According to new data from the , U.S. sales of agricultural tractors dropped 21.6% compared to May 2025, with combine sales dipping 56.1% in the same period. 

Canadian sales show a 17% drop in total agricultural tractor sales and a 56.5% decline in combine sales compared to May 2025.

“The May reports reflect the ongoing uncertainty and softness in this market,” said Curt Blades, AEM Senior Vice President. “Farmers are hurting, and equipment sales numbers are a clear indication of the overall health of the farm economy and depressed commodity prices. America’s farmers and ranchers need long-term trade certainty and public policies that help them stay profitable and resilient.”

Source:

Reprinted with Permission from Precision . Originally published June 5, 2026.

View the presentation: This article is based on Chris Hunsaker’s presentation at the 2026 Ag Equipment Intelligence Executive Summit. Readers can access the full slide deck .

Editor’s Note: Chris Hunsaker, founder, Acuitus Ag, led an autonomy presentation and ensuing discussion for manufacturers, dealers, distributors and suppliers at the inaugural Ag Equipment Intelligence Executive Summit on May 20, 2026, in Chicago. 

Is this the end of the Iron Era?

The business model of farm equipment is well understood. Sell machines, sell parts, sell service. Overall growth is generally dictated by the replacement cycle, which is well-documented to be about 4% annually.  Growth rates higher than 4% can be achieved, but it usually comes at the expense of some other value stream. New product launches might outperform this; but growth always reverts to the replacement cycle’s cap eventually.

OEM equipment gross margins generally fall in the 20-35% range — with some specialty crop implements approaching 50%. Sales channel gross margins are generally lower and vary depending on channel structure, geography and crops. Parts and service margins are higher, but still nowhere near what’s emerging.

And what’s emerging? Honestly, it’s fluid and far from settled. But what IS clear is that the NATURE of what’s emerging changes the game entirely.

Here’s the reframe. The customer used to amortize equipment cost over as many acres as possible, and the value of the job done by the equipment was well understood by the customer. The manufacturer would develop new machine features or new models based on whether or not they could hit the gross margin they required to keep their businesses in the black.  Distribution would mark up the equipment on a similar basis. New solutions are hired to do a job — the combined work of multiple machines, several humans and workflow steps the equipment seller doesn’t currently touch. The customer judges value by outcome, not by the asset. Suppliers (software, automation-as-a-service, data analytics, uptime guarantees) price as a function of that outcome, capturing a share of the efficiency, quality or throughput gains. Because those gains are so large, they can afford real innovation risk, and gross margins run 65-85%+. These solutions win on both sides of the economics equation — on price because more value is delivered to the customer and on cost because once software is written, the marginal cost to sell the next instance is near zero. Add subscriptions on top — the customer doesn’t pay everything up front, adoption gets cheaper, the developer stays incentivized to keep improving — and steady, predictable cashflows make innovation less risky to fund.

The old paradigm of software in ag equipment was that software was used to enable your machine. That paradigm is dead. The new paradigm is that your machine is the hardware that enables the intelligence of software. If you’re still the company only selling iron, you’re not just losing on margin. You’re losing on scope. Someone else is capturing value across a much wider piece of the operation than you ever did.

This leads to a critical question. In 2030, or even just in a couple of years, will your company still be selling iron or will it be selling outcomes?

The engine driving all of this is autonomy. Software pricing, outcome contracts, bundled value capture, none of it works without autonomy as the underlying mechanism.

There are four main forces shaping autonomy in ag:

Four Forces

The first force I’ll call the AI catalyst. This force makes everything else relevant.

Five years ago, autonomous perception required about $100,000 of LiDAR hardware and sensors. Today, AI is making a $500 camera see the same way that the $100,000 LiDAR stack could. Perception cost has collapsed, which removes a significant barrier to entry.

The second force is capital intensity. Building autonomous machines from the ground up takes huge amounts of capital and conviction. In the self-driving car business, for example, Tesla is the only startup that’s been profitable so far. One of its highest profile competitors, Waymo, is not profitable because the cost of its vehicle is significantly higher than Tesla’s. Even so, Tesla has only survived up to this point because Elon Musk was willing to stake his entire fortune at near death experience moments during the company’s history to get it to where it’s at.  

