 10-20 years, a -40% scenario represents a plausible realization of their forecast. In practice, employment from 2010 to 2024 has been roughly flat (575,000 → 504,800), indicating partial F&O vindication: some displacement has occurred via robotics and declining domestic food-crop acreage, but the magnitude and speed are far less than 0.87 would imply. The F&O analysis modeled technical feasibility; it did not model the H-2A program's political-economic function as a permanent supply mechanism, or the CAPEX barriers to farm-robot deployment.
Eloundou et al. — "GPTs are GPTs" (2023)
2028
1%
of tasks
GPT-4 task-by-task LLM exposure labeling on O*NET tasks for crop farmworkers. Crop farmworkers score very low on LLM exposure because essentially none of their core tasks — transplanting seedlings, hand-weeding, harvesting, tying vines, operating irrigation — are text-based tasks an LLM can perform. This is not the relevant threat for this occupation. Eloundou's methodology correctly captures that this occupation is not threatened by language models; the threat is physical robotics (laser weeders, autonomous tractors, robotic pickers) and that threat is categorically different and not well modeled by GPT-4 task labeling. The -1% estimate represents only AI-assisted planning tools (precision irrigation scheduling, yield prediction) that may marginally reduce per-acre labor requirements.
Today, in this role

What's shifting in the work right now

The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.

What's changing in your day

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereRecord crop-production data including pesticide applications, irrigation volumes, yields, and labor hours in farm management software or paper logs to support compliance, cost tracking, and agronomic decision-making.

Record crop-production data including pesticide applications, irrigation volumes, yields, and labor hours in farm management software or paper logs to support compliance, cost tracking, and agronomic decision-making.[1],[6]

Tools picking this up
Where your edge is

Learn digital farm management platforms (Granular, Climate FieldView, AgWorld) to transition from paper-log entry to data-verified agronomic recordkeeping roles with greater responsibility and pay.

AI is sitting alongside you hereScout fields on foot or using AI-assisted drone imagery platforms to identify pest infestations, disease outbreaks, and nutrient deficiencies, then report findings to farm supervisors or agronomists for treatment decisions.

Scout fields on foot or using AI-assisted drone imagery platforms to identify pest infestations, disease outbreaks, and nutrient deficiencies, then report findings to farm supervisors or agronomists for treatment decisions.[6],[7]

Where your edge is

Train on precision-ag scouting platforms (Taranis, Climate FieldView) to interpret AI-generated threat maps; pursue a Certified Crop Adviser credential to formalize the agronomic knowledge gap.

AI is sitting alongside you hereOperate tractors and tractor-drawn machinery for tillage, planting, cultivation, and spraying, following GPS-guided field paths and monitoring on-screen prescriptions for variable-rate seed and chemical application.

Operate tractors and tractor-drawn machinery for tillage, planting, cultivation, and spraying, following GPS-guided field paths and monitoring on-screen prescriptions for variable-rate seed and chemical application.[8],[1]

Where your edge is

Complete manufacturer training on GPS auto-steer and autonomous-kit operation; learn to read and troubleshoot machine telematics dashboards to position yourself as an equipment operator rather than a manual operator.

Where this role is heading

Natural next steps for someone with your foundation: not exits, evolutions.

A direction you could grow

First-Line Supervisors of Farming, Fishing, and Forestry Workers

First-Line Supervisors of Farming, Fishing, and Forestry Workers coordinate labor crews and increasingly oversee robotic and autonomous equipment deployments. Experienced farmworkers with bilingual skills, pest-scouting knowledge, and equipment familiarity are the primary pipeline for these supervisory roles on mid-sized operations.

What you'd add
  • · Crew scheduling and labor-compliance recordkeeping (OSHA, FLSA, H-2A standards)
  • · Pesticide applicator license
  • · Basic farm management software (Granular, FarmLogs)
  • · Conversational English and Spanish for bilingual crew coordination
What it takesSome new skills to pick up
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The data behind this timeline

On record since1862
Latest tracked employment265,500 (US, 2025)
Latest median pay$35,660 (2025)
Outlook-3.3% by 2034 (BLS National Employment Matrix 2024-34)
View all 28 cited data points
YearUS employmentMedian annual paySource
19001,800,000n/aESTIMATE
19421,500,000$480ESTIMATE
19561,700,000n/aESTIMATE
1970900,000n/aESTIMATE
1990700,000$8,500ESTIMATE
2003233,450$15,450BLS-OEWS
2004240,000$16,030BLS-OEWS
2005620,000$16,450ESTIMATE, BLS-OEWS
2006230,780$16,540BLS-OEWS
2007239,380$17,020BLS-OEWS
2008242,390$17,960BLS-OEWS
2009233,650$18,540BLS-OEWS
2010575,000$18,000ESTIMATE
2011233,280$18,690BLS-OEWS
2012253,670$18,670BLS-OEWS
2013261,720$18,710BLS-OEWS
2014269,650$19,060BLS-OEWS
2015520,000$19,770ESTIMATE, BLS-OEWS
2016273,450$22,000BLS-OEWS
2017282,300$23,380BLS-OEWS
2018287,420$24,320BLS-OEWS
2019295,520$25,440BLS-OEWS
2020293,910$28,660BLS-OEWS
2021277,200$29,630BLS-OEWS
2022284,000$33,000BLS-OEWS
2023258,730$34,470BLS-OEWS
2024504,800$33,600BLS-OEWS, ESTIMATE
2025265,500$35,660BLS-OEWS
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