Artificial Intelligence

Turn Daily Farm Work and Data Into a Custom Podcast With Help from AI

Fri, 08 May 2026 20:19:19 GMT

Instead of listening to music or making calls on his way to work, Mitchell Karstetter tunes into his favorite podcast. It’s not a celebrity or news pundit; it’s two digital hosts, powered by artificial intelligence, talking about data from his farm during harvest season.

“I like that it’s breaking down everything that we’re doing,” says Karstetter, the owner of RJK Farms. “It’s giving me real-time data that I can use to make decisions faster.”

A grower pulls up his HarvestReplay dashboard. HarvestReplay provides operational insights in the form of daily, updated intelligence briefing to inform real-time decision making, like where to shift a harvest crew or when to start them, based on a grower’s own data such as daily harvest labor and on-farm weather sensors.

(Innov8.ag)

Karstetter is using Innov8.ag’s HarvestReplay system to collect data and make decisions based on their workforce. Each day, it gathers data from the farm and then synthesizes and relays it to growers in the form of an audio podcast.

“ With HarvestReplay, they now have access to the kind of operational insight they have gotten used to having on the row crop side of their business,” says Steve Mantle, CEO and founder of Innov8.ag .

He says right now, this new technology is helping specialty crop growers due to the labor-centric nature of the business, but there are plans for growth into other areas of farming.

How HarvestReplay Scanners Provide Real-Time Insights

For the HarvestReplay to work, they need an automated labor and tracking system. FairPick and FairTrak , which have two ways to track how much a single employee has harvested throughout the day, are examples of these systems.. The first option is for employees to put their harvested product on a scale-like scanner, where it tracks work output, such as pounds per hour picked. The second option is to have their badge scanned by a phone-like handheld scanner to report their statistics. At RJK, they are currently using it on around 600 acres of apple and cherry trees. This allows farmers to track and follow worker’s efficiency and ultimately their productivity.

“It gives you something where you can go, ‘Why is this guy, who’s normally my best guy, not performing as well,’” Karstetter explains. “It helps you identify problems faster.”

Field laborers weigh their cherry bins using Innov8.ag’s FairPick harvest scales, ruggedized, legal-for-trade field scales that record every pick weight, time, GPS location and picker ID, creating automated, real-time harvest labor data used to inform HarvestReplay.

(Innov8.ag)

The HarvestReplay also tracks future weather conditions to help make important decisions, such as when the best times are to harvest or spray. It uses on-farm or state-operated weather sensors, such as AgWeatherNet .

It can also incorporate a grower’s harvest data from previous years to help provide insights into the farm’s historical trends. Adding it all together, AI hosts can then educate farmers on things like how early frost impacts crop volume and quality.

“It’s giving me insights into fields that were not as productive as I thought they were on cost, labor or efficiency,” says Ellie Norris, owner and CEO of Oregon’s Norris Blueberry Farms.

The Three-Tiered Power of HarvestReplay’s Data Ecosystem

The system produces three types of podcasts, depending on who’s listening and their role in the operation:

CFO/owner podcast focuses more on economics, such as comparing orders from different buyers.
The farm manager podcast can be either in English, Spanish and/or other languages. It discusses what happened on the farm and offers advice on decision-making for the upcoming day or season.
The crew lead’s podcast is typically in Spanish. This revolves around recommendations for improving operational efficiencies that affect the bottom-line economics of the farm.

It’s part of a bigger smart data interface. The podcast is only one-third of the HarvestReplay system:

Replay History looks to turn multi-year harvest and labor records into reports and goals. This shows the past performances and economics of previous harvest decisions.
Replay Live gives same-day feedback using GPS labor tracking. It can raise or flag issues such as congestion, slowdowns or misallocated crews so managers can adjust.
Replay Podcast is an AI-generated audio briefing built from the grower’s own harvest data.

“Farms don’t have data analysts, IT teams or CTOs,” says Mantle. “HarvestReplay handles the heavy lift of data aggregation and integration while keeping their data private and the decision-making customized to their operations.”

Leveraging Real-Time Data to Protect Farm Profitability

In 2025, there was a 46% increase in U.S. farms declaring bankruptcy from the previous year. HarvestReplay’s goal is to target areas where farms lose money such as labor, crop production and decision-making.

The system uses the data it collects to recommend changes in order to provide a path for growers to save money. Karstetter shares an example of quickly using the HarvestReplay’s information to switch things up.

“We can go into a block and see that some cherries have been on the smaller side, so we need to prune heavier,” Karstetter explains.

It also allows him and his managers to make decisions on the crews that are working. Karstetter says that in the latest podcast entry, it shared that one group was being more productive than the other. Now he can use this information to see what one group is doing differently and how it sets them apart.

“It’s giving you a kind of like a real-time look at what you’re doing and where you’re at,” Karstetter says. “We really don’t have that unless you sit down and input all this stuff manually.”

Farm Business In 2026: Relationship First, Digital Convenience Second

Tue, 28 Apr 2026 17:48:22 GMT

Based on the 2026 State of the Farm data, farmers aren’t looking to replace their advisers with algorithms; instead, they want digital tools that remove the friction from the business side of their operation. The State of the Farm Report is prepared by Bushel with the goal of illuminating trends in three things:

Farmer tech use
Payment trends
Supply chain

The most recent survey had 1358 respondents, and here are some of the key takeaways for farmers and agribusiness.

Killing The Trope of The Technology Adverse Farmer

The survey has been conducted since 2018, first by FarmLogs, which was acquired by Bushel. As Julia Eberhart explains, the overall takeaway of the survey from every year has been farmers are not resistant to technology adoption.

“Year after year, we’ve tracked the same data point—farmers’ willingness to adopt tech. And overwhelmingly the data shows farmers are willing to adopt. But we still have this stereotype that agribusiness says farmers won’t use it. And we see across all age groups, we see a willingness to try new technologies,” she says.

Eberhart points to key tenets to pull out from the results in how farmers prefer to do business.

“It’s valuable to both agribusiness and farmers,” she says.

Artificial Intelligence Has Arrived

While in early days of adoption, the survey proves farmer use of AI has broken through with 14% of respondents say they use AI tools on the farm today.

“20% of who said yes, had more than 5,000 acres,” Eberhart says explaining that perhaps larger scale operations are adopting the technology at an earlier pace. Adoption of AI is highest for respondents under 60 years old.

Using AI is an indicator for tech-savvy farmers as 70% of AI users from the study are also “willing to experiment with new technologies,” compared to 42% of the other respondents.

And 11% of respondents say they are unsure, which Eberhart could be a reflection of farmers acknowledging how AI is embedded in much of the software they use but they don’t directly engage with the AI.

What Does This Mean for Ag Service Providers?

Per the State of the Farm, technology enhances but does not replace relationships, interactions, and payments/transactions.

“It’s about how to make doing business easy,” Eberhart says.

She says to win the farmer’s business in 2026, ag retailers must empower their agronomists with tools to build loyalty, offer a mobile or web platform so farmers can easily review prices and quotes on their own time, and provide flexible, integrated financing options alongside traditional check payments.

The Differentiator Lies in the Relationship

In 2025, when Bushel asked “If the price is equal, what is the primary reason you purchase inputs from one retailer over another?”, 52.3% pointed to the “Relationship with staff & overall customer service.” In 2026, that number jumped up 8% to nearly 60%.

If you’re assuming younger farmers only want to interact through screens, the data shows the opposite–85% of farmers under 40 cite the relationship with the staff and overall customer service as their primary reason for choosing a retailer—the highest of any demographic.

Another demographic-driven trend is farms over 2,000 acres show a higher preference for text messaging and digital business. However, farms less than 500 acres show a preference to handle business in person.

In-Person Trust Bridged with Digital Convenience

“Farmers are more willing to share data than they themselves recognize,” Eberhart says. “Year after year, data sharing is rooted in who provides value, what relationship they are having, and who is providing easier ways to be sharing it.”

Farmers are most likely to share data when applying for a loan, with their bankers and accountants, as well as crop insurance providers.

“Those three are by far they are getting the most data sharing for good reason,” Eberhart says.

When it comes to input purchasing and service orders with ag retail, there is a nuanced shift. Farmers still highly value talking to their agronomist, but they want the actual transaction process to be much easier.

Digital Quoting

The end goal of “frictionless business” includes the final checkout. The Bushel research points out while the preference for how a farmer submits their order has remained relatively stable year-over-year, their expectations for what happens before the order has changed.

“Farmers are increasingly adopting digital tools to manage their broader operation, and they are bringing those consumer-level expectations to their retailer,” Eberhart says.

As such, farmers are seeking:

Customized quotes
Product availability transparency
Price comparison tools

And much of that product information available when convenient to them on a portal or a digital storefront.

Support Traditional Payments While Expanding Financing

Eberhart says the State of the Farm has shown how 80% of agribusiness and farmer transaction is done by paper check.

“Over the years, we’ve seen steady growth of digital tools, and reliance on checks being reduced by 1% to 2% every year,” she says.

She says this emphasizes to meet farmers where they are at while simultaneously making it easier for staff to have simplified processes.

Two other financial trends have been in retail supplied financing and farmer credit card use—illustrating how farmers are seeking flexible payment options and new financing or credit programs.

In 2022, over 20% of farmers said they used a credit card to pay for their crop inputs, which fell to 8% in 2024, and then most recently in 2026 2.6% of farmers said they used credit cards.

At the same time, ag retailer financing products have doubled their use since 2022—going from 4.5% to 9%. And 17.3% of farmers said in 2026 they were using operating lines of credits for input purchases.

Key to Business in 2026

Per the Bushel report, the winning formula for ag service providers in 2026 and beyond is clear: Use digital tools to handle the paperwork so your team has more time to handle the handshake.

How AI Insights are Reducing Manual Scouting for Midwest Retailers

Fri, 24 Apr 2026 11:15:12 GMT

Recently, Syngenta and Taranis declared their AI-backed partnership a winner as it combined their respective prowess in leading crop protection and AI crop intelligence for retailers and farmers in the Midwest.

Syngenta’s leadership pointed to AI as agriculture’s next major breakthrough, with early results from the 2025 collaboration demonstrating how pairing Taranis’ leaf-level AI Crop Intelligence with Syngenta’s portfolio helped create value for retailers and growers—momentum that the partnership is now positioned to scale.

“Over the past two years, we’ve been intentional about keeping a pulse on growers’ pain points and making practical improvements to enhance their experience,” says Paul Backman, Syngenta’s Head of North America Crop Protection Digital Agriculture & Sustainable Solutions. “With the help of AI, technical expertise, and strong partnerships, we are enabling growers to spot issues and respond with solutions faster than they have before.”

Ag Retailers: At the Frontline Connecting Growers to Solutions

As the new growing season kicks off for the Midwest, Syngenta’s teams say they are taking off the training wheels and anticipating the program’s success in the retail sector to be the foundation for its growth.