In ag, a Tesla-equivalent doesn’t exist yet, and even if it did, it would only solve half the problem. Self-driving cars are the tractor autonomy problem.  There is no automotive analog to the implement autonomy problem, and as such, application of the self-driving car playbook stops at the drawbar.  Incumbent OEMs in ag have a significant defensive moat around their businesses that’s underappreciated. They’ve already invested deeply in design, manufacturing and distribution. They have this moat, startups do not.

The third force is marginal vs. revolutionary innovation. Ag OEMs have built their businesses on true innovation. Much of that innovation came from upstart shortliners. However, what was innovation at some point has become incremental improvement, and that’s dictated by the economics of legacy machines that are in service, dealer networks and risk-averse corporate cultures.

Right now, tech is creating a new set of economics independent of the old economics, and this is a revolution that’s justifying innovation and risk taking for anyone who can see it.

The fourth force is institutional inertia. Ironically, the mass of investments already made by incumbent OEMs that give them a defensive moat also make strategic course changes really difficult. As the saying goes, it’s hard to turn a battleship around in a bathtub. Can OEMs adjust fast enough? That’s the question at the front of everybody’s minds as we see what’s emerging. Startups are lean, nimble and unencumbered by any of that institutional inertia.

The hidden asset that’s key to autonomy overall is the operational data of the machines that are currently in the field and being produced. If you don’t have that, automation is ridiculously harder to achieve. Startups without domain knowledge stall because they can’t reverse engineer years of experience with implements operating in the field. Each OEM holds the key to their own data, and many haven’t unlocked it yet. They’re not even capturing it yet. Startups that are coming to the market are capturing that data from day one. Given these forces, how does autonomy play out from here?

The Four Paths to Autonomy

Four distinct paths to autonomy are emerging and each one has different winners, timing and barriers.

1. Integrated Autonomy. An autonomous CNH tractor was announced at the Farm Progress Show 10 years ago and it got a lot of attention at the time, but it was also a little bit of a “getting over your skis moment” because it hasn’t been shown publicly since that year.

Ironically, CNH built the tractor, but they didn’t build the autonomy stack. That was built by a company in Logan, Utah, called Autonomous Solutions.

There’s a lesson here. The speed and complexity of this path are tricky. Incumbents struggle because cultures that are built to support marginal innovation and institutional inertia make it really hard to shift gears.

Several startups have tried fully autonomous tractors, and they’ve also struggled because of sky-high capital requirements and non-existent distribution. But even if OEMs and startups overcome these challenges, they’d still have an issue because again, tractor autonomy alone isn’t of much value if you can’t solve implement autonomy.

1. Retrofit Kits. John Deere has made attempts at ground-up integration of autonomy, but they seem to be leaning into the second path, which is retrofit kits. This path appears to be where a lot of the action is right now in the industry.

Deere’s second gen retrofit kit is supposed to be available this year, but there’s a lot of cost that goes into this. I look at Deere’s current offering as being like the Waymo of ag autonomy. It’s built on older technology because of risk aversion, and it’s what’s available in the supply chain.  The AGCO PTx Outrun Autonomous Grain Cart system is available, and I’ve seen that one in action. It’s impressive, and they’ve made some smart design choices in the architecture that kind of break out of this mold of just taking what’s in the standard supply chain and running with it.   

There are also autonomy startups like Carbon Robotics, Sabanto and Blue White with machines already in the field. The startups are moving faster with less complexity, and they have a lower price point. OEMs might lead today and they might have an advantage because of their manufacturing and distribution, but will that last?

1. Purpose Built Platforms. One example of this is the GUSS autonomous orchard sprayer, which is already being used in hundreds of fields.  

Startups with technical expertise and agility are owning this path right now because they’re coming up with novel solutions. But implement OEMs with the right domain expertise could absolutely play in this space as well. Interestingly, the major OEM reaction to GUSS was a Deere partnership that quickly turned into a full acquisition in the fall of 2025.

1. Humanoid Robots. This path might come at you out of left field. It’s a huge wild card. If humanoid robots crack general perception and manipulation, they retrofit any existing tractor implement without any redesign. They capture the high margin intelligence layer, and traditional OEMs are at risk of becoming contract manufacturers. I believe this threat is dramatically under-discussed in ag right now.

