How Has Technology Changed Farming? Data and Real Costs

Technology has changed farming in two big steps. Machines replaced much of the hand and animal labour, and now data and automation are changing how decisions get made. US farm output in 2023 was nearly three times its 1948 level, while total input use grew only 0.12% a year, according to USDA Economic Research Service productivity estimates.

So how has technology changed farming on a real farm? Far less evenly than the headlines suggest. In USDA’s latest crop surveys (2016-19), guidance or auto-steer was on well over half of the acres planted to six major US row crops, while drones, aircraft and satellite imagery were used on 10% or less of the acres in the same surveys. This guide shows what changed, what the evidence says it delivered, what it costs and how to test whether a tool pays on your acres.

How has technology changed farming? Five main shifts

1. Machines replaced much of the labour. US self-employed and family farm labour fell from 7.60 million people in 1950 to 2.06 million in 2000, a 73% drop, and USDA says mechanization contributed to the long decline (USDA ERS farm labor data).
2. Output rose without much more input. US total factor productivity grew by an average of 1.40% a year from 1948 to 2023 (USDA ERS).
3. Satellite positioning put every pass on a map. Guidance, section control and yield monitors let farmers steer accurately, shut off sections and record what each part of a field produced.
4. Farmers can see crops from above. Open satellite data, commercial satellites and drones show crop vigour across whole farms, so scouting can start where a change appears.
5. Data now feeds daily decisions. Weather stations, soil probes, livestock sensors and farm software turn records into irrigation schedules, spray timings and yield estimates.

The first two shifts played out over the last century. The last three are still spreading, and they have gone further on larger farms.

▶ A light explainer on how NDVI maps show crop stress across a 400-acre corn farm. · 4:09

What changed first: machinery and labour

The tractor came first. The FAO State of Food and Agriculture 2022 summary calls it one of the most influential innovations of the twentieth century. FAO dates its spread in the United States to between 1910 and 1960, followed by Japan and Europe after 1955.

FAO also makes a useful split. Any farm job has three phases: diagnosis, decision-making and performing the work. Motorized machines automated the performing. Digital tools now reach into diagnosis and decisions too. That is the plainest way to describe the change from the last century to this one.

Labour did not vanish, and the story did not run one way. USDA reports that farm employment stabilized after about 1990. Wage and salary jobs in US agriculture rose from 1.07 million in 2010 to 1.18 million in 2024 (Bureau of Labor Statistics data, reported by USDA ERS). Labour is still a large cost in some crop sectors. In the 2022 Census of Agriculture, wages and contract labour made up 40% of production expenses on fruit and tree nut operations, against 12% for all farms. That gap helps explain the interest in robots for specialty crops.

How precision technology changed field work

Precision agriculture means managing differences inside a field instead of treating it as one unit. Its tools fall into three groups: those that collect data, those that turn it into maps and advice, and those that act on it.

Guidance and auto-steer

This is the clear adoption winner. USDA’s Precision Agriculture in the Digital Era report (February 2023) found guidance on 5.3% of planted US corn acres in 2001 and about 58% in 2016. Later surveys found 64.5% of cotton acres and 72.9% of sorghum acres in 2019.

The saving is easy to see. Iowa State University measured overlap on two Iowa farms without precision equipment in 2011, across more than 2,500 acres of work. Planting overlap averaged 3.3%, and spring tillage overlap was 7%. Those are two farms, so measure your own before you rely on them.

Yield monitors, yield maps and soil maps

Yield monitors record what each part of a field produced, and that record feeds later decisions. Yield maps rose steadily: corn acres went from 7.7% in 1997 to 43.7% in 2016. GPS soil maps stayed lower, under 25% of planted acres for every crop surveyed.

Variable-rate application and section control

Variable-rate technology (VRT) changes seed, fertilizer or pesticide rates as the machine moves. It covered 37.4% of US corn acres in 2016 and 25.3% of soybean acres in 2018. Section control shuts off planter rows or boom sections over ground already covered, and it was on 41% of cotton acres and 45% of sorghum acres in 2019.

Camera-guided spraying

Sprayers with cameras can treat only the weeds they detect. In a 2024 demonstration on five soybean fields totalling 415 acres, Iowa State University recorded post-emergence herbicide savings of 43.9% to 90.6% by field. The average was 76%, or about US$15.70 an acre. Weed pressure drove the range, so a weedy field saves less. It was one season and one commercial system. Always follow the product label and local rules.