“We believe ag retailers play a critical role in bringing conservation solutions together for growers,” says Backman. “The powerful capabilities brought together through our partnership with Taranis put us in an excellent position to collaborate with retailers and create value for them as we deliver on this vision.”

Early insights from the field signal momentum. Retailer enrollment continues to accelerate, with participating acres expanding rapidly throughout the Midwest.

“We’ve worked to scale the partnership more broadly in our second year – this means connecting AI Crop Intelligence with our Crop Protection portfolio and bringing these solutions to more retailers,” he says. “The results from our first year together demonstrated a clear benefit for growers to be more targeted and to address field issues earlier – helping growers and retailers be more efficient in pinpointing challenges and the right solutions to address them.”

Now, the company says that the program is optimized with data-backed intelligence for corn and soybean producers, and in the early stages of exploring its applications in potato production as well.

A Win-Win to Unlock Conservation Opportunity

Geography and crops are not the only expansion on the table for 2026, Backman says. The partnership is working to help growers enhance profitability and access to conservation funding and technical assistance by matching farmers with public conservation programs and working collaboratively through the enrollment process.

“We know that turning a profit and having the funds to invest in new practices can be one of the biggest barriers growers face when deciding whether to adopt a new practice,” Backman says. “This, in essence, is what makes Syngenta’s partnership with Taranis a real game changer.”

Through the partnership, Taranis Technical Service Providers will identify opportunities to access funding through popular federal mechanisms like the Conservation Stewardship Program (CSP) and Environmental Quality Incentives Program (EQIP). “The Taranis Conservation Partnership solution is designed to help growers access USDA conservation funding and implement sustainable farming practices on their farms with minimum effort,” he says.

Backman also notes that smooth enrollment isn’t just a convenience – it’s key to enabling growers to access resources to invest in their operations and experiment with new practices that might otherwise be out of reach.

“We see it as a win-win for all parties involved,” he says.

Sustainability, Driven by Digital Tools

AI-powered intelligence from Taranis is the latest capability offered alongside Syngenta’s suite of digital tools that underpin its corporate sustainability strategy .

“Syngenta has a long history of supporting growers to help increase yields, and today we’re leaning into a broad portfolio of digital tools to meet that mission,” Backman says. “Over time, we’ve learned that leveraging crop protection and advancing sustainability can go forward together.”

This AI-backed partnership, along with digital sustainability tools such as the CropWise™ Sustainability App, are critical levers to achieving Syngenta’s overall sustainability goals – one of several reasons the company combined the two into a new Digital and Sustainable Solutions team.

Backman’s team is charged with finding solutions that work at the farmgate, but also help to manage productivity, profitability, and stewardship.

“A key to meeting these goals and scaling sustainable practices starts with solutions that truly work for farmers, which is why we’re embedding sustainability into our business strategy and operations and equipping our field teams with resources to communicate how our solutions support those efforts,” he says. “While technology has long helped farmers increase yields, today we’re combining it with sustainable practices to help achieve higher yields with lower impact.

“By improving soil health, protecting biodiversity and conserving natural resources, we can help create lasting value – ensuring that growers succeed today, and well into the future.”

Farmers Don’t Use AI for Answers — They Use It to Think Better

Fri, 17 Apr 2026 15:10:22 GMT

What you should know:

To use artificial intelligence in your business for a competitive advantage — not just a gimmick:

Ask better questions than most people
Combine AI with real-world experience
Execute on the answers

For Rachael Sharp, dry weather hasn’t made planting go any easier in the Lowcountry of South Carolina. And when a planter went down, the first thing she did was pull up Chat GPT.

“I pulled up the part number, and I saw that I’d actually entered in there last year. So it told me the date I changed it, and that was helpful, because I was trying to figure out why is this wearing out so quickly?” she says. “We’re in desperate need of rain, and we’re pulling in some pretty hard non-irrigated land right now. I logged that we changed the bearing again, and so next time, knock on wood, it hopefully doesn’t go out again, but if it does I can look and see I changed it twice in the last year.”

That’s just one of many examples of how Sharp is using ChatGPT to manage equipment, her time, and the farm business. She and her father, Don, are featured in an OpenAI commercial, which premiered during the Super Bowl.

And she’s in good company with other farmers in how to use the artificial intelligence platforms.

Marc Arnusch, the 2025 Top Producer of the Year, says ChatGPT is the most used app on his phone.

Jeremy Jack, leader of Silent Shade Planting Company the 2023 Top Producer of the Year, uses AI as his daily management teammate from agronomy and business decisions.

Here are the four ways these farmers use AI every day on the farm.

(Photo: Yvonne Min)

1. Make better decisions faster

Colorado farmer Arnusch uses ChatGPT and Grok to narrow down his consideration set when making decisions.

“It helps on the strategic side of things, and when making a decision, I’ll let it give the top four or five things to choose from, which helps when there’s a million choices,” he says. “It really is like my funnel. I’ll set up my phone on my dashboard and just dictate to it. Then when I’m back at the farm office, my wife Jill is relieved because I’ve already processed out loud with the AI tool.”

While most farms collect data, Jack uses AI to make decisions, particularly agronomic.

“I uploaded multiple years of soil data across our farms,” he says. “And we’ve found ways to manage fertilizer better, for example with sulfur.”

The data interpretation has shifted his thinking by connecting the yield zones with as-applied fertility and return on investment.

Jack is also using the technology to double check every spray application — from rates, to tank mix, to nozzle selection, to pressure optimization.

Sharp has also found AI helpful in managing chemical applications. She can remember chemical boxes marked up with her father’s calculations by hand.

“I tell the prompt what I’m spraying, where I’m spraying, how many acres, tank size, and then I let it tell me what to order,” she says. “Over time, it’s learned which products are liquid and which are dry flowables. And it’s helped me keep track of the inventory we have so we don’t end up with pallets of odds and ends.”

(Photo: OpenAI)

2. Be more efficient

When it comes to where to start with AI, Sharp has one piece of advice.

“Think of the task that you don’t like to do at the end of the day. For me, I didn’t want to do paperwork at the end of the day,” she says. “So I threw it over to ChatGPT, and I said, hey, this is what I planted today, this is the date, and I left it at that. I started really, really simple.”

Now, she’ll record things directly in the field or in the truck. She says it has helped with FSA 578 forms. And in day-to-day operations, she’s found benefits for time management and accuracy in all record keeping.

“We have seed samples that require a handwritten seed form that I turn in along with the sample, but I spoke into my phone and said, hey, Chat GPT, I need you to log that I sent this variety, this lot number, on this date, to the lab. And so, that’s probably one of 15 entries that I’ve made over the course of a month. And at the end when we finally turn in our last sample to the lab, I’ll ask it for a spreadsheet with all that listed,” she says.

(Photo: Sarah Green Photography)

3. Think more clearly about complex problems

Jeremy Jack often asks ChatGPT “What does this mean for my farm?” with current events.

“With the war in Iran, global fertilizer supply chain concerns, and even things like USDA reports, it’s given helpful perspective in how to think about what’s happening off the farm but impacts the farm.”

And he’s found success in using the platform to specifically think about the business strategy for his farm with vendors, including lenders, landowners and more.

4. Manage more professionally

Jack has been active with an advisory board for their farm, but AI has become like a boardroom in his pocket.

“I bounce ideas—pressure test if you will—before it costs me real money,” he says. “This includes input purchases, land agreements, and equipment purchases.”

He’s also come to use it in his external communications about the farm including his regular social media posts on LinkedIn.

When it comes to team management, Arnusch has input culture index results for vendors and employees, then the AI compares their individual characteristics with the job they are being asked to do.

“This has been a breakthrough,” he says. “It’s shown me that at no fault of their own, why some people fail at what they are being asked to do. It wasn’t because they weren’t working hard or doing the job. It was stretching them beyond what they can do.”

He gives the example of a farm foreman position on the farm, and how he used this process to match the candidate with the role.

(Sarah Green Photography)

How Growmark’s New AI Agronomy Agent Turns Data Overload into Field-Level Wins

Wed, 15 Apr 2026 17:21:16 GMT

“When we look at who we need to be for our farmer customers in 2035, technology has to be at the core,” says Brendan Bachman, FS agronomy director. “I don’t think we see it as an option. We have to embrace technology for who we need to become in the next 10 years.”

As such, Growmark is embedding AI into the myFS Agronomy platform. The “AI Agronomy Agent” is a specialized tool built on the Anthropic Claude model, customized with Growmark’s proprietary data and Intelinair’s interface.

The Data Inflection Point

Agriculture has moved from a lack of data to “paralysis by analysis.” Growmark is acting now to turn decades of raw data into “decision aids” to manage risk and associate value.

The AI Agronomy Agent is designed to act as a digital assistant for the crop specialist, and will be exclusively available to FS crop specialists for 2026.

“It doesn’t take out the art of agronomy. Because it allows the FS crop specialists to create their own ecosystem of tools and technology to apply the agronomic recommendations that they’ve seen justified,” Bachman says. “And we’re training our team to be cautionary about just taking what the AI tools as the gospel and applying that to a farmer’s field without any critical thought process from a professional agronomic lens.”

The technology supports, rather than replaces, human expertise.

Speed to Insight

The “why” is driven by efficiency. Processes that previously took hours or days of manual data cleaning now take minutes, allowing agronomists to spend more time on strategy and less on spreadsheets. The AI tool uses planting, weather, environmental models, as-applied information, in-season crop insights, yield information, soil test information, as well as many different source materials on management practices.

Benefits from the tool include:

Automated Decision Insights.
The AI replaces the need for “hard-coded” software. For example, it can recreate the “FS Profit Maximizer” break-even analysis on the fly in minutes using real-time data.
Gap Analysis & Hybrid Positioning
The tool uses millions of acres of spatial data to perform “gap analysis"—showing farmers not just what performed best on their farm, but which hybrids in the region would have outperformed their current top choices by 10+ bushels.

(Growmark)

This AI announced is on the heels of the app’s Yield Estimation Tool, which can help predict yield within 5% at the field level yield in July-August and was also the result of a partnership with Intelinair. Bachman says the team has seen great benefits provided to farmers with that tool because it gives farmers another month or two-and-a-half months in their marketing strategy based on its yield prediction on their total production.

(Growmark)

Viewing 2035 As the Goal

The MyFS Agronomy app was launched two years ago with now 98% of FS companies using the platform and more than 5,000 users.

To remain relevant to the next generation of farmers, Growmark believes they must “disrupt themselves” today to build the technology-core required for 2035.

“As I look forward, what excites me the most is for people to really start to embrace the change because we are at a point of inflection, and how we have historically done agronomy is not going to change. Good agronomy is always going to be good agronomy. But what data we use to inform the right decision on that farming acre, just got accelerated,” Bachman says. “And it’s no longer about hard-coding features and functionalities, it’s about feeding the AI the model and asking the question, and having it bring about the value outputs that matter to the individual user.”