Regardless of the path forward, consider one other key insight. Using the Tesla/Waymo example again, Tesla has made a gigantic bet that simple perception with cheap hardware will be sufficient to solve full autonomy, while Waymo believes it can only be solved using significantly more expensive LiDAR.

Deere, in particular, might be leaning more toward the Tesla model as its Gen 2 tractor autonomy kit consists of 16 cameras (no LiDAR) that see 360 degrees around the tractor. It also seems to be a starting point to solve implement autonomy simultaneously as the cameras can also see the implement.

Who Wins Autonomy?

The answer to the question is whoever solves implement autonomy first.

The value created in autonomy is all hinged on getting the operator out of the field. That unlocks labor cost savings, training cost savings, higher quality/more consistent work, 24/7 capacity beyond human limits, reinforcement learning and continuous improvement at scale.

An experienced operator might cost $30 or more per hour, and if you can’t get them out of the field, the math doesn’t math and most of the value remains untapped.

Tractor autonomy with manual implements is driver assist. It’s not autonomy, and it already exists.

It’s important to note that implement automation doesn’t have to be all or nothing. It can be done in steps. Start with a function where customer value is high or pain is sharp, like the following:

• Controls (architecture is future proof)
• Sensors (cameras, vision)
• Edge compute (data capture, inference and RL)
• Connectivity (remote monitoring, data transfer to cloud)
• Cloud architecture (analyze, coordinate and learn).

Build the stack once for one function, and it compounds across every function thereafter.  There’s some urgency in this. Inaction isn’t a neutral stance. Value is transferring to whoever owns the intelligence layer of the machines in the field and ultimately the autonomy. If implement OEMs don’t automate, there’s a risk that someone else’s autonomy will catch a large chunk of the implement’s value, leaving it nothing more than a commodity. If implement autonomy is the key to who wins, what does equipment look like when it’s solved?

Bigger Isn’t Always Better

There’s a startup called Aigen Robotics that deploys a solar-powered, lightweight autonomous weeder. Nothing about it looks like a traditional implement, and that’s kind of the point.

We can immediately start thinking about things in a different way when there’s no operator in the cab. One way is to think smaller.

If I have one machine that has a capacity of 100 acres per day and a 10% probability of breaking down, when it does break down, I lose 100% of my throughput. If I have 10 small machines each with a capacity of 10 acres per day and the same probability of downtime, when one goes down, I still have 90% throughput online.

Technology can also allow for more precision, which is in turn enabled by more compute power. As compute power gets cheaper, more form factors get tried. As more form factors get tried, more compute power gets deployed. This is an economic idea known as Jevons Paradox, which I first heard described in the context of explaining why building better and higher capacity roads never seems to reduce traffic. When better roads are available, people drive more and they’ll keep driving more until the traffic pain offsets the benefits of driving. The same thing is happening here. The more compute that is available for a cheaper cost, the more it will be deployed, which in turn is what enables more exotic and innovative precision automation.

Bigger built this industry over the course of decades. Smaller might be something that rebuilds it, but there’s still one wildcard that could change everything.

The Autonomy Wild Card

A startup called Figure AI, one of the leading humanoid robot companies, has raised $2.5 billion to date and currently has its humanoids deployed in BMW manufacturing facilities. In early May 2026, it had a live feed of one of its humanoids sorting packages in a warehouse. The humanoid was tasked with figuring out which side of the package had the shipping label on it and orienting it face-down on the conveyor. I checked the feed one morning, and the humanoid robot had sorted 204,000 packages in just under 164 hours. No breaks, no workers’ comp claims, no managerial issues. The humanoid was doing roughly one package every 3 seconds. They ran it head-to-head against a human intern, and the intern barely beat it by a couple dozen packages over 12 hours. These robots are getting smarter because of recursive and reinforcement learning. Tesla, Figure AI, Apptronik, Hyundai and many others are pouring money into this. The total global investment in the space to date is estimated to be between $30-$50 billion and a third of that is attributed to pure startups. If any of these companies solve general perception and manipulation in unstructured environments first, every form factor argument that I made earlier breaks. Existing tractors and implements become autonomous without any further redesign. This is the main justification behind the massive investment in these products. I believe these humanoids are already good enough to manipulate tractor controls. The question is whether you can train the humanoid to watch the implement and operating environment like a human. The short answer to that question is if you can see it with your eyes, you can train a camera to see it, too. OEMs’ unique access to machine data in their specific domain can become a real strategic asset in this endeavor as this training plays out. It’s something they’re closest to and have more access to than anyone else does — if they’re capturing it. Even if half of this is right, an OEM’s strategy probably needs to consider a humanoid element, and there’s value in capturing existing machines’ operational data regardless of how autonomy shakes out. I think this is an OEM’s call option on the future.

