Fields of the Future: Autonomy and the New Era of Global Farming

Overview

Autonomous machines are a hot concept in agriculture with declining labour pools and rising costs. But is it truly the path forward and how are agricultural OEMs and robotics developers shaping the future?

Explore key topics and thoughts from industry leaders in Hexagon's first agricultural industry ebook.

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A perfect storm is ravaging the agriculture sector across the world. Acute labour shortages, mounting pressure from climate change, a challenging policy landscape and an urgent need to feed an ever-growing population are forcing the sector to find ways to do much more with less.

Arguably, agriculture has never faced such a challenging period in its history. However, this crisis is becoming a catalyst for innovation and, at the heart of that innovation is autonomy.

Autonomous equipment on farms has the potential to not only address the maelstrom of obstacles facing agriculture and ensure a growing global population is fed, but to also improve sustainability, drive new efficiencies, shore up food security and, most importantly, improve the profitability of our beleaguered farmers.

For agricultural Original Equipment Manufacturers (OEMs), startup robotics companies, and farmers alike, the shift towards autonomous machinery isn’t just a technological challenge—it’s a cultural one. It’s a reimagining of the modern farm.

The VP of agriculture strategy at Hexagon’s Agriculture Division, Bernardo de Castro, says:

“Autonomy is the next big wave of technology in the industry. It will increase accuracy and that will ensure we can produce more food with less. This will drive huge savings in inputs and help to make farming more sustainable—both environmentally and financially,” he adds.

The labour shortage is a critical issue globally. America has a deficit of 2.4 million agricultural workers with more than half of farmers reporting labour shortages (1). In California alone, they face a shortage of 400,000 agricultural workers and that number could increase by 10% a year (2).

In the UK, the after-effects of Brexit have seen significant shortages in workers on farms and across the entire food supply chain, from butchers to truck drivers. An estimated $27 million USD worth of fruit and vegetables went unharvested last year because of worker deficits (3).

In Canada, the agricultural sector lost an estimated $3.5 billion USD in sales in 2022 due to worker vacancies and predicts the nation will face a shortage of 100,000 workers by 2030 (4).

Australia is short 172,000 agricultural workers and consumer prices are rising as a result (5); Japan has the highest agricultural labour shortage in the world with an 85% deficit (6); and the European Union saw a 4.5 million drop in the number of agricultural workers between 2005 and 2020 (7).

This issue is growing the world over, with key factors like climate change and migration hindering food production and the productivity of farms from Southeast Asia to Saudi Arabia and on to Sub-Saharan Africa and South America.

Peter Robinson, Regional Head of Sales for the UK, NA and Australia at autonomous agricultural vehicle specialist AgXeed, adds: “The challenges facing agriculture—whether it be political, environmental or commercial—are significant and, moving forward, we are going to have to do more with less.”

He continues, “Farmers are seeing an ever‑changing climate and facing a requirement to get work done in an ever decreasing time window. As people see robotic milking machines, robotic mowers and autonomous cars in some parts of the world, adoption and perception of these systems has greatly improved and we are seeing more farms starting to purchase autonomous options as possibilities increase.”

In this eBook, we explore the current landscape of agricultural autonomy around the world, the challenges and opportunities it presents, and what the road ahead looks like—from hybrid tractors, to fleets of small intelligent robots.

From the earliest forms of agriculture with simple hand tools, through mechanisation and on to next‑generation sensors, GPS and autosteer systems, the evolution of agriculture relentlessly marches on.

The precision agriculture revolution has transformed farming, cutting inputs, driving efficiencies and increasing yields while simultaneously helping to restore depleted soil health.

However, agriculture must continue to evolve to remain sustainable and we are now entering the next phase of farming, moving from assisted automation to true autonomy.

Hexagon’s portfolio manager for agriculture autonomy, James Szabo, explains:

This evolution can be summarised in three key phases. We’ve seen the rise of the Sensor Era with precision agriculture, and this has seen a huge increase in collecting environmental and operational data, which has helped to transform decision making on farms.