Bachman says the team at Growmark believes in their tech-forward strategy not as an optional add-on, but as a fundamental requirement for the future of the cooperative system. And for the 2026 season, this advanced AI functionality is being included at no additional cost to FS member companies, framed as a “progressionary add” or standard upgrade to their existing cooperative technology suite.

The New Ag Economy: Why This Downturn is a Structural Shift, Not Just a Cycle

Mon, 13 Apr 2026 21:22:19 GMT

What You Need to Know:

Structural Evolution: This downturn is a permanent market shift, not just a temporary cycle.
Friend-Shoring: Trade is moving toward geopolitical allies to ensure supply chain resilience.
Aggressive Cost-Cutting: Farmers are doubling generic input use and delaying machinery purchases to protect margins.
Financial Resilience: Better management and working capital make today far more stable than the 1980s.
Premium Protein Demand: GLP-1 medications are driving consumers toward smaller, higher-quality meat portions

As the industry enters the third year of this downturn, farmers and agribusinesses are questioning if a recovery is on the two-year horizon. While cyclical behavior is normal, two economists suggest the structural evolution within crop protection, machinery, technology, livestock and other individual sectors is creating a different kind of staying power for those who survive the recovery.

The Evolution of the Cycle

When characterizing the current economic cycle in agriculture, historical patterns provide a necessary baseline, yet the present landscape is defined by unique pressures. Typical agricultural cycles consist of roughly six years of expansion followed by four years of decline. Currently, the market is navigating a “corrective period,” returning to long-run averages.

The drivers of growth are typically demand shocks — export surges, fuel demand or policy shifts such as the Renewable Fuel Standard. However, Wes Davis, ag economist at Meridian Ag Advisors, notes the current environment is an intersection of traditional contraction and sector-specific evolution.

“What I think we’re experiencing right now is that typical cycle behavior where we see growth in some business firms, and then some contraction and pullback to adjust to the cycle going back to more of the long-run average,” Davis explains. “I think we’re also seeing evolution of individual sectors within the market where there’s adjustments happening because of the industry itself.”

In other words, this isn’t just a cycle — it’s also a structural shift.

Change Fatigue and Modern Volatility

Farmers aren’t strangers to volatility, but global trade disruptions, policy shifts and rising competition, especially from Brazil, are layering uncertainty onto already volatile markets.
Farmers are grappling with “change fatigue,” a byproduct of the high velocity of information and extreme price swings that dwarf the relative stability of the early 2000s.

“When I go talk to any industry group right now, the phrase that I hear is ‘change fatigue’, and I feel that. Every couple minutes, something shifts,” says Trey Malone, Purdue University ag econ professor. “But to be clear, it’s not that the farm economy isn’t used to volatility, it’s just the uncertainty and the volatility now is, like, ‘hold my beer relative’ to the old volatility.”

Malone attributes this to layers of uncertainty created by global trade and policy. The rise of Brazilian production, coinciding with the disruption of U.S.-China trade relations, has created a permanent state of flux. This sentiment is reflected in the Purdue Ag Economy Barometer, which shares a higher correlation with the Small Business Index (.5) than with actual commodity prices. This suggests farmers view themselves primarily as small business owners facing broad economic pressures rather than just price-takers.

“We don’t see very strong correlations even with lagged soybean prices and corn prices,” Malone notes. “The world is more complicated than just looking at what happened in the market yesterday and gauging how farmers feel.”

Global Competitiveness and the Trade Reallocation

A primary concern for U.S. producers is their position as low-cost providers. While the U.S. maintains an infrastructure advantage that lowers the cost of getting products to export ports, Brazil continues to close the gap.

“It’s a fair question farmers ask a lot: Are we actually the ones who are the low-cost producers, and do we still have a place in the global market if Brazil continues to lower the cost of production and transport their grain to export terminals?” Davis asks.

However, Davis points out that global trade hasn’t shut off; it has reallocated. Only three global regions — North America, Latin America and parts of Southeastern Europe/Central Asia — are net exporters. The rest of the world remains net importers.

“While our trade has kind of shifted around ... that shift has really reallocated stuff in different places. Those calories and products end up going somewhere. It’s just a question of where,” he says.

The Shift to “Friend-Shoring” and Resilient Supply Chains

The industry is moving from “just-in-time” (hyper-lean) procurement to “just-in-case” (inventory-heavy) strategies, a lesson reinforced by the pandemic. This shift is accompanied by “friend-shoring,” where the U.S. prioritizes trade with geopolitical allies.

“We’ve gone from offshoring to onshoring to nearshoring to friendshoring,” Malone explains. “We’ve got a paper that’ll be coming out ... where we document friend-shoring in ag and food supply chains. Over the last 10 years, there’s been a shift where we mostly in the U.S. trade with other people who vote like us in the WTO. That’s kind of one way to measure friends.”

This resilience is also visible in crop protection. In 2019, 80% of active ingredients were sourced from China. Today, that is closer to 60%, with manufacturing shifting to India and domestic sites. Davis calls these “geopolitically resilient” supply chains.

The Rise of Generics and Decision Paralysis

The economic downturn is fundamentally changing the business model for input providers. Farmers are aggressively cutting costs, leading to a massive surge in generic usage.

“The latest survey I saw shows about 60% of farmers use generics today. That was about 30% to 40% just 5 years ago,” Davis says. This forces companies to pivot from differentiation to operational volume.

In the machinery sector, high costs and economic uncertainty have led to “decision paralysis.” Farmers are extending the life of their equipment, treating machinery replacement as the most controllable variable in managing annual ROI. Davis notes the U.S. ag equipment cycle is currently 15 to 20 percentage points lower than typical low points, driven by this hesitation. Furthermore, there is significant skepticism toward subscription-based technology models.

“Farmers don’t terribly love this idea, and I think the other interesting thought here is I’m not sure that retailers like selling them either,” Malone adds.

AI: The “Undergraduate Intern”

While artificial intelligence (AI) is a major talking point, its current role in agriculture is more supportive than transformative. Malone views AI as a “highly capable undergraduate intern” — useful for processing information but incapable of replacing the trust and risk management provided by human advisors.

“I don’t think you need to be replacing your agronomist. I think your mediocre agronomist just got OK,” Malone says, noting while LLMs can pass CCA exams, they cannot manage the risk of a wrong decision. “The risk management value proposition of an in-person Claude, or whoever, is probably going to win out because there’s still a risk.”

Currently, the adoption gap is wide: While 75% of agribusiness managers see potential in AI, only 4% have implemented it, according to a Purdue University survey in 2025.

Livestock and the GLP-1 Impact

The livestock sector is facing a unique demand shift driven by weight-loss medications (GLP-1s). This is leading to “premiumization.” As consumers eat smaller portions, they are opting for higher-quality cuts.

“The explosion in demand for protein is just shocking,” Malone says. “What GLP-1s do to that calorie count is they are all shifting toward premium cuts. You don’t care how much it costs because you’re only going to have seven bites of it. But you’re going to have a steak. That premiumization is going to really, really take off in the next 10 years.”

Conversely, the hype surrounding “fake meat” has largely faded, proving to be more of an investor-led phenomenon than a market-driven one.

Financial Stability: Not the 1980s

Despite the downturn, the financial health of the American farmer remains more stable than during the crisis of the 1980s. Currently, 10% to 12% of farmers are in a “tight” financial position , compared to 20% to 30% in the 80s.

“We do have a completely different, more professional ag workforce than we did back then,” Malone says. “The farm policy we have right now does not necessarily match what we need for the future, but all of these things make me think we’re in a much more stable position.”

Farmers have built-in “shock absorbers,” Davis adds, including off-farm income and working capital built up during the expansion years. However, in his research Davis has seen how alternative financing is becoming a major tool for the 50% of farmers who use it — either to manage stress or, for larger operations, to leverage relationships with retailers.

Strategic Reassessment: Winning at the Bottom

The experts agree the “bottom of the cycle” is the time for professionalization and upskilling. Surviving — and thriving — will require sharper management. It is an opportunity to reassess farm transitions and management disciplines, such as financial management, accounting and planning, which become critical in tight margins.

“Farmers are going to have to get smarter and get more creative with how they manage,” Malone says. “This is a good opportunity to take a step back and think about what the strategy needs to be moving forward.”

Davis emphasizes relationships are solidified during these periods: “Farmers are going to remember the folks who were around when they were in the bottom of the cycle, and who were there to support them. The best farmers will continue to get better ... I get excited about what we can look like as we come out of this cycle.”

So Is This Ag Cycle Different?

These experts say yes as every cycle presents its own unique reshaping of future opportunities.

To download the full report on why this ag cycle is different and what it means for your operation, click here .

‘Farmville for Real:’ How Autonomous Tech is Rebranding Tractor Drivers as Digital Operators

Fri, 10 Apr 2026 20:30:13 GMT

For George Grote, a typical day doesn’t involve a steering wheel or a dusty cab; instead, it looks like he’s glued to his phone or tablet. From the climate-controlled comfort of a pickup or while strolling between the crop rows, Grote monitors a fleet of autonomous tractors as they navigate with precision. It’s a scene that Agtonomy CEO Tim Bucher calls “Farmville for real,” where gripping the steering wheel is being replaced by the quick-twitch reflexes of the gaming generation.

As the agricultural industry grapples with a deepening labor crisis and an aging workforce, companies such as Agtonomy are betting that high-tech autonomy is the key to recruiting Gen Z. By rebranding traditional tractor driving as “digital operation,” the California-based startup is leveraging app-based interfaces to transform farming into a tech career.

Raised on a dairy farm, Bucher coupled his love of agriculture and machinery with a career in the tech field to create the prototype that would become the company’s first autonomous tractor. Today, as a farm owner and father of three, Bucher says it’s not likely his children will return to the farm. With this technology, he hopes to attract the next generation to his farm and the industry.

“The younger generation doesn’t want to be in the dirt and the dust because there are other opportunities for them,” he says.

(Photo provided by George Grote)

The Gaming Advantage: Why “Fast Hands” Matter in the Field

Grote, a 30-year-old field engineer with Agtonomy, does not have a farming background, but he always knew he wanted to work outdoors. He graduated from California Polytechnic State University with a degree in crop and fruit science and now works alongside Agtonomy customers. He says being able to process information on a screen while being fast with his hands is something he picked up from gaming.

“I can tell you [gaming] 100% helped me, being able to toggle between different features in the app and being quick with technology,” Grote says. “If you can play a video game, then you’re more than capable of running five, six, seven or eight tractors at once while sitting in your truck and watching them run autonomously.”

8.14.25_agtonomy-102

(Agtonomy)

Marc Di Pietra, regional service maintenance manager for Treasury Wine Estates , says the cutting-edge technology can help bridge the labor gap, provide upskilling opportunities and reduce physical demands.

“New technologies are making it incredibly dynamic and attractive for younger generations,” Di Pietra says. “With a younger workforce, I expect that evolution to accelerate. There’s a natural comfort with technology, and a willingness to challenge legacy processes, which is critical.”

Adding this technology has been game changing in the wine business, De Pietra says, and it can shape the rest of the agricultural industry as well.