Opportunities & Threats

Everyone in the industry has a specific opportunity and threat when it comes to autonomy.

Dealers’ business depends on iron volume and parts and service right now. As outcomes get sold, that backstop weakens. Dealers have a local presence, customer trust and operational knowledge that nobody else in the chain has. The opportunity is to stop only selling iron, lean into technology and become the deployment monitoring and uptime partner for whatever runs in their territory. If they don’t, somebody else probably will.

Tractor OEMs have the brand, the channel and the balance sheet. What they don’t have yet is integration completely past the drawbar in all cases. But tractor autonomy alone is a little bit of a cap. The win is to own the implement plus tractor system as one integrated outcome. Either build the autonomy in-house or partner deeply and quickly with the people who already have the domain expertise. The Deere acquisition of GUSS in 2025 is one template. AGCO’s partnership with Trimble is another.

Implement OEMs have the domain expertise that others don’t, and they have access to operational data if they’re capturing it. They’re potentially the difference maker in all of the autonomy paths, regardless of how they play out, and that opportunity is enormous. But the threat is equally enormous. If implement OEMs don’t own autonomy for their space, their implement becomes a contract-manufactured commodity bolted onto someone else’s autonomy stack. Forgive me for being blunt, but there may not be a second chance to rectify that.

Startups have the shortest distance to travel on the autonomy path, but they lack scale, and that’s a big hurdle.

Every segment in the industry can choose their path, but there’s no neutral position on the autonomy spectrum. Standing still is still potentially moving backward. 

Five Strategic Questions

At the end of the day, there are five big questions to consider:

1. In 2030, what percentage of your revenue comes from autonomy?
2. Are you positioned to own implement autonomy — or lose it?
3. What’s your machine data strategy — do you have one?
4. Who’s your partner for what you can’t build alone?
5. How does your business change if humanoid robots arrive in five years instead of 15?

Ultimately, I don’t know who wins in ag autonomy. But I’m sure of this — the winners will be the ones asking these questions out loud inside their companies before the answer gets forced on them.

Chris Hunsaker is Co-founder and CEO of Acuitus Ag, a software company engaged in improving the efficiencies of the world’s agricultural operations.

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The following market indicators provide a quick overview of economic and commodity trends influencing agriculture, equipment purchasing decisions and manufacturing costs across the shortline industry.

Corn: Corn futures traded near $4.15-$4.35/bu this week as favorable weather across much of the Corn Belt continued to support crop development. Markets remain focused on summer weather patterns and yield expectations heading into the critical growing season.

Soybeans: Soybean futures held near $11.10-$11.35/bu, supported by steady export demand and continued interest from renewable fuel markets. Traders are closely monitoring U.S. crop conditions and South American production forecasts.

Wheat: Wheat futures remained near $5.80-$6.05/bu as improved moisture conditions in several key growing regions eased some supply concerns. Global production estimates continue to influence market direction.

Cattle: Live cattle futures remained historically strong near record levels, supporting profitability for many livestock producers. Strong cattle prices continue to support demand for feeding, hay, forage and livestock-handling equipment.

Steel: Hot-rolled coil steel prices remained above $1,100/ton. Manufacturers continue monitoring steel markets following recent Section 232 tariff adjustments and ongoing trade policy developments that could influence material and component costs.

Aluminum: Aluminum prices remained relatively stable this week. Manufacturers continue monitoring tariff developments and global supply conditions, as aluminum remains an important material for grain handling equipment, trailers, tanks and lightweight components.

Diesel: Ultra-low sulfur diesel prices held near $3.50-$3.70/gallon, providing relative stability for transportation, field operations and equipment delivery expenses.