The second phase is the Assisted Autonomy Era, and this has seen GPS‑guided operations and task automation becoming the norm across our agricultural landscapes.

The next stage is the Perception Era. This is the next step in the autonomy revolution and is about using artificial intelligence (AI)‑powered systems with computer vision and machine learning. These systems are able to look at the landscape and understand what obstacles or opportunities are there, making instant decisions about whether it’s a clump of weeds that can be agronomically treated or an obstacle that presents a risk and must be avoided by the autonomous machine.

Hexagon is contributing to this evolution with advanced perception technologies. AI‑powered camera systems which help machines understand and navigate complex environments, even in GNSS‑denied areas, a key hurdle for full autonomy in many permanent crop agricultural operations.

Global Navigation Satellite Systems (GNSS) are fundamental to agricultural autonomy, providing the precise positioning, navigation, and timing that enables autonomous farming equipment to operate with centimetre‑level accuracy. Hexagon has a long history of supporting agricultural OEMs on their precision agriculture journey and, with its perception technology, is paving the way to the next era of farming technology.

This level of perception will also enable us to look at each plant individually, a key step in improving farm productivity and securing food supply in the future.

James Szabo adds, “We successfully replaced the horse with the tractor, and we replaced the farmer using a hoe with implements. We’ve now replaced relying only on human judgement for crops, by backing it up with science and precision agriculture data. We’re now replacing that with a single plant approach. Autonomy in the Perception Era can see the plant in real‑time and then act individually. It means we can optimise everything for that one plant in the field, and the benefits of that are immense. With perception technology, we can understand the environment much better at a resolution not previously possible, and autonomy then allows us to take advantage of that new level of understanding.”

Much like we’re seeing in the evolution of autonomous cars on our roads, the immediate future of autonomy in agriculture across the globe isn’t fully robotic—it’s hybrid.

Marketing manager of tractor giant Fendt, Ed Dennett, says: The reality is that, for now, you are still going to need a switched‑on operator in the cab, but we will see a hybrid approach initially. “This will mean the operator will be responsible for driving the machine to the field, but it will then take control and carry out the planned operation autonomously, using AI to learn from any adjustments that the operator may make.”

Director of global agricultural machinery manufacturer Horsch, Stephen Burcham, added: “What we have found is that everyday still wants a cab. Inevitably, John Deere will soon make an autonomous tractor, that will work well, but it won’t really be much different to what you can see today.”

Stephen adds: “It’s alright saying you can control it on a joystick, but if something goes wrong, you still have to move it in the yard, you still have to put it on a trailer and you still have to get it to the field and open the gate. That will mean someone needs to be able to climb in and drive it.”

Manufacturers agree large machines capable of switching between manual and autonomous modes will be the gateway technology.

Picture a tractor driven to the field by a human operator, then switching to full autonomy to carry out ploughing or seeding. This approach provides reassurance, ensures regulatory compliance, and helps build farmer and societal trust.

Bernardo de Castro from Hexagon explains:

Bernardo adds: “Many developers are taking a retrofitting approach to autonomy, leaning into the hybrid strategy. Sales of agricultural machinery are down around the world, but the reality is that there is still a huge fleet of vehicles out there in the field.”

“These can be retrofitted to be hybrid machines, and that will also help overcome the barriers to getting autonomy on the farm, too,” finalised Bernardo.

Hexagon’s James Szabo adds: “The reality is we are a bulk industry and have to deal with tonnes of grain, produce or inputs. That means we are looking at a near‑term future of mid‑size hybrid machines between 140‑180hp that can cope with large implements and loads rather than lots of smaller machines operating across the field.”

“And, when crops are growing, you’ll still need machines that are big enough to operate above the crop,” says James.