“These technologies allow us to be more precise with our farming, winemaking techniques and sustainability efforts, effectively creating safer environments for our employees, reducing our emissions and producing better quality wines,” he explains.

Agtonomy_George Grote

(Agtonomy)

How Agtonomy Works

At this point, Agtonomy is being used on fruit and nut tree, grapevine, avocado and citrus operations. The company works with Bobcat , specifically the Doosan Bobcat CT 4045, for more versatile utility and maintenance tasks, and Kubota to automate narrow-track diesel tractors, such as the Kubota M5N series.

Agtonomy’s software is embedded into a tractor’s OEM control system at the factory. Outfitted with the technology, the machine can autonomously handle repetitive tasks, such as mowing, spraying and seeding. Using cameras and sensors, tractors can “see” their surroundings, allowing them to navigate rows and avoid obstacles. Sensors and data links also ensure that sprayers or mowers are working at the correct intensity and height. When an issue occurs, a notification is sent to a smartphone and/or tablet, complete with details to help the tractor decide what to do when it deviates from the original instructions.

The New Survival Skill: Build Like a Polymath, Lead Like a CEO

Wed, 08 Apr 2026 13:14:35 GMT

Have you been concerned about jobs being eliminated because of artificial intelligence (AI)? My exhortation is that, now more than ever, if you want to protect your position in the market, your company and your role, you must become more innovative and entrepreneurial with and through AI.

To lead, not just survive but thrive, you must become an AI-driven entrepreneurial polymath.

Some entrepreneurs dedicate their lives to building and scaling a single enterprise, but the most impactful among them — entrepreneurial polymaths (or serial entrepreneurs) — never stop creating. They build multiple ventures, innovate across disciplines and contribute to both industry and society.

Polymath comes from the Greek “polymathēs” — “having learned much.” Historically, polymaths like Leonardo da Vinci and Benjamin Franklin applied mastery across multiple fields. In an entrepreneurial context, a polymath entrepreneur blends adaptability and insatiable curiosity with the commercial instincts to turn knowledge and innovation into enterprises.

Where the typical entrepreneur may invest all energy into one idea, the polymath entrepreneur has a restless drive to solve problems repeatedly. With AI, this isn’t just easier; it has become essential for survival.

The question for you is: Are you a maintainer, a one-venture wonder, or do you have the capacity for ongoing leadership and innovation across multiple pursuits?

Leverage for Leaders

Over my career I have interacted with thousands of CEOs, hundreds of whom have been clients and many who have become friends. The most fascinating and fruitful among them have always been the polymath entrepreneurs.

Whether they wear the title of CEO, founder or simply manager, they are the true engines of progress. They see opportunities others overlook, and in an age of technological disruption and AI, they often find it easy to reinvent industries.

But vision and creativity alone are not enough. As Peter Drucker reminds us, “Entrepreneurship is neither a science nor an art. It is a practice.”

Entrepreneurs often have blind spots in the disciplines of management, strategy, innovation management, implementation, culture, resource allocation, productivity and sustainable value creation. Without these, even a polymath’s brilliance can stall.

One shortcut is leverage: Partner with external strategists who’ve implemented AI-driven innovations across many businesses, so you’re not learning everything the expensive way, through delays, misfires and internal politics.

When partnered with strong functional leadership, however, the polymath entrepreneur becomes nearly unstoppable. Their power multiplies when aligned with:

Operations leadership (chief operating officer/VP of operations) to translate vision into scalable systems.
Financial leadership (chief financial officer) to ensure disciplined capital allocation and risk management.
Specialized expertise (e.g., internal full-time or external consulting or fractional chief marketing officer, chief information officer or chief strategy officer) to deepen customer, technology or domain execution.

As Michael Porter taught: “The essence of strategy is choosing what not to do.” The polymath thrives because they can choose across domains, letting go of the old to seize the new. And as Joseph Schumpeter argued in “Capitalism, Socialism, and Democracy,” the entrepreneur is the true agent of “creative destruction.” The polymath entrepreneur embodies this, not just once, but repeatedly, breaking down old models and building new ones.

Unlike the myth that entrepreneurship is a product of personality or charisma, whether Steve Jobs at Apple, Richard Branson at Virgin or Elon Musk with his many ventures, Drucker insisted that entrepreneurship is a discipline. It can be studied, replicated and managed. What separates polymath entrepreneurs is their repeated ability to master this discipline across domains.

Bottom line: The most successful will be those who will be applying the fast-evolving tools of AI to not just innovate and add new value through the optimization of your organization but also to create new solutions for your customer/market that innovate your industry — and often will create a new sustainable business faster and more value-creating than ever before.

Mark Faust (513-621-8000, mark@em1990.com) works with owners, CEOs and sales managers who want to grow their businesses. You can schedule a free profit improvement session with Mark by visiting calendly.com/markfaust . Read more ideas from him here .

Agronomist in Your Pocket: How AI Is Transforming Global Pest Management

Tue, 07 Apr 2026 18:59:39 GMT

For over a decade, a dedicated team at Iowa State University has been working at the intersection of artificial intelligence and agriculture with a mission to provide farmers with the tools they need to stay ahead of an ever-changing landscape of threats. Led by Arti Singh and Soumik Sarkar, this research has culminated in the development of the PestIDBot, a sophisticated AI companion designed to act as an “expert crop advisor or extension agent in your pocket.”

By combining massive image databases with conversational AI, the team is moving agricultural protection from a reactive struggle to a proactive, precision-based science.

A Decade of Data-Driven Identification

The core of the technology lies in two specialized applications: Insect ID and Weed ID, the result of training massive AI models on staggering amounts of data. The Insect ID app has been trained on 16 million images and can identify roughly 4,000 different species, ranging from common pollinators and predators to invasive threats. Similarly, the Weed ID app utilizes 15 million images to identify 1,600 weed species, including noxious and invasive varieties.

While these models are global in scope, they have been fine-tuned specifically for regions.

“If a farmer in Iowa does a web search on a pest, they might get information relevant to the Southern U.S. that isn’t applicable to an Iowa farmer,” Singh says. By narrowing the model’s focus to local threats and incorporating management practices vetted by University Extension scientists, the tool provides personalized, actionable information tailored to the user’s specific location.

Image of spotted lantern fly egg masses on tree bark is identified in PestIDBot.

(Image courtesy of Iowa State University)

From Identification to Conversation

The true breakthrough of the PestIDBot is the integration of identification with a conversational chatbot. In the field, a farmer can take a real-time photo of an unknown insect or upload an image taken previously. Once the AI identifies the pest — even in early stages, such as egg masses — the chatbot allows the user to ask contextual follow-up questions.

“Rather than searching for a human expert while the clock is ticking, you can ask your first questions directly to the app,” Sarkar says.

Users can inquire about treatment timing, the necessity of spraying or specific management steps based on their observations. For example, if the app identifies the eggs of an invasive species like the spotted lanternfly, it doesn’t just provide taxonomic details; it can advise the user to contact specific state agencies, such as the Iowa Department of Agriculture and Land Stewardship.

Solving the Green-on-Green Challenge

Building an AI that works in a controlled lab is one thing, but the field presents chaotic variables. Sarkar notes that early models lacked the robustness to handle cases like green-on-green (pests on leaves) or brown-on-brown (pests on bark or soil) scenarios. To ensure the system is trustworthy and reliable, the team implemented strict guardrails to prevent hallucinations — where an AI confidently provides an incorrect answer.

These safety measures include out-of-distribution detection, which allows the AI to recognize when it is looking at something it wasn’t trained for (like a human face) and simply say, “I don’t know.” Furthermore, when the model is unsure, it is programmed to provide several likely options rather than a single potentially wrong identification, allowing the farmer to consult with experts using a narrowed set of possibilities.

Shown from left, Iowa State University’s Arti Singh and Soumik Sarkar are part of a team working at the intersection of artificial intelligence and agriculture to provide farmers with the tools they need to stay ahead of an ever-changing landscape of threats.

(Photo courtesy of Iowa State University)

The Global Horizon: The BRIDGE Project

The next frontier for the team is the AI Engage (BRIDGE) project, funded by the National Science Foundation. While insects and weeds are well documented, identifying crop diseases caused by bacteria, viruses and fungi is a much tougher problem due to the limited quality and expert-verified data.

By partnering with researchers in Australia, Japan and India, the team is building a global dataset of disease images. This international collaboration is critical for biosecurity.

“Threats emerging in Africa or Asia will eventually show up on our shores,” Sarkar warns.

By training models on global data now, U.S. farmers can be prepared for future threats before they arrive, shifting the agricultural industry from a reactive stance to a proactive one.

Vision for Sustainable Stewardship

Beyond technical identification, the team is driven by a passion for sustainability and the future of the agricultural workforce. By enabling precision-based farming, the PestIDBot can help farmers pinpoint exactly which part of a field needs treatment. This hyperprecise approach reduces the need for blanket chemical spraying, lowering input costs for farmers while protecting water systems and overall environmental health.

Finally, Singh and Sarkar are using this technology to make “agriculture cool again” for the next generation. Through workshops and gamified modules for K-12 and 4-H youth, they are fostering land stewardship and encouraging young people to see themselves as future innovators in both ag and AI. As Singh reflects, empowering a kid in a front yard to identify an invasive species can be the first step in a statewide defense against agricultural threats.

End the Software Shuffle: How Razor Tracking is Driving Retail Efficiency

Wed, 25 Mar 2026 16:45:04 GMT

For ag retailers, time is the most valuable commodity. The recent integration between Razor Tracking and Agvance Dispatch is designed to give that time back by eliminating the “software shuffle.”

The Bottom Line: Efficiency Equals Dollars

In the heat of the season, every minute counts.

“Every bit of efficiency you can build, every time you can turn around anhydrous tank, every time you can get a new tender truck out with fertilizer quicker, that’s dollars to the bottom line,” says Eric Mauch with Razor Tracking.

By merging visibility of accounting, customer records, and fleet tracking into a single interface, retailers can:

Turn assets faster: Get anhydrous tanks and fertilizer trucks back in the field with less downtime.
Reduce “Tab Fatigue": Eliminate the need to jump between different programs to track an order versus a vehicle.

“We’ve had larger customers ask for this and so far the feedback has been fantastic,” Mauch says.

Key Takeaways for Your Team

Customized Views by Role: Your team sees only what they need. An order prepper stays in the Agvance screen, while a safety manager monitors the fleet in Razor Tracking—yet they are both looking at the same synchronized data.
A “Moat” of Alignment: Since 2020, Razor Tracking has moved away from closed systems. By partnering with John Deere, CNH, and now Agvance, they are creating a connected ecosystem rather than a digital silo.
AI-Driven Innovation: Razor Tracking is using AI to assist development times, reduce feature completion times and simplify the direct customer feedback to meet their needs faster.

“As a business we are looking to serve the needs of existing and new customers. One way to do that is give them new reasons and showing a quick evolution in how we can take a customer request to a delivered product,” Mauch says.