Fertilizer: Fertilizer prices remained elevated, with urea trading near $550-$575/ton. Input costs continue to impact grower budgets and may influence equipment purchasing decisions throughout the remainder of the growing season.

Hydraulics & Components: Availability of hydraulic cylinders, pumps, valves and related components remained generally stable. Manufacturers continue monitoring lead times and supplier pricing for specialized hydraulic systems used across a wide range of agricultural equipment.

Electronics & Precision Ag: Supply chain conditions for controllers, sensors, displays and precision ag components remain improved compared to recent years. As technology adoption continues to expand, manufacturers are closely watching component costs and availability.

Equipment Market: Industry analysts continue to report healthy demand for repair parts, retrofit solutions, precision agriculture technologies and productivity-enhancing upgrades as many producers focus on maximizing returns from existing equipment fleets.

Corn: Corn futures traded near $4.35-$4.50/bu this week as favorable weather across much of the Corn Belt continued to support crop development. Markets remain focused on summer weather patterns and yield expectations heading into the critical growing season.

Soybeans: Soybean futures held near $11.60-$11.80/bu, supported by steady export demand and continued interest from renewable fuel markets. Traders are closely monitoring U.S. crop conditions and South American production forecasts.

Wheat: Wheat futures remained near $5.90-$6.10/bu as improved moisture conditions in several key growing regions eased some supply concerns. Global production estimates continue to influence market direction.

Cattle: Live cattle futures remained historically strong near record levels, supporting profitability for many livestock producers. Strong cattle prices continue to support demand for feeding, hay, forage and livestock-handling equipment.

Steel: Hot-rolled coil steel prices remained near $850-$900/ton. Manufacturers continue monitoring steel markets following recent Section 232 tariff adjustments and ongoing trade policy developments that could influence material and component costs.

Aluminum: Aluminum prices remained relatively stable this week. Manufacturers continue monitoring tariff developments and global supply conditions, as aluminum remains an important material for grain handling equipment, trailers, tanks and lightweight components.

Diesel: Ultra-low sulfur diesel prices held near $3.50-$3.70/gallon, providing relative stability for transportation, field operations and equipment delivery expenses.

Fertilizer: Fertilizer prices remained elevated, with urea trading near $550-$575/ton. Input costs continue to impact grower budgets and may influence equipment purchasing decisions throughout the remainder of the growing season.

Hydraulics & Components: Availability of hydraulic cylinders, pumps, valves and related components remained generally stable. Manufacturers continue monitoring lead times and supplier pricing for specialized hydraulic systems used across a wide range of agricultural equipment.

Electronics & Precision Ag: Supply chain conditions for controllers, sensors, displays and precision ag components remain improved compared to recent years. As technology adoption continues to expand, manufacturers are closely watching component costs and availability.

Equipment Market: Industry analysts continue to report healthy demand for repair parts, retrofit solutions, precision agriculture technologies and productivity-enhancing upgrades as many producers focus on maximizing returns from existing equipment fleets.

Sources: USDA, CME Group, Federal Reserve, Trading Economics and industry market reports.

Pet’s Name / Nickname: Malley (short for O’Malley, because she was born on St. Patrick’s Day).

Owner: Laura Sutherly, Agtivation

Title: “Dog Alarm” in Training

Breed: Australian Shepherd

Years on the Job: One month, and still in probationary puppy status.

Favorite Snack: Anything she can find, steal, or convince someone to share or dropped.

Special Skills: Distracting all of us from our work with those puppy eyes.

Favorite Hangout Spot: Right next to Taffy, her 8-year-old Australian Shepherd and newly promoted mentor, who is patiently teaching her how to keep the office calm.

Best Office Habit: Leading mandatory exercise drills while the team chases her around the office to retrieve her latest stolen chew toy.

Most Likely To: Interrupt a Zoom meeting, demand attention during a phone call, or act like she has very important office business.

About Malley

After years of handling office mascot duties on her own, Taffy apparently decided she deserved an intern to train. Enter Malley, the newest member of the Agtivation crew.

Malley comes from the same Australian Shepherd family line as Taffy through Jamie, one of Agtivation’s designers. Nearly eight years after Taffy joined the office, Malley arrived from the newest litter, making the two distant relatives and now office sidekicks.