OEMs must therefore invest in modular systems: machines that can operate manually, semi‑autonomously, or autonomously, depending on the task and conditions, allowing the farmer to get a return on their investment throughout the entire farming calendar.

The future is in the eyes of the beholder. In the current machine landscape, developers and innovators are crafting diverse visions for these machines, each tailored to meet specific industry needs and challenges. From precision‑focused robots to versatile, multifunctional giants, the future of autonomous agriculture promises enhanced efficiency, sustainability, and productivity. This section explores the cutting‑edge concepts and technologies being developed to redefine farming as we know it.

Swarm Robots: Collaborative Intelligence in the Field

The good news for smaller robotic businesses is that, while hybrid systems are seen as the short‑term reality in larger agricultural operations, long‑term visions include swarm farming—fleets of lightweight, autonomous robots working 24/7 across fields.

Plus, many manufacturers see a role for smaller machines in a range of growing operations away from the typical large‑scale feed operations.

These smaller machines will cost less; task‑specific; electrically powered; and safer to operate near people and animals.

In the recent The Future of Agricultural Machinery report, Kit Franklin, principal investigator of the Hands‑Free Farm at Harper Adams University, says: “The future is lots of small autonomous machines working across the farm.

“Yields are stalling because poor soil health largely caused by compaction because of the larger tractors. The big bits of mechanisation have overcome the labour shortage, but they have also caused the issue with soil health. We need to think about precision autonomous agriculture and the big machines are not suited to that.

“Smaller, lighter, more precise machines is what we need to be working towards. Those are the benefits, and we can target that. We just don’t need 600hp autonomous machines.”

Horsch’s Stephen Burcham says: “I can see smaller, little autonomous robots taking off in nurseries or greenhouses and things like that, but it’s a way off in the commercial arable world yet.”

Start‑up robotics companies are at the forefront here, creating compact, nimble platforms that reduce soil compaction and can work for longer hours than traditional tractors.

However, these smaller players often face challenges in autonomy integration. They need off‑the‑shelf autonomy solutions—modular, cost‑effective systems that can be rapidly integrated without large R&D budgets.

Hexagon’s focus on scalable autonomy frameworks aims to meet this need, enabling the next generation of robotic disruptors to focus on innovation, not infrastructure.

Task‑Specific Robots: Precision and Efficiency in Action

Some innovators are taking a more niche approach to autonomy. Task‑specific machines are highly specialised and designed to perform a single, often intricate task, like weeding, thinning, or crop‑specific activities like harvesting or spraying. They excel in precision for their dedicated function and are frequently designed for high‑value crops.

The success of these machines is based solely on the ROI they can achieve by doing one task very, very well.

Labour‑intensive activities like fruit harvesting are seeing developments to address labour shortages and increasing costs, which can make fruit inaccessible to the average family.

Spraying robots for orchards and vineyards are also seeing more investment and robot developments to improve the safety of operators by reducing exposure to agrichemicals, as well as increasing the efficiency of the task by using only what is needed, where it is needed.

Weeding robots are another popular type of task‑specific machines. They are focused on increasing the production and quality of high‑value crops while reducing the use and environmental impact of herbicides.

The challenges with single‑task agricultural robots are that they have to do the task better, faster, and/or cheaper than the alternatives available today. This requires developers to understand the target price threshold they need to achieve for the machine to have a positive ROI for farmers.

By knowing where to use proven off‑the‑shelf autonomy solutions and where to focus internal resources, these machines have a great opportunity to get to market faster than infrastructure solutions.

Versatile Giants: Redefining the Tractor with Multifunctional Machines

Designed from the ground up as autonomous tools, cab‑less units capable of performing a wide range of tasks by hitching various standard implements. They are the versatile “tractor replacement”.

Many of today’s most successful scale‑up companies have adopted this vision. Its success may be in part due to the adaptability these machines provide and their use of current farming practices. These machines use implements that are already owned and being used in the field, just removing the time commitment needed to have a person sit in the cab.