The “So What?”

This isn’t just a software update; it’s a strategy for scalability. As software development moves 10x faster, retailers who adopt these integrated platforms will be able to respond to market demands and customer needs far quicker than those stuck using disconnected legacy systems.

Cultivating Trust: How the Agriculture Industry is Bridging the AI Adoption Gap

Fri, 20 Mar 2026 14:13:55 GMT

For California farmer Joe Del Bosque artificial intelligence was once a foreign concept. Today, he uses AI for autonomous weed control and water management.

According to McKinsey & Company analysis , AI can create economic value by improving labor and input costs as well as yield to the tune of $100 billion and by increasing sales and productivity by as much as $150 billion across the agriculture industry. However, most farmers continue to approach AI with a mixture of cautious optimism and skepticism.

“We have increasing costs all the time, we have challenges with pests and with the climate, so we’re looking for AI to help us,” says Del Bosque, who grows cantaloupe, watermelon, honeydew and Galia melons on 2,000 acres.

It’s crucial for farmers and technology companies to come together to find solutions for some of agriculture’s most pressing concerns with AI, he adds.

Building Trust Through In-Field Results

In her work as chief product officer for Avalo, Inc , a crop development company creating climate-resilient crops, Rebecca White recognizes the investment price tag for technology is a significant barrier for producers. For example, autonomous and robotic systems can cost hundreds of thousands to a million dollars per unit, she says.

That financial scope can heighten caution around new technology – a point addressed at the recent World Agri-Tech event. As industry leaders emphasize, for trust to form, the technology must first prove its reliability in the field.

Bridging the Gap Between Data and Action

AI requires data – and lots of it. The council for Agricultural Science and Technology explains data is, “commonly fragmented, distributed, heterogeneous and incompatible,” which makes it challenging to use in a way that can be readily analyzed with AI.

The real value in data lies in how it’s returned to the producer, says Ryan Gilbert, a consultant with Deep Root Strategies LLC , a company that drives innovation in agriculture through adopting new forms of technology.

“The foundation [of success] is the data being generated by the companies selling the products and how they deliver that data to farmers to be able to use” Gilbert says. “The question is: What can AI do to actually increase the quality of the information and deliver it when the farmer wants it and in the format they want to achieve the outcomes they need to remain profitable?”

Unlocking AI’s Potential Through Teamwork

The next generation could play a role in building trust. At the Center for Digital Agriculture at the University of Illinois , Jessica Wedow says students are working on several projects that connect AI and agriculture. She says having one foot in each discipline could help form a stronger sense of trust.

If you’re able to involve students who have an understanding of the problems in agriculture and the need for the end users – the farmers and the growers – when building AI-enabled tools that’s a win-win, Wedow explains.

Fredy Diaz, deputy chief data officer for USDA, also believes collaboration, sharing research and insights, will strengthen the role of AI on the farm.

“It is all about teamwork; we’re really big on a partnership between government, industry and academia. It’s something we practice almost every day in my office,” Diaz says.

For example, USDA is working with students from various universities and Amazon Web Services to create technology that solves problems in real-world agriculture.

Beating Decision Fatigue: 3 Practical Applications for AI in Ag Retail

Wed, 11 Mar 2026 15:11:43 GMT

With stressed margins and an overwhelming amount of data, ag retail managers are looking for clarity. Ever.Ag’s Ben Sloan explains how to turn AI into a tool for protecting margins, reducing shrink, and driving real-world ROI.

“There’s so much coming at us. How do we know what the trusted partner or the best solution that’s part of that,” says Ben Sloan at Ever.Ag. “And there’s an opportunity to identify our biggest problems right now, and then which can be solved right now with AI.”

Sloan says the artificial intelligence (AI) tools are available, but first, the most important step in getting started is making sure businesses are asking the right questions—that’s what leads to the right answers. Here are some examples.

3 areas in the ag retail business where AI can be applied:

Showcase and share knowledge
Automate work
Identify gaps in the business

Spread Tribal Knowledge, Strengthen Teams

“I often hear, ‘John’s our guy at this location who takes care of us,’” Sloan says. “There’s immense benefits to share that tribal knowledge programmatically via these tools.”
As an example, new team members can use AI agents to upskill their knowledge faster. This helps flush out unwritten practices or insider, generational know-how.

A requirement to get there is capturing daily interactions of your team every day. This provides the repository to train the AI on and then build from.

Do More Value-Driven Work, Faster

“AI can automate the components of grunt work, or busy work, that is really about leveraging efficiency,” Sloan says. “It creates more capacity on a per-person basis because you can automate components.”

He adds Ever.Ag is promoting it’s retail customers keep humans ‘in the loop’ for now as they build these systems to ensure accuracy and is encouraging a crawl, walk, run approach.

Where You’re Missing Opportunities

With a handful of examples, Sloan says identifying gaps in the business and helping retailers address those is giving real-world ROI on investments in AI.

One is through an Inventory Insights product built for Merchant Ag ERP currently being piloted by five ag retail businesses.

“We looked at the problem of shrink, and if a standard U.S. business would have a shrink of 1-2% a year, if you’re a $100 million business, 1% shrink is $1 million. There’s a lot of juice to squeeze here as a result,” Sloan. “So we singularly apply an agent toward it,broke it down into three discrete problems, and then chained all those agents together to create a workflow for the user.”

This includes:

Demand forecasting
In-season management
Post-season inventories/end of season balances

“We can give the right insight for the type of problem we’re looking to build upon with a timeline for those items. So based on what you did in-season, it maybe changes the demand forecasting,” he says. “It’s how can we curate the right data based on the context to get to the agent to deliver an insight.”

That’s one example of how AI agents are informing workflows and giving customers actionable insights.

Another example is in Roger, Ever.Ag’s agribusiness logistics software. With repeatability in loads from week to week, AI can help simplify workloads by automating dispatches set to be confirmed by the human staff member.

“Just as simple as creating copies, it’s a 4x to 5x reduction in the time it takes to do the same task in the workflow,” he says.

For agronomics, Ever.Ag’s FieldAlytics is deploying AI to give prompts, apply standards, and output insights. And customers who use multiple Ever.Ag products can layer those applications.
“Take FieldAlytics and Merchant Ag, there’s new insights that we can generate because we can connect those two datasets for that customer if the appropriate permissions are defined,” Sloan says. “I very much believe in the capabilities that Agentic tools are presenting themselves near term.”

AI Provides Unique Insights to Individual Businesses

Building on the adage that “when you’ve seen one co-op, you’ve seen one co-op,” Sloan says it’s powerful when a retail business applies its own data in these case studies and applications of the tools available.

“Everyone is delivering fertilizer, selling seed, applying things, but we all do it just a little bit differently. And I believe integrating both the work aspect, but then the customer’s own internal SOPs will really bring value to the customer base,” he says.

How to Use AI for More Results and Less Busywork

Mon, 09 Mar 2026 15:01:07 GMT

Most leaders don’t have a time problem. They have a throughput problem.

And in ag retail, throughput isn’t just paperwork. It’s quoting, planning, advising, documenting, staffing, dispatching, explaining, following up and reconciling, while your customers are trying to farm smarter with tighter labor, tighter margins and higher expectations for speed and precision.

That’s why smart farming isn’t only about sensors, imagery and variable-rate scripts. It’s also about smart work, how quickly your retail team can turn data into decisions — and decisions into action.

Here’s a provocative thought: If you want to double white-collar productivity, you must IDEA 70% of your workflow. The same logic behind compounding in finance applies here: Real gains don’t come from heroics; they come from a repeatable operating system that moves work through your organization without dropped balls, confusion or rework.

And today, the “A” in IDEA, Automate, has a new horsepower behind it: artificial intelligence.

AI isn’t replacing agronomists, ops managers or account reps. It’s replacing the busywork that steals their best hours, drafting, summarizing, searching, reformatting, re-explaining, re-creating and re-keying. Done well, AI becomes the second set of hands every stretched team wishes they had. That’s a big deal for ag retail, and it’s why now is the time to embrace it.

The IDEA System (Now Supercharged by AI)

IDEA provides a simple operating system for leverage:

Innovate — improve the method
Delegate — move ownership to the right person
Eliminate — stop doing low-value work
Automate — let systems do repeatable tasks

Delegation is the hinge. Done right, it creates leverage. Done wrong, it creates delegation debt, which is your future self paying for today’s vagueness.

AI helps in a surprising way: It makes delegation clearer, faster and more consistent, because it can turn fuzzy thoughts into written outcomes, checklists, drafts and definition-of-done language in minutes.

The IDEA Delegation System (Simple. Written. Repeatable.)

Step 0: Run the Drucker Filter (60 seconds)

Before you delegate anything, ask:

What result am I responsible for? (not tasks, results)
Is this the highest-value use of my time?
Who is closest to the work and can own the outcome?

Where AI fits: Use it as a clarity engine. If you can’t state the outcome crisply, you can’t delegate it cleanly. Try prompts like: “Turn this goal into a clear outcome, definition of done, constraints and a three-step plan.” The value isn’t cool tech. The value is speed to clarity, and speed matters when customers want answers now.

Step 1: Delegate in writing (clarity beats charisma)

In a short message, include the outcome, why it matters, definition of done, constraints, due date, an interim check-in and authority level (decide/recommend/execute with approval). This prevents the No. 1 delegation failure: The leader thinks they delegated a result, but the teammate heard a vague suggestion.

Where AI fits: AI turns “tribal knowledge” into repeatable instructions. It can convert a customer call recap into a clean follow-up email and next steps, turn a product program into a one-page cheat sheet or generate consistent field-visit summaries across reps. That’s how you scale communication quality, not just volume.

Step 2: Confirm understanding verbally (tone tells the truth)

A two- to five-minute check-in saves a week of rework. Ask: “Tell me what success looks like,” “What could block you?” and “Confirm your first step.”

Where AI fits: Generate a fast alignment brief for the check-in — “List the top risks, missing inputs and decisions needed.” AI helps managers manage better, not just faster.

Step 3: Follow up before the due date (support plus subtle reminder)

Put a short check-in on the calendar before the deadline. Best question: “Any roadblocks? Do you need resources, access or a decision?” Then request a “progress artifact” (draft, outline, screenshot, three bullets). This removes friction (the real bottleneck) and brings the task back to top of mind without nagging.

Where AI fits: AI turns raw progress into usable artifacts, customer-ready summaries, pros/cons options or readable narratives from scattered inputs. Smart farming creates more data; data only matters when it becomes decisions.

Step 4: Reward completion (make wins visible)

Delegation scales when people feel ownership and appreciation. Offer public praise for outcomes, private thanks for effort and judgment and a quick “what worked/what to improve.”

Where AI fits: Capture the learning. Ask AI to create a short SOP from what you just did, steps, templates and common pitfalls. That’s institutional memory, and it stops you from reinventing the wheel every season.