While Taffy specializes in keeping the office calm, Malley’s specialties include stealing chew toys, interrupting meetings, disappearing the moment it’s time to leave, and wearing the office team out long before anyone has a chance to wear her out. She also never runs short on puppy kisses.

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We know business insurance. In fact, we’ve been providing it to companies like yours for over a century. So when you choose to trust your business with us, you can be confident that we’ll get to know your operations and your employees.

We encourage our members to leverage this expertise by exploring Sentry’s free resources and tapping into their experienced safety team. Their library offers a wealth of safety materials, including dozens of insightful articles.

Topics include: Establishing a Product Safety Process at Your Business, Document Management Program, Reporting an Incident or Claim: A Guide for Farm Equipment Manufacturers and Loss Control Guidelines.

August 12, 2026 | 10-11 A.M. CT Sentry Webinar: Learn about contractual risk transfers for sub-contractors. Some complex jobsites require subcontractors to hire their own subcontractors to perform additional work. In this webinar, we’ll help attendees recognize

• When guarding is needed
• How to identify different types of guarding
• Which regulatory requirements each type of guarding meets

Sentry Resource Library: Members can find a comprehensive library of safety resources from Sentry at: FarmEquip.org/SentrySafetyLibrary.

| Member since 1974

Section 232 tariffs, which primarily affect imported metals and derivative products, were originally implemented during President Trump’s first term. According to the Administration, the tariffs are intended to support domestic industries and address national security concerns related to imports.

The new Proclamation makes the following adjustments to the tariffs, effective June 8 through the end of 2027:

• A temporary tariff reduction from 25% to 15% on certain types of ag, construction and mobile industrial equipment identified in Annex I-C when imported from qualifying trade-deal countries. (See full list of equipment below.)
• A lower threshold for products to qualify as being made “entirely” from U.S. steel, from 95% to 85%.
• 10% lower tariffs on products made in another country with at least 85% U.S. metals, measured by weight.
• Special provisions for USMCA products, including a 25% duty on only the non-U.S. content of the product.

The White House said the modifications are intended to address national security concerns while encouraging investment and domestic production in sectors including agriculture, housing and manufacturing.

In the Proclamation, President Trump stated that the temporary modifications take into account the role these products play in U.S. economic activity while maintaining the broader tariff framework established under previous Section 232 actions.

The changes could reduce tariff costs for some equipment manufacturers that source components globally or manufacture products outside the United States. The relief comes as OEMs continue to report mixed financial results, with many citing tariffs among the factors affecting their businesses.

Recent reports from OEMs highlight the ongoing impact:

Caterpillar: Consolidated operating profit rose 20% to $3.1 billion in the first quarter, driven by a $940 million positive sales volume impact but offset in part by an additional $710 million in manufacturing costs, including higher tariff-related expenses. The company estimated its full-year 2026 tariff costs between $2.2 billion and $2.4 billion. CFO Kyle Epley said during the earnings call that the estimate does “not currently include any IEPA-related refunds as the result of the Supreme Court’s decision.”

CNH Industrial (parent company of Case and New Holland): Global net sales in CNH’s construction equipment segment were down 3% year-over-year to $574 million. In the first quarter, the construction business posted a $28 million loss in adjusted earnings before interest and taxes. Contributing factors included lower sales volumes in North and South America, higher tariffs, higher trade show marketing costs and labor cost inflation, partially offset by improved equipment pricing.

Komatsu: While the Japanese manufacturer finished its 2025 fiscal year with global and North American construction, mining and utility equipment sales up year-over-year, operating income declined. Global construction, mining and utility equipment net sales increased 0.2% to $24.1 billion, while operating income for the segment fell 18% to $3.1 billion.

Kubota: Consolidated revenue for the first quarter increased 13.7% to $5.1 billion, and operating profit rose 59.1% year-over-year to $616.4 million. The company cited higher sales volumes and pricing adjustments in North America as key drivers, while noting approximately $150 million in additional costs related to U.S. tariffs.

Volvo CE: Volvo CE is shuttering its Rokbak articulated hauler business, citing rising operational and supply chain costs and global trade challenges, including U.S. tariffs. The company said these factors have significantly affected financial performance.