These machines are lighter, more fuel‑efficient and can run for long periods of time. Their reduced weight minimises soil compaction and their accuracy and efficiency can result in use of costly inputs.

However, there are additional challenges for developers to overcome with larger multi‑functional machines.

Safety

Safety has long been an issue in the agriculture industry, being among the top three most hazardous industries globally. According to the International Labour Organization (ILO), one‑in‑three fatal occupational injuries worldwide occur among agricultural workers.

Large machinery in the field, whether autonomous or not, poses a safety risk. Developers need to ensure their systems and sensors can reliably avoid and prevent dangerous scenarios. By integrating reliable, resilient and redundant positioning and perception technologies, machines know where they are and can detect and identify what is around them to maximise operational uptime and assess safety risks.

Implement variability

With versatile machines comes a variety of add‑on equipment from other suppliers and manufacturers. These machines need to be able to operate regardless of what type of implement is attached to them.

Perception systems need to be able to identify the implement as an extension of the machine to prevent it from identifying it as an obstacle or hazard, while still acting on safety risks that approach near the implement.

In addition, these robots need to be able to control the various implements, so integrating industry‑standard communication protocols like ISOBUS becomes even more important with autonomous machines.

Mission management

When machines are expected to do several different types of jobs with different attachments, mission management could make or break their market prospects. Operators need to be able to easily and logically switch from one task to the next to keep operations running smoothly.

By using trusted, reliable, and proven navigation and control technologies, developers can focus their development resources on mission planning and execution programming to create a farmer‑friendly system.

Technology is only as useful as its adoption rate. One of the less discussed but most significant barriers to autonomy in agriculture is the farmer’s mindset.

Many farmers, especially the older generation, can be cautious about fully autonomous machines. And, the average age of farmers is rising around the world. In Europe, the average age of a farmer is late 60s. In Japan, where labour shortages and food security have become critical, the average age of a farmer is now over 70. Globally, the average age of farmers hovers around 60 years of age, and this looks set to increase as younger generations from rural areas and the barriers to entry in agriculture get higher.

Trust, reliability, and return on investment are top of mind for farmers. However, the tide is turning. Younger farmers, who grew up with smartphones and precision ag tools, are more open to autonomy.

Carl Groff, from agricultural machinery manufacturer Bateman, says: “I’m not sure all farmers are ready to embrace autonomy in farming just yet. Unfortunately, with the average age of farmers growing, I think there will be a slower take‑up. The younger generations are certainly more up to speed and ready to discuss autonomous options in my opinion though.”

While farmers have successfully been adapting to rapid changes in tractor technology and wider implement technology for decades, many fear the switch to autonomy will be seen as a major hurdle.

Bernardo de Castro from Hexagon adds: “For autonomy to gain traction, it needs to be as seamless as possible. Big changes are directly associated with risk so that means we need to make the move to autonomy as comfortable as possible for farmers.”

However, AgXeed’s Peter Robinson disagrees, saying the mood in farming is changing: “The reaction to autonomy has been really impressive over the last three years. GPS was introduced in the late 90s, and auto steer in the early 00s. That took a good decade before it was taken up as a mainstream technology within agriculture.”

Peter adds: “However, over the last three years, perception of autonomy has changed drastically. Early on, there was lots of negativity, concerns and challenges over how it would be integrated and how it would affect rural communities.”

The lesson for OEMs and tech providers is that they must design autonomy solutions with progressive pathways. This will allow farmers to start small, see value, and scale up without having to face the risks associated with big changes.

“It’s not just about the machine being autonomous,” warns Fendt’s Ed Dennett. “The implements attached to the machine will need to be smart too.”

A fully autonomous machine isn’t just about a tractor that can steer itself. The entire implement chain must become intelligent.