Chart

Yield map adoption by crop

Percent of planted acres, selected crops. Soybeans 1996-2018, corn 1997-2016, sorghum 2003-2019, wheat 1997-2017, cotton 2000-2019

Who actually uses farm technology

Adoption depends on the tool, the crop and the size of the farm. USDA’s report says at least half of relatively large row crop farms use yield maps, soil maps, VRT or guidance. Except for cotton, under a quarter of the smallest farms use any of these four. USDA suggests that returns may be greater at larger scale.

Chart

Technology use on US corn acres

Percent of planted corn acres, 2016 survey

Basic connectivity is far more common. The USDA NASS Technology Use report (August 2025) found that 85% of US farms had internet access and 82% had a smartphone. Half bought farm inputs online in 2025.

These US surveys cover row crops. USDA notes that no national adoption data exist for specialty crops or livestock, so claims about those sectors deserve extra care. Survey years also differ by crop, and the numbers stop in 2019 for the crop-level series, so current use is likely to differ.

Chart

How US farms were connected in 2025

Percent of US farms

Did technology raise profits and cut inputs?

Yes, on the evidence, but by less than sales material tends to imply. A USDA study of 2010 US corn farms estimated these gains in operating profit for a farm of average size:

• GPS mapping: almost 3%.
• Guidance systems: 2.5%, with net returns up 1.5%.
• Variable-rate technology: 1.1%.

These are small percentages, on corn, from older data. They do not show what a new system would earn today. On the environment, USDA’s 2023 report says the evidence to date is mixed. Adopters generally have lower costs for fertilizer, pesticide and fuel, but the reductions have been modest and vary by technology.

The cost side matters as much. Table 3 of the USDA report gives what surveyed farmers reported, and the chart below shows the soybean figures. These costs are from 2018, the VRT premium covers the whole operation, and pricing varies by manufacturer. Treat them as a dated guide, not a quote.

Chart

What soybean farmers reported for precision kit

US$, 2018 survey, replacement cost or VRT premium for the whole operation

Satellites, drones and radar: seeing the whole farm

Satellites changed the scale of scouting. The European Sentinel-2 mission has bands as fine as 10 metres and is designed to revisit every 5 days at the Equator. Combining it with Landsat shortens the gap further, as a published revisit analysis shows. Clouds can still block optical images. Radar satellites such as Sentinel-1 send their own microwave signal, so they can image through cloud and at night.

A vegetation map shows where a crop has changed. It does not name the cause. Someone still has to walk to that spot and find out whether it is water, nutrients, pests or a planter fault. That is why imagery works best as a way to choose where to scout. Services such as the Farmonaut Satellite + AI Farm Monitoring System put these maps in an app, without hardware on the field.

On US farms, imagery use was still low in the survey years. Drones, aircraft and satellites together ranged from 2.8% of cotton acres (2019) to 9.8% of soybean acres (2018). USDA’s question could not separate the three.

▶ A full walkthrough of satellite crop monitoring: reading NDVI, running an AI advisory and pulling a field report. · 19:36

AI and machine learning: from data to advice

AI is the newest layer, and the least measured. Models combine imagery, weather, soil and field records to estimate yield, flag disease risk or suggest timing. Computer vision is the most concrete case, since it powers the camera-guided sprayers above.

FAO’s 2022 report says digital tools can automate diagnosis and decisions, and it sees potential gains in precision, resource use and resilience. It also warns that barriers can keep small-scale producers from sharing in the benefits. Judge each tool on a test of your own: did its advice change a decision, and did that decision pay?

A short test helps. Ask where the model was trained, whether it was checked on your crop and region, and what it does when data is missing. Ask who owns the data you upload, and if you can export it.

▶ A tutorial on the Farmonaut web app for monitoring a farm with satellite imagery and AI. · 8:43

Sensors and automated irrigation

Water is where sensors have a clear job, yet use was low in the survey these researchers cite. University of Nebraska-Lincoln researchers wrote in 2022 that soil moisture probes were used in only 7-12% of fields (citing USDA-NASS, 2019). Traditional checks such as plant and soil appearance remained popular. They name cost and ease of use as the main barriers, and they note that uncertainty leads farmers to add extra water as insurance.

The research goal is lower labour per data point. The Nebraska team mounted thermal and multispectral sensors on a center pivot in a 140-acre research field, so the pivot itself collects crop data as it moves. The team reports that sensors on the pivot worked well, but that their cost was still high compared with the profit gain from less water and more yield. Fertigation adds nutrients through the same water. Where it is used, check the label and local water rules.