Why Ag Retail Should Embrace AI Now

Smart farming is accelerating, and ag retail sits in the middle of the action, between products, practices, performance and proof. AI is a practical answer since it can:

compress cycle time (faster quotes, faster follow-ups, faster internal handoffs).
raise consistency (standardized communication, documentation, customer messaging).
expand capacity without immediately expanding headcount (workforce augmentation).

The organizations that win with AI will be the ones who build a simple operating system for how workflows, IDEA, then plug AI into the repeatable parts.

A Practical 90-Day AI Pilot for Ag Retail

If you want traction fast, don’t start with “AI strategy.” Start with three workflows that are high-volume, repeatable and annoying:

Customer communication: call recap → clean email → next steps → CRM note
Internal alignment: meeting notes → action list → owners → due dates → follow-up prompts
Agronomy/ops documents: program summary → one-page SOP → talk track → customer FAQ

Two rules: human-in-the-loop (AI drafts; your people decide) and data discipline (don’t paste sensitive customer data into unapproved tools).

The Payoff

In a smart-farming world, ag retail’s edge will come from speed, clarity and execution, not just products on a truck. AI is now the most practical lever to increase that edge, because it helps good teams act like great teams.

Heroes burn out. Systems scale. And the smartest systems are learning to work with AI.

How to Bridge the Gap From AI to ROI

Wed, 25 Feb 2026 14:47:47 GMT

Conversations around whether artificial intelligence (AI) could genuinely transform farming are beginning to feel familiar: another technology elevated to savior status before the hard realities set in.

The point isn’t to dismiss AI, but to put it to work in the right way.

In ag retail, the biggest gains will come from disciplined execution: clean data, clear workflows and people who trust the tools they’re being asked to use. Some great examples already exist where AI is working in the field, like Winfield United’s Oz AI copilot that helps agronomists retain institutional knowledge and serve farmers better or John Deere’s See & Spray technology, which covered 5 million acres last season.

Market researchers project AI in agriculture will reach $7 billion to $9.5 billion by 2030. Some applications are delivering real, measurable ROI right now. John Deere’s See & Spray doesn’t just save herbicide; in Iowa State trials across five soybean fields, it averaged 76% reduction in herbicide applications. WinField’s Advanced Acre Rx programs show strong returns, with their Impact Rx program delivering 9.8 bu.-per-acre yield gains. Nutrien’s Echelon platform claims at least 5% yield increases while optimizing for sustainability.

These successes share something critical. They work with existing data or collect their own in real-time. See & Spray doesn’t need your historical yield maps; it identifies weeds as the sprayer rolls. Drone scouting doesn’t require five years of pest records; it spots problems in this year’s crop. WinField’s Oz copilot taps into existing product knowledge, not farmer field histories.

But here’s the disconnect: Most farmers have struggled to maintain consecutive years of quality field data. AI’s biggest transformational opportunities, things such as predictive field-by-field recommendations and AI-optimized variable-rate prescriptions, hinge on access to such elusive data.

Worth Remembering

When Monsanto unveiled FieldScripts in 2012, the promise was compelling: variable-rate seeding prescriptions that would match specific corn hybrids to field conditions within management zones, optimizing populations for 5 to 10 bu.-per-acre yield increases. At $10 per acre delivered through certified dealers, it looked like agriculture’s future had arrived.

There was just one problem. FieldScripts required a minimum of two years of yield data covering at least 85% of each field, recent grid soil samples, and years without abnormal weather events. The data had to be farmer-owned; if it had been exported to a third party, it couldn’t be used.

The reality was that the data was on obsolete PC cards and misplaced USB drives or it had been lost because of equipment trades. Some existed on paper, but digitally it was worthless. By compromising on data quality to salvage FieldScripts enrollment numbers, the prescriptions failed to deliver.

The lesson seemed clear: Don’t build prescriptive services on data infrastructure that doesn’t exist.

History Repeating

In 2026, the data problem hasn’t been solved; it’s actually gotten worse, particularly for ag retailers.

A CropLife/Purdue Precision Agriculture Dealership Survey shows that among 93 Midwest ag retailers surveyed in 2025, the classic precision services AI-driven tools depend on are in decline.

The latest CropLife/Purdue Precision Agriculture Dealership Survey tells a troubling story. Among 93 Midwest agricultural retailers surveyed in 2025, the classic precision services that AI-driven tools depend on are in decline — precision soil sampling most dramatically, dropping from 92% of dealers offering it in 2019 to just 62% today. VRT seeding prescriptions and yield data analysis have followed a similar trajectory, each falling roughly 24 points from their peaks around 2020.

The reasons are mundane, not mysterious: Dealers can’t find the people to deliver these services and can’t charge enough to make them profitable, and their customers can’t afford them. It’s a squeeze from both sides of the counter, and it’s happening just as the industry is promising AI will revolutionize what precision agriculture can do.

Today’s AI tools demand even more data than FieldScripts did. Experts recommend three to five years of yield data before the information becomes statistically meaningful. You need that much history to distinguish true soil productivity differences from annual weather variability.

But according to Farm Journal’s Trust in Food 2020 research, 62% of farmers don’t use a farm data platform at all, and 28% still store data primarily on paper.

The vicious cycle continues. Farmers collect data they can’t interpret, don’t maintain it because they see no immediate value, can’t provide it when prescriptive tools finally emerge that could use it, and then those tools fail to deliver promised results. Trust erodes further.

Elephant in the Room

Here’s the uncomfortable truth: AI in agriculture hits a brick wall at the farm gate, and it’s not a technology problem; it’s a trust and infrastructure problem.

American Farm Bureau Federation surveys reveal that 59% of farmers are confused about whether current agreements allow technology providers to use their data to market other services back to them, while 77% worry about data being used for regulatory purposes. Farmers compare guarding data to a chef guarding a prized recipe. And 55% don’t know if the contracts they sign indicate they own their data.

From the retailer’s perspective, you can typically access soil test results (if you conducted the sampling), field boundaries and crop types planted. What you usually can’t access? Multiyear yield histories, real-time machine data locked inside OEM platforms, complete historical performance records or any financial information.

The result is AI tools promising personalized recommendations that can’t deliver without data you don’t have access to.

What Must Be Done

The good news is we know what doesn’t work. The hard news is fixing it requires structural change and patience.

First lesson for ag retailers: Don’t promise what the data can’t deliver. Qualify farmers before enrolling them in AI-powered prescription services. Be clear about data requirements and the timeline to results. Have the courage to say “no” when data quality isn’t sufficient. Protecting farmers from disappointing results protects your relationship.

Focus first on AI applications that don’t require historical farmer data, solutions like See & Spray, drone scouting, real-time sensing and agronomist AI assistants. Build trust with solutions that work today before asking for deep data access.

Then invest in the long game. Help farmers establish data collection systems. Provide genuine value during the three- to five-year accumulation period. Position yourself as the trusted data partner, not a data extractor.

According to McKinsey’s 2024 Global Farmer Insights survey, farmers view input distributors as the main influence on technology decisions. That’s your competitive advantage, but only if you earn it.

The Choice Ahead

AI in ag retail has two paths:

Repeat history — Overpromise on insufficient data infrastructure. Disappoint farmers with poor results. Damage trust in technology transformation. Watch adoption stagnate for another decade.
Build it right — Accept that most farmers aren’t ready for AI prescriptions today. Lead with solutions that work now while building data infrastructure in parallel. Earn trust before asking for data. Acknowledge the three- to five-year timeline to transformational AI and plan accordingly.

The technology is ready. The algorithms work. The question is whether we’re willing to do the unglamorous work of building the foundation those algorithms require.

AI won’t fail in agriculture because the math isn’t good enough. It will fail if we repeat history by asking farmers for data they don’t have, to power solutions they can’t trust, promising results that don’t materialize.

Steve Cubbage is a precision ag consultant and farmer from Nevada, Mo. He is the founder of Longitude 94, an agriculture sustainability and technology consulting business.

Companies Team Up To Accelerate Ag Innovation With Artificial Intelligence

Tue, 20 Jan 2026 20:20:35 GMT

SAP SE and Syngenta have announced a multi-year strategic technology partnership designed to bring AI-driven innovation directly to the agricultural sector. For farmers, this means a more modern, data-driven approach to the products and services they rely on daily, from manufacturing and supply chain management to field-level support.

As farmers navigate the complexities of climate variability and global market uncertainty, the partnership aims to bolster the tools available to meet the challenge of feeding a projected 10 billion people by 2050, Syngenta reports. By integrating AI across Syngenta’s operations, the collaboration is positioned to unlock faster innovation and stronger operational resilience that scales to meet the needs of agricultural producers.

“AI is the catalyst for agricultural transformation and has quickly become a core competitive edge for Syngenta,” said Feroz Sheikh, chief information and digital officer, Syngenta Group, in a prepared statement. “Our partnership with SAP is transforming how we run the enterprise, modernizing core operations and unlocking new ways to work — a testament to our commitment to becoming an agriculture company with AI at its core.”

“Syngenta’s transformation sets a benchmark for digital innovation in agriculture,” said Philipp Herzig, chief technology officer at SAP SE, in a statement. “Together, we’re demonstrating how cloud and AI technologies can drive sustainable growth and efficiency in one of the world’s most critical industries. This partnership will help Syngenta future-proof its operations to feed the world responsibly.”

The transformation begins with SAP Cloud ERP Private solutions, modernizing Syngenta’s value chain to ensure the company remains agile and responsive to market shifts. For U.S. farmers, this translates to a more reliable partner capable of weathering volatility and delivering consistent results, Syngenta says.

Through the SAP Business Data Cloud, Syngenta is establishing a unified and secure data foundation essential for real-time decision-making. Combined with SAP Business AI and tools like the Joule Copilot , the company intends to drive operational efficiency and accelerate the development of new technologies. Importantly, this initiative focuses on delivering superior products and services while ensuring farmers maintain control and privacy over their proprietary information.

WinField United Deploys Artificial Intelligence To Improve Its Agronomic Adviser Retention

Wed, 19 Nov 2025 16:17:42 GMT

It takes new solutions to fix problems otherwise yet to be solved. And that’s what WinField United sees as the opportunity to use artificial intelligence to help with team member retention. Specifically, as explained by Leah Anderson President, WinField United and SVP, Land O’Lakes, Inc, one in four retail sales agronomists in their system (Winfield United and its retail owners) churns out of the system every year.

To support their retail agronomists with decision-making and product recommendations, WinField United partnered with Microsoft to take its 800-page Land O’Lakes Crop Protection guide and build a copilot called Oz (named for the abbreviation for Ounce).

When prompted, Oz delivers fast, mobile-friendly responses. It is currently in its pilot phase with expected availability across the entire WinField United network next year.

Anderson says the project has two goals:

Support retail agronomists in their recommendations
Support decisions with a focus on return on investment

“This is about helping our agronomists be as productive and effective as they can be with the time they have,” Anderson says.

She says the Crop Protection Guide has been a valuable resource and making it more accessible with the technology will bring more value from the data sourced from the company’s Innovation Center, Answer Plots and more.