From seed drills to sprayers, implements must communicate with tractors, respond to terrain changes, and make real‑time adjustments at the plant level. This will also involve them having a degree of autonomy from computer vision, sensor, and AI systems.

AgXeed’s Peter Robinson says: “With autonomy, we have a full understanding of what the machine is doing, where it is, how it is operating and working optimally for the task. Connected smart implementation is needed next.”

Peter adds: “We need the implement manufacturers to have integration and sensors to understand and optimise, through machine learning, to improve what they are doing and to make sure it is working at the right depth and safely.”

“By offering that integration, through the ag bot and reporting back to the user, it will give confidence that the job is done,” finalised Peter.

This means there is a growing need for standardised communication protocols on implements, embedded AI and sensors and real‑time data analysis to ensure plants are treated at an individual level and, critically, the tractor also understands what the implement is seeing.

Alex Fisher, Senior Technical Engineer at Househam Group, a leading UK agricultural sprayer manufacturer, said: “For us, at sprayer level, there are different stages for what customers want to achieve. What people are tending to do is not increase the size of machine but farm smarter with more precision with the aim to increase yields and reduce costs.

Our typical machine upgrade path is increasing section control for more precise section control combined with GPS upgrades. Then customers look at variable rate application maps for applying the right amounts where it’s needed. They start talking autosteer and individual nozzle control.”

Thomas Sands, director of SAM Crop Sprayers, adds: “Autonomy and AI are going to be a key part of the future of farming. We have a lot of customers wanting to get into spot spraying, looking at getting the chemicals in the right place at the right time, and being able to scan fields.”

However, he warns that the costs associated with making smart implements will be a key concern for farmers.

He explains: “The technology is there, but there is still a lot of work to do to get it into the farming world. The key will be making it more affordable to the market.”

“For example, if you have got a lot of cameras on booms, which can collide with a telegraph pole or something else, and they cost thousands each, that will get quite expensive and fast.”

For OEMs, this presents both a challenge and an opportunity as the next frontier in agriculture isn't just smart tractors, but fully integrated smart systems.

The agricultural technology debate has been hounded for years by the issue of rural connectivity. Many of the world’s most productive farms are located in isolated rural areas with poor internet infrastructure and little to no mobile phone network coverage.

While the rise of satellite internet services is helping to overcome this issue, some areas still suffer from major data connectivity issues.

This means autonomy, which relies solely on cloud processing or constant connectivity, simply isn’t viable. That’s why technologies enabling onboard intelligence and offline operation are critical.

Bernardo de Castro says:

Bernardo adds: “These systems need to be able to operate in a safe way if they lose GNSS or drop their internet connection, and that is a challenge as autonomous systems do require significant computing power, and cloud solutions help overcome this issue.”

Another key issue with rural infrastructure will also be power. The advance of autonomy in agriculture requires significant amounts of energy. The electrification of agriculture will be a key component of the rise of autonomy, and this will place a major demand on power networks to charge the batteries and keep the technology running.

As the technology in the field advances, a key question is whether both the energy infrastructure and the battery infrastructure will be able to cope.

Another major challenge for the adoption of autonomy is the complexity of the machines. For the average farmer—and even some of the dealers—these machines represent a great leap forward, and few will be equipped to manage the technology or equipment involved.

This means autonomous agricultural machines will not only need to be intelligent in terms of navigation and plant analysis, but also smart enough to be able to look after themselves and support farmers in planning operations.

The majority of farmers are not programmers, which means OEMs and robotic companies must design autonomy that includes self‑diagnostics and predictive maintenance, user‑friendly interfaces and AI‑driven support tools for troubleshooting.

Fendt’s Ed Dennett says:

James Szabo says: “The skills gap in rural communities was identified 20 years ago and the agricultural universities around the world have done a great job of training the next generation of agricultural engineers and farmers.”

James continues: “However, autonomy does change things as both farmers and dealers will need a different level of knowledge.”