Robots and autonomous machines

Autonomous agriculture is real, but it is early. Guidance went from 5.3% of US corn acres in 2001 to about 58% in 2016, and it helps a driver rather than replacing one. Full autonomy asks for more: reliable obstacle detection, safe remote supervision, and a way to fix faults in the field.

Labour cost shows where robots may pay first. Fruit and tree nut operations spend far more of their budget on labour than the average farm, as the census figures above show. Before buying, ask three things: what happens when it stops mid-field, who services it during harvest, and how many hours a season it must work to beat your current cost.

Greenhouses, vertical farms and livestock tech

Controlled environments

Greenhouses and vertical farms use climate control, LED lighting and recirculated nutrient solution. USDA ERS describes these systems as being used mainly for specialty crops, and it flags their sensitivity to energy prices. Energy is the main limit for vertical farms. A 2025 peer-reviewed analysis puts the conversion of purchased electricity into food energy at about 1% to 2%. It finds that vertical farming is not currently competitive with dried cereals or pulses, and only limited for products such as tomatoes and lettuce.

Livestock

Wearable sensors, automated feeders and barn cameras aim to spot illness and lameness sooner and to tune rations. Virtual fencing uses collars to manage grazing without fixed wire, and Texas Tech researchers began a post-fire grazing study using it in 2025. Because USDA has no national adoption data for this sector, ask suppliers for trial results from herds like yours.

Breeding

Newer genetic engineering methods have moved from labs to approved products. The US National Academies’ 2016 report on genetically engineered crops noted that a few crops changed with such methods (genome editing, synthetic biology or RNA interference), including a nonbrowning apple, were approved for US production in 2015. Rules differ by country, so check them where you farm and sell.

What technology has not changed

Some limits have stayed in place. Weather still sets the season. Agronomy still decides whether a map means anything. A sensor reading is only as useful as the person who acts on it.

• Small farms get less from fixed costs. A US$20,000 kit is easier to spread over 5,000 acres than over 200. Rented kit, custom hire and app-based services can lower the bar. USDA notes that Nebraska custom rate surveys show small upcharges for variable-rate application.
• Data rights are still messy. Read who owns your records, who can share them and if you can export them. Ask if the formats will work with other brands.
• Not every farm is well connected. In 2025, 55% of US farms used broadband, while 74% had a cellular data plan (USDA NASS). Check that a tool works when the signal drops.
• Skills take time. New tools need someone to set them up, check them and read the output. Allow for that time in your costs.

Which technology to look at first

Start with the cost line you already know well. Run one field against a comparison strip for a season, then decide. Keep one person responsible for the data, and write down what the result would need to be for you to keep the tool.

Does a precision upgrade pay on your farm?

The calculator below uses the logic of the Iowa State overlap study: less overlap saves input cost, and you compare that against the yearly cost of the kit. Enter your own numbers. It leaves out yield effects, fuel, time and tax, so get professional advice before a large purchase.

Try the numbers for your own farm below.

FAQ

How has technology improved agriculture?

It has raised output per unit of input. US farm output in 2023 was 210% above 1948, while inputs grew 0.12% a year (USDA ERS). Newer tools add smaller gains, such as an estimated 1.1% to almost 3% in operating profit on US corn farms in 2010 data.

What is the most widely used precision farming technology?

In USDA’s surveys, guidance leads among the mapping, rate-control and steering tools it compares, on well over 50% of acres for six major row crops. Drones, aircraft and satellite imagery were at 2.8% to 9.8% on the crops in the survey years.

Do small farms benefit from farm technology?

They can, but adoption is lower. Except for cotton, under 25% of the smallest US row crop farms in USDA’s data use maps, VRT or guidance. Smartphones are far more common, at 82% of farms in 2025, so app-based and hired services are a practical way in.

How does radar help see through clouds?

Radar satellites send out microwave signals and measure what returns. Those signals pass through cloud and do not need daylight, so they can fill gaps when optical images are blocked.

How will drones, robots and AI change a farmer’s daily routine?

Less time may go to driving and routine checks, and more to reading alerts, checking flagged spots and maintaining equipment. How far that goes depends on the crop, the farm size and the service support nearby.

Where farming technology goes next

The next gains are likely to come from tools working together. USDA’s survey already shows that some farmers combine them: maps, VRT and guidance together covered 23% of corn acres in 2016. The FAO frames the wider opportunity as automating diagnosis and decisions, not only field work. Tools that share data cleanly, and that show their value on your own fields, will be easier to keep.

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