“Especially in this moment when farmers are under so much financial stress, there isn’t an ability to waste a dime on a product spend that’s not going to yield an ROI,” she says. “It’s about how we get the information in the hands of retailers and agronomists and farmers faster, better, so that they have more confidence as they’re making those decisions on their farm and managing their crop every year.”

More AI To Be Embedded In the Business

Anderson says this is phase one for Oz and signs of more of what’s to come from how WinField United uses artificial intelligence. Regarding tools for agronomists, she sees adding predictive analytics, emerging pests and more products and technologies. She sees how AI will be applied on the business side of WinField United as a distributor with logistics and predictive tools for inventories.

“We’ll continue to work on the overall efficiency of how product is flowing and moving,” she says. “We’ll work on getting to a point where, you’re confident the right thing is in the right place at the right time for the right purpose, even before you get the call from the retailer saying they need it.”

And AI has the potential to help transform the logistics of the business to meet the current demand. Speaking to how U.S. farmers typically plant their acres of corn and soybeans in a three-week timespan, the supply chain is “overbuilt” for that small time window.

She continues, “in order to make sure that ultimately farmers have everything they need, all of us, whether it’s retailers or distributors or basic manufacturers, we’re all doing everything we can to build really big piles of stuff and get it out into the country to be ready for whatever it is that the grower’s going to need. My observation about that is that it’s pretty inefficient today. The reality is, there’s too many piles of stuff, and they’re too big. And a lot of times, the piles just get returned back at the end of the season.”

WinField United will experiment in how to use AI to drive more efficiency in their supply chain.

“It really bloats a lot of people’s balance sheets, working capital, with too much inventory. We’re paying too much to store stuff,” she says. “There’s lots of inefficiency that comes from not having a really good demand sensing capability and appropriately designed forecasts. Everybody does their best today. This isn’t being critical in any way, but you think about what AI can start doing for us to be better modeling demand and forecasting, so that we can be smarter about how big those piles of stuff really need to be, and where they need to be.”

She concludes saying AI isn’t about replacing people or talent but rather doing business differently with an aim of doing it better.

“This gives us an opportunity, to show people the power of AI being an and–not an or–not a replacement, but an enhancer,” she says. “And so there’s a piece of this too just getting comfortable with what AI can be and what it can do for all of our shared businesses.”

AgZen, Corteva Team up on AI-Powered, Retrofit Sprayer Tech

Wed, 22 Oct 2025 15:08:47 GMT

AgZen announces an agreement with Corteva to further “explore the commercial potential” of AgZen’s AI-powered crop spraying optimization technology, RealCoverage.

The news comes on the heels of Corteva’s big announcement on Oct. 1 , detailing the crop protection multinational’s plan to split its crop protection and seeds businesses.

AgZen, a tech startup spun out of MIT, is making a name for itself by pioneering feedback optimization for spray applications — a new approach the company thinks has potential to improve farmer outcomes and reduce crop input costs.

(AgZen)

AgZen’s first product, RealCoverage, is a retrofit kit that can be bolted onto any sprayer to measure and optimize the number of drops of agrochemicals applied to crops. The system features a boom-mounted sensor that analyzes the coverage and quality of spray applications in real-time, displaying actionable data to a tablet mounted in the cab. Farmers can use the data to optimize the physical settings on spray rigs, both self-propelled and pull-behind, to increase coverage.

The startup says its system works by leveraging AI and cutting-edge computer vision, and customers have used RealCoverage to save 30% to 50% on input costs.

Farmer Feedback

(AgZen)

Northwest Indiana farmer Bryan Brost slapped a RealCoverage system onto his Hagie STS 16 high-clearance sprayer to use on his waxy corn and soybean crops. He says it has helped boost his spray program efficiency overall by reducing application rates while maintaining optimal coverage throughout his 12,000-acre operation.

“The payback came in the first year,” he tells Farm Journal via text message. “We have increased our acres [covered] per day with less hours on the machine, the operator and the nurse tanks supplying product [to the sprayer].”

Corey McIntosh set the technology loose across his 4,000 acre spread in Missouri Valley, Iowa. He is looking forward to using the data to improve his application efficiency across the board. He’s also letting his neighbors and local retailer in on the secret.

“I was getting a chem shuttle refilled at [the] co-op, these guys have always been complimentary of our weed control, I asked them: ‘What percentage of leaf surface area do you think you are covering with your sprayers?’ One of their best operators said he thought 50% coverage. The salesman next to him said it would definitely be more than 60%,” McIntosh says.

“They were shocked when I told them we were at 9% to 10%, but nobody has had ever had a way to quantify this before,” he adds. “We are really looking forward to making improvements.”

Since launching on the market in 2024, AgZen says it covered more than 970,000 commercial acres of application across the U.S. on row crops and specialty crops.

Your Next Read: Breakthrough Fungicide Delivers White Mold Disease Control in Key Crops

App Delivers Yield Predictions Via Remote Sensing and Artificial Intelligence

Thu, 16 Oct 2025 22:25:13 GMT

With at least 95% accuracy at key estimate timings in late July and early August, Growmark’s myFS agronomy platform gives its retail advisors and farmers new insights. Brendan Bachman, FS Agronomy Director, explains how the tool works and what it means for the future.

“We started the pursuit of what is now the MyFS Agronomy tool back in 2018, and really the mindset was as farmers continued to get better at collecting data it was very much real reality in the fact that we were data-rich and insight-poor. What we’ve tried to do is solve that problem,” Bachman says.

He explains the myFS Agronomy platform aims to be hub for all the data a field generates through the growing season, adding in weather, and additional insights. With technology, he says there’s been a learning curve of what works well, and what doesn’t achieve the quality expected, but in the past seven years, his team has achieved a view of a field via data that factors in the agronomic inputs and outcomes.

“We’re able to do now is really kind of synthesize a crop year in almost real time, utilize remote sensing and different modeling aspects to make some better decisions in season, but ultimately help that farmer really analyze how well their crop performed throughout,” he says. “For example, in a 2025 cropping season to make those appropriate changes going forward into ‘26.”

(Growmark)

The latest agronomic insights being delivered are in-season yield estimates, which are in partnership using Intelinair technology. The company says in late July/early August the application has achieved results with yields of at least 95% accuracy. This past year, FS agronomy teams had 4.9 million acres of farmland monitored through remote sensing (airplanes, drones, and satellites), to generate corn yield estimate data.

Bachman shares how the FS team is bringing this tech to farmers in the latest episode of The Scoop Podcast.

A New Eye In The Sky: High Frequency, Multispectral Satellite Constellation Approaches 2026 Debut

Thu, 11 Sep 2025 19:40:17 GMT

The 2025 crop season has been a solid proving ground for the value and utility of satellite and aerial imagery in farming.

That’s because corn and soybean fields this summer appeared incredibly healthy and high-yielding from the drive-by scouting pass in the pick-up truck, but then crop scouts marched into those same fields , uncovering widespread yield variability and a high level of foliar disease pressure .

EarthDaily (formerly Geosys) says it will soon leverage a new satellite constellation to beat USDA yield forecasts by capturing daily calibrated images of crops and feeding those images through artificial intelligence (AI) tools.

The news

Satellite imagery of a corn field in the U.S. with corresponding NDVI (plant health) and precipitation data all the way back to 2017.

(EarthDaily)

EarthDaily says it intends to provide daily, high-quality aerial data that agronomists, grain traders and commodity brokers can use to get snapshots-in-time for farm fields, without ever having to launch a camera drone or upload thousands of images to stitch together an orthomosaic. Farmers also stand to benefit because the data will be available within many popular farm management information software systems.

The company is in the process of launching a new 10-satellite constellation that will be fully operational by the 2026 cropping season. This constellation is different from other ag-monitoring satellites orbiting the earth in that it will feature a yellow-band index among its impressive 22 spectral bands.

How is it different from other ag satellites?

EarthDaily satellite data showing the crop progress of China’s corn production regions for the last five growing seasons. The 2025 trend line (black) shows higher than historical average crop health.

(EarthDaily)

“Most [ag] satellites do not have an imager to collect the yellow band,” says Nick Ohrtman, key accounts success lead, EarthDaily. “We have a yellow band imager on ours that we’re pretty excited about moving forward, because obviously yellowing is a key indicator of a lot of plant stresses.”

Ohrtman adds the company has yet to get out and ground-truth the yellow-band imagery in the field, but the potential to catch more yield-robbing agronomic issues on the front-end and alert retail agronomists before crops really take a hit is intriguing.

Intriguing, yes. But Ohrtman, a former Iowa farm kid himself who still helps with the family farm when he’s not working in Minneapolis, says it still serves as just a complement to the traditional scouting pass. Nothing will ever replace farmer and/or agronomist boots-on-the-ground, he adds.

“You can’t be in every field every day, walking crops,” Ohrtman says. “But if you are in the field, you’re probably going to know better than I am from a satellite.”

Main takeaways, per EarthDaily:

The EarthDaily Constellation is purpose-built for broad area change detection, with 16 imagers on each bus capturing 22 spectral bands at the same time each day.
The system will be able to deliver AI-ready data that brings speed and accuracy of insights to today’s EO analytics market.
The full constellation will be operational in 2026, though the robustness of the data will not fully align with the crop season until then.
Among its 22 spectral bands, the yellow band, unique to EarthDaily, is valuable for detecting early signs of crop stress.
EarthDaily’s offering begins with data capture, which is then transformed into downstream analytics purpose-built for agriculture.
For farmers, the technology pinpoints when and where attention is needed in the field, predicting crop health and providing actionable insight without constant boots-on-the-ground monitoring.

Your next read: Could USDA Raise Corn Yields in the Report? Is China Buying U.S. Soybeans?

Farm Drone News: AgEagle Multispectral Sensor, GPS Satellite Launched and Rantizo Spins Off Software

Tue, 12 Aug 2025 20:32:33 GMT

AgEagle Aerial Systems Unveils New RedEdge-P Green Camera

(AgEagle Aerial Systems)

AgEagle Aerial Systems announces the launch of its new RedEdge-P Green, a multispectral camera designed to enable precision agriculture from planting to harvest.

AgEagle says farmers that use the new sensor payload can achieve higher yields through quicker interventions both early on and late in the crop cycle. Operators can reduce fertilizer and irrigation inputs and engage in smart harvesting techniques using optimized indices and targeted indices like the Plant Senescence Reflectance Index (PSRI).

Available as a standalone camera or in paired configurations with the original RedEdge-P and the RedEdge-P Blue, users can leverage up to 15 noise-resistant, data-rich spectral bands essential for large-area precision agriculture.

The RedEdge-P Green camera is NDAA-compliant and integrates with multiple drone platforms. Each camera kit includes a Calibrated Reflectance Panel (CRP) and a Downwelling Light Sensor (DLS2) for radiometric calibration.

Production of the RedEdge-P Green camera is underway, and the first units are expected to ship this week. For more information about the RedEdge-P Green visit ageagle.com.