“For example, farmers will now need to not only understand the equipment but also change how they operate. A farmer will have to see the bigger picture from the farmhouse. You won’t be able to just make the decision in the field anymore. In the early days of autonomy, there will be an emphasis on planning and how that operation should be completed, with or without minimal human intervention.”

“The support network of agronomists, service providers and dealers will also need new abilities to be able to handle the new technology. Just look at the high‑end sensors in the field right now, who can fix them if they go wrong?” finalised James.

Arguably, one of the biggest crops farmers now harvest is data. The barrage of sensors and analysis equipment associated with precision agriculture is generating huge amounts of data that can be invaluable for making critical decisions on the farm.

With autonomy, the amount of data being captured will increase exponentially, making it even harder to interpret and make reliable decisions impacting crop performance.

That’s where AI support systems come in, transforming raw data into actionable decisions.

Ed Dennett of Fendt says: “This is the data capture era. Most farmers are now fully accepting of data capture and our task is to help them use that data to influence decisions they make on their farms. Machines can record huge amounts of data. Making this data easy to understand and highlighting the data that supports key decisions is crucial.”

This unlocks true added value in autonomy, with the machinery not just doing tasks, but improving farm profitability through new levels of insight.

Another key debate that continues to be a thorny issue, is the question of who owns the data and the need for standardised data so it can all be reviewed and seen holistically.

Bernardo de Castro explains: “Too many manufacturers are keen on using data on their own and we need to share those insights to reap the greatest rewards.” Bernardo adds: “Ultimately, the farmer owns that data, but manufacturers must provide support to use that data and help the farmer do more.”

Alex Fisher of Househam Group argues the incompatibility of data often goes further and is calling for a central database. He adds: “One of the biggest barriers is a central database is missing. Spray Mapping, for example, going from one database to another can’t always be automatic and synchronous. A central database would enable us to use and move data seamlessly from one platform or manufacturer to another. That is a big thing for the industry as a whole to try and achieve.

“We have customers going for a platform‑based approach. If you have John Deere kit you tend to make all the other equipment have John Deere head units as it just makes the data handling and transfer so much easier. For smaller companies like ours, it requires too many resources and is too vastly complex to make our databases integrate properly when there are various proprietary standards in use by different manufacturers for how data is dealt with.”

Autonomy in agriculture is not developing in a vacuum. The automotive industry’s push toward autonomy has paved the way in sensor development, AI, and perception systems.

With a wealth of car manufacturers now producing vehicles that can be driven autonomously and fully autonomous taxi services now being trialled in cities around the world, the leap to a tractor that’s intelligent, sustainable, and entirely autonomous isn’t as far as many people think.

OEMs can learn from the automotive industry in areas such as scalable hardware platforms, fleet management and updates via the cloud and, crucially, driver‑assist transitioning to full autonomy.

Househam’s Alex Fisher says: “Attitudes about autonomy in agriculture are coming hand in hand with what is happening in the auto industry.

"Look at new cars with automatic braking and cruise control and things like that. People are more accepting of that and realising just how much of the day‑to‑day workload can be taken off by a reliable autonomous system."

Hexagon’s James Szabo argues another key lesson from the auto industry is how cars are maintained and managed. He says:

While the automotive industry provides an initial framework, its technologies cannot be directly transplanted into agriculture. The farm environment presents unique challenges that cars don’t face. Unlike a structured road network with painted lines and traffic signals, a field and the farmyard are dynamic, unstructured spaces.

Autonomous machines must navigate varying terrain, account for crop growth, expect different pieces of large equipment to be moved around the yard and distinguish between plants and weeds—tasks far more complex than staying in a lane on a highway.

This means there is a need for specialised sensors developed for the agricultural space and bespoke machine learning algorithms. While there is much to be learned from the automotive space, the agricultural sector must adapt these technologies to handle the nuanced, often chaotic, conditions of a farm.