In response to the Proclamation, the Association of Equipment Manufacturers (AEM) issued a statement supporting the changes, stating that the tariff reductions could help lower input costs and ease supply chain pressures for equipment manufacturers and farmers. AEM also said the action reflects the challenges manufacturers face when expanding domestic production capacity while remaining globally competitive.

Source:

by Jeremy Groeteke, Senior Global Leader at Syngenta and speaker at the 2026 Supply Summit & Showcase

When I spoke at the FEMA Supply Summit, I opened with the original “See & Spray” — a young entrepreneur with a shortliner Bean Buggy, deciding plant by plant what needed attention. What’s old is new again. The difference today is that the intelligence we once carried in our own heads is moving into the iron itself.

I’ve spent 25 years at the intersection of agriculture and technology — as a farmer, agronomist, scientist, and now a technologist. From every one of those seats, the same conclusion holds: agriculture is naturally AI-compatible. AI thrives in complex, uncertain, data-rich environments, and there are few environments more complex than a field. What has changed is that you no longer need to know how to perform a task yourself in order to automate it. AI lets us automate the indescribable — and that puts entirely new targets on the table for the machines you build.

Consider the scale. The U.S. plants roughly 90 million acres of corn a year — about 2.9 trillion plants. A single petaflop of compute could analyze that entire crop 370 times every second. As I discussed the compute capacity as gone from one microscopic cell to one stalk, took about 60 years of compute science; to go from that single stalk to compute capable of “replanting” America’s entire corn crop 1,700 times took us about 13. The curve isn’t just steep. It’s accelerating, and the slope is the point.

Here’s what equipment makers need to internalize. The Internet changed distribution. The cloud changed scalability. AI brings automated intelligence directly into our products. The merger of iron and AI — robotics, new sensors, computer vision, and large language models working together — is no longer a lab demo. It’s becoming the spec sheet. The machine that perceives, decides, and acts in the row is the machine our customers will increasingly expect.

The industry already feels it. In recent research, 91% of agricultural leaders said AI is moderately to very important for staying competitive — ahead of traditional levers like capital and operational excellence. They expect yield gains, better margins, and sharper decisions. But the most cited barrier is unproven ROI, and nearly 80% believe AI’s impact will come down to quality of execution, not the technology alone. That tension is the whole story: the same leaders who see AI as their biggest opportunity also name it as their biggest risk.

So where should we focus? My advice is to treat efficiency as the entry point, not the prize. Trimming cost with a smarter sprayer or an automated parts lookup is real, but the durable value is in growth — new products, new services, and business models that didn’t exist before the intelligence was in the iron.

Winning will be as much organizational as technical. The companies pulling ahead operate on what I call geek norms: clear ownership, openness to pivots, decisions settled by evidence, and a bias toward speed — plan a little, iterate a lot, and always know the ROI of your AI. As I compared SpaceX and Boeing on NASA’s crew program; the younger, faster, evidence-driven organization is now the routine provider while the legacy player is still closing out certification. The lesson for our industry is blunt.

Don’t show up to fight yesterday’s war. The iron isn’t going away — but the intelligence riding on it is about to define who leads. Start now, start specific, and build the foundation before your competitors do.

Jeremy Groeteke is Global Head of IT & Digital Strategy for Syngenta Group’s Vegetable and Flowers business, where he leads AI, data, and digital agronomy initiatives that drive profitability and sustainability. With more than 20 years of agribusiness leadership experience, he has led multimillion-dollar product launches, built global teams, and forged key industry partnerships.

If you haven’t downloaded the FEMA app yet, now is the perfect time. Download or refresh the app today using the QR code or by visiting to access the latest updates and features.

Did you know you can use the app to access the Farm Show Directory? Stay up to date on farm show dates and locations, and use the RSVP feature to let us know which shows you’ll be attending.

To access the directory, tap “Farm Show Guide” at the bottom of the home screen (look for the tractor icon). You can search by city, state/province, or event name. Each listing includes event dates, location information, website links, and contact details. Members can also RSVP to events and see which shows fellow members plan to attend.

Stay tuned to the Shortliner each month for more app tips and tricks! If you have any questions about the app, contact Gina at Gina@FarmEquip.org.

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