Regulations covering autonomous machines in agriculture vary significantly from country to country. Some are anchored to decades‑old laws preventing use of machines without an operator, while others are working to understand the autonomous revolution but are still wide of the mark.

The agreement among manufacturers is that agriculture is often misunderstood at best, or overlooked at worst. Critically, the legislative uncertainty is hindering OEM innovation and slowing farmer adoption.

Bernardo de Castro says: “There is lots going on in terms of regulation but there is still a lot to be done. The end users are less concerned about regulations but more about safety.”

“The reality is, this is a very complex subject, so the industry has a role to explain how technology will be used and how it will benefit the agriculture sector and wider food security.”

“As I’ve previously said, we also need to make sure this process is seamless for farmers and support them to understand how any new legislation will affect them and how it applies to the autonomous solutions they are adopting. Crucially, we also need to ensure they understand how this helps them to operate the machinery safely,” Bernardo finishes.

Hexagon is working with a range of leading agricultural manufacturers to develop an agreed set of standards for autonomy in agriculture, but James Szabo warns this can be a political issue too.

He says: “For many, the autonomy debate can become a bit of a political football as it’s often seen as displacing rural workers. We all know the reality is there aren’t many rural workers left to displace.”

Each country is approaching autonomy legislation in agriculture in a different way. It usually takes a really active lobbying body to make sure the technology is embraced.

“The insurance companies have become the biggest supporter of autonomy in agriculture as it takes people out of the equation and, in their eyes, will make farming safer.”

Ed Dennett from Fendt also raises a cautionary finger, adding:

As legislation is agreed and the debate continues, key issues include who is liable during autonomous operation, how are autonomous agricultural vehicles classified as machines or vehicles and what are the rules around data privacy and AI decision‑making?

The reality is, standards and regulations are constantly evolving to adapt to the rapidly updating technology and that means stakeholders, from manufacturers to policymakers, must collaborate to create clear, progressive legislation that enables responsible autonomy in agriculture.

So, what does the farm of the future look like? Will it be a swarm of small autonomous machines working in sync or large, versatile tractors and machines operating without a driver? And when can we expect to see a fully autonomous farm operating?

All agree a hybrid approach will be key in the short‑term, that we will see smart implements adjusting in real‑time and that we’ll have AI managing tasks, analysing data, and suggesting actions.

Bernardo de Castro is optimistic, saying: “We will start to see fully‑automated operations in some growing situations within three to five years, particularly in those facing acute labour shortages. I think it will be around five to ten years before we start seeing predominantly autonomous machinery in dealerships.”

“The first autonomous operations will be in tasks like spraying in orchards, tasks that are very repetitive and very intensive. The first autonomous solutions will be in situations that can be scaled and where the farmers are sophisticated.”

“I think we’ll also see some early adopters of autonomy with mixed fleets of vehicles who will utilise retrofit options within three to five years,” Bernardo says.

For James Szabo, he argues that while we may see some early adopters running a fully‑autonomous farm in around 20 years’ time, the reality is fully autonomous farms are still 50 years away.

He says:

What is key to this is that autonomy in agriculture isn’t about replacing the farmer—it’s about amplifying their capability. With intelligent machines, better data, and scalable systems, we move toward a future where farms are more productive, more sustainable, and more resilient.

Bernardo concludes: “There is still a lot of focus on driverless tractors or robots, but the industry is recognising that there are other key steps to autonomy, such as selective spraying. Previously, we were guilty of skipping some of the key steps and now we need to take a step back, make the tech more mature and, most importantly, bring the farmer along the journey.”

“Autonomy is the solution, but we need to make sure the ecosystem around autonomy grows with the technology we are developing. If it, or the farmer, falls behind adoption will be slow, and the agriculture sector and our food security will suffer.”

Want to explore how Hexagon can support your journey to agricultural autonomy? Contact us to learn more about our autonomy solutions, including positioning, perception and control technologies.