Dutch Startup Launches Largest GPS Network for Drones, Tractors

(Lindsey Pound, iStock)

FreshMiners, a Netherlands-based IOT firm, launched a GPS service that enables accurate positioning for agriculture, construction and drone navigation, according to AgriMarketing.com.

AgriMarketing.com writes that the Dutch company is launching a service for extra-accurate GPS. It is intended for drone pilots, farmers and others. With this new technology, users can correct their GPS positions down to the centimeter. Real-time correction signals are sent to the user’s GPS receiver via a global network of base stations. This correction is essential for applications in agriculture, land surveying and drone navigation, among other things.

A subscription gives users access to the GEODNET network, which, with more than 19,000 base stations in over 140 countries, is now reportedly the largest RTK network in the world.

Read more at AgriMarketing.com.

Missouri Doctoral Student Says Drones Are Fine Tool for Crop Scouting

(Photo by Abbie Lankitus)

Researchers at the University of Missouri have discovered a mix of drones and AI can help farmers measure the health of their corn more efficiently.

Instead of relying on handheld devices, which are slow and impractical for larger fields, the researchers surveyed corn fields in mid-Missouri using drones equipped with special cameras to capture images and data.

After combining the drone images with soil data, the Mizzou researchers used a type of AI known as machine learning to quickly predict the chlorophyll content in the corn leaves of the entire field with great accuracy.

The study was led by Fengkai Tian (pictured above), a Mizzou doctoral student who works in the lab of Jianfeng Zhou, an associate professor in the College of Agriculture, Food and Natural Resources.

Read more from the University of Missouri here.

Rantizo Spin-Off American Autonomy Inc. Says It Can Close the Spray Drone Data Loop

Rantizo is now connected with the John Deere Operations Center through John Deere API services.

(Rantizo)

Ground rig as-applied data has been around for decades, and it comes in handy when you’re tabulating your end of year scorecard to find out which treatments boosted yields and where a spray might have fallen short.

Yet even though spray drones treated over 10 million crop acres in 2024 alone, there’s still a gap that exists in capturing that data and integrating it into your farm management software.

Former Rantizo CEO Mariah Scott, who is now the CEO of a spinoff operation dubbed American Autonomy Inc., says her new outfit’s AcreConnect platform can help close that gap with API connections into John Deere’s Operations Center and more major FMIS platforms.

“We talk to farmers about getting that complete view of your field management, by closing the loop so you understand what’s effective or what’s not,” Scott says. “Most of the farmers we talk to use spray drones and a ground sprayer, and that (as-applied) data from the sprayer goes right into their FMIS account, but with the spray drone it doesn’t always work like that.”

The deal to divest the spray drone operations side of the business was quietly announced on Aug. 1. The Rantizo name, the startup is a pioneering spray drone service provider, still lives on, but now there’s a clean break between the spraying operations and the software on the back end that enables it.

Learn more about the Rantizo-American Autonomy Spinoff over at PRNewswire.

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Artificial Intelligence Joins The Fight Against Weeds, Insects And Disease

Thu, 07 Aug 2025 19:45:30 GMT

The crop protection industry needs a reboot, according to Tony Klemm.

As CEO of Enko, a crop-protection startup, he says the company is taking a different approach to solving one of agriculture’s biggest problems – developing safe, effective and sustainable crop protection products that can be brought to the marketplace faster and more economically.

Traditional discovery pipelines for herbicides, fungicides, insecticides are not keeping pace with real challenges farmers face, such as resistance issues, he told Chip Flory, host of AgriTalk on Thursday.

A 2024 study funded by Crop Life International reports the costs associated with bringing a new active ingredient to major U.S. and European markets now top $300 million. In addition, the survey says the average lead time between the first synthesis of a new crop protection molecule and its subsequent commercial introduction is now over 12 years.

Part of the long development time required is related to regulatory hurdles. “There’s just increasing demand for meeting environmental safety needs, rightfully so,” Klemm says.

A Paradigm Shift
Enko, based in Mystic, Conn., is using artificial intelligence (AI) and a machine learning discovery platform to guide the company’s research and development efforts. Klemm describes the strategy as a paradigm shift from the current industry practices for how small molecule crop protection discovery has been done.

“We use DNA-encoded libraries, and these libraries allow our scientists to explore this massive, diverse chemical space in a very targeted, automated and expansive way,” he says.

The technology allows Enko scientists to look at billions of molecules and screen them for safety and efficacy and, in the process, develop them faster and more economically.

“We still have to take the regulatory journey that, right now, no one’s figured out a way to expedite,” he notes. “But getting to that regulatory queue faster and better on the front side is really what’s bringing us that cost savings, that efficacy and is going to allow for more products to be put into the regulatory queue in a faster manner.”

Progress To Date
So far, Klemm says Enko has delivered about 50 active programs that cover all facets of weeds, insects and disease. Many use novel or new modes of action that Klemm believes will help farmers fight resistance issues, such as herbicide resistance in Palmer amaranth and pigweed.

“We’re really working on how we can bring new modes of action to farmers, give them fresh tools to win that fight. And our chemistries work using fewer active ingredients, from perspective of the load on the acre, so we’re designing safer chemistry for the future,” he says.

Specifically, Klemm says Enko recently announced a new grass herbicide is in the pipeline for the European cereals market for control of black grass. The company also has conducted field trials for corn and soybean products in the U.S. that he anticipates are five to 10 years away from market launch, depending on how long they take to move through regulatory channels.

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Meet The Forge: Kelly Hills Unmanned Puts New Spin on Ag Tech Field Testing

Wed, 02 Jul 2025 21:37:17 GMT

Over the weekend, Kelly Hills Unmanned, a company that says it is dedicated to accelerating multimodal technologies in agriculture and autonomy, announced the launch of The Forge.

It’s being described as a deployment-centered program designed to meld best-in-class ag technologies into new tools that farmers, ranchers and service providers can trust and use for decades to come, according to a press release from the group.

The Forge’s inaugural cohort hopes to bring together a “powerhouse group” of innovators and operators from across the ag technology landscape into a coordinated, systems approach to help growers identify and overcome agronomic issues before they become yield robbers.

The cohort members, or pillars, are:

Precision AI: Developers of real-time drone-based precision spraying systems that reduce chemical inputs and deliver hyper-targeted agronomic action.
Pyka: Builders of autonomous electric aircraft designed for aerial applications, logistics and mission-critical crop operations.
ScanIt Technologies: Experts in using early detection of airborne pathogens to maximize yields and minimize costs.
Heinen Brothers Agra Services: One of the nation’s largest aerial applicators and ag services companies, offering deployment scale and deep field expertise.
Yamaha Precision Agriculture: Pioneers of robotic and aerial technology for small scale, high-efficiency farming.
Drop Flight: Providers of droplet characterization and aircraft calibration tools to optimize spray accuracy and compliance in real-world operations.
Taranis: Global leaders in ultra-high-resolution aerial scouting, delivering precise field-level insights to boost agronomic decision-making.

For more information, head to www.kellyhills.us/the-forge .

Farm Journal reached out to Lukas Koch to pick his brain about this new, novel entrant to the ag tech ecosystem. We first met Koch last year during the Kelly Hills Unmanned summer field day near Seneca, Kan., where his group unveiled the Pyka Pelican Spray drone — at the time the largest, highest-capacity ag spray drone on the market (280-liter capacity). This year Kelly Hills is integrating the Pelican 2 (300-liter capacity, up to 222 acres per hour at 60-foot swath rate) into its aerial application arsenal.

Farm Journal: Would you call this an ag tech incubator or accelerator type of program, and if not, what’s makes The Forge different?

Lukas Koch (LK): “(The Forge) is neither of those, because we’re not taking a cash influx to create an R&D program. What we’re doing is creating new tools with existing technology — if they’re part of plug and play that’s fine, but we don’t care about that. We want to know if the tech has merit and does it fit on the acre, but maybe something with it is not fully there just yet? So, what are we supposed to do with it then? You have a technology and, for example, it can take high-res pictures and identify areas of your fields that need attention, but today the most likely options are using a ground rig or hiring an airplane to manage that in a meaningful way. For that example, we think there’s an opportunity to do that with a small spray drone, but then again the logistics are tough; you have to come back and land and swap out a battery or refill the tank so often. We’re going to take a bunch of existing technologies that already exist, ask them to change nothing and put them to the test — and we’ll push the bounds of what they can do, to make these all work together in a system.”

FJ: How will this all kind of come together and take shape this summer as the program rolls out?

LK: “We have a few drone companies (in the cohort), and there’s a droplet analysis program involved — I thought that was an important piece in analyzing the spray coverage we get. Right now, we have the in-field sensors out in the field to help us ground truth the data we get from overhead. And then the remote sensing piece gives us situational awareness; it tells us where we should be focusing our efforts. And overall, I think, OK, that’s great, but now you still have to make a treatment with either a ground rig or hire an airplane.

(www.KellyHills.us)

“But with our FAA test range (pictured above) that we were approved for last summer within Kelly Hills, now we can autonomously fly to those spots with a drone, either in line of sight or Beyond Visual Line of Sight (BVLOS), and we can make those treatments autonomously. This year, the tool we’re focusing on is true spot spraying BVLOS in corn and soybeans, and then next year hopefully we can make more tools or take that technology that already exists and make it into a tool for a grower, who can sign up for this subscription and buy one of these drones, and now I have a full encompassing suite of tools and I can know for sure what works and what does not work.”

FJ: How can farmers in Kansas learn more and possibly sign up to work with you guys?

LK: “There’s really two ways right now. For anything specific they might want to do, maybe there are some projects they are thinking about, go ahead and ping us on the website , and we’ll get back to you. And the other way is, once we’re done with a set tool or we wrap up our summer series of projects, we plan to make the results and findings available online, kind of like Beck’s Hybrids does with its farm applied research studies. We want people to see what we’re doing and to reach out with their ideas on how we can make better tools inside of The Forge and showcase some of these technologies together in one new product, and growers are very interested in this and would love to understand if they can package these technologies together and make an ROI.”

FJ: You already have this inaugural cohort in place, but are you already thinking about what’s next?

LK: “I have a couple companies that I need to further engage with now that they can see what The Forge is all about. A couple of those are involved in year-over-year (data) modeling technology that can say, OK, help me start to determine this is my pattern, and this is what I did last year; now can you tell me what to do next year and how to create more ROI? And then I think soil is a huge key right now, too. I don’t have any any soil type products in there, and soil sampling is great, but there are some neat companies that are focusing on soil-sensing technology that I think would be interesting to package in there, too. You know, in due time I think we’ll get there.”

Koch says the plan is to unveil many of the insights and results from The Forge at this summer’s Kelly Hills Unmanned Field Day. That event is set for Aug. 19, and you can get registered for it here.

And, just for fun, here’s a video breakdown of the Pyka Pelican 2:

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John Deere-Sentera Tie Up: Here’s What We Know So Far

Fri, 23 May 2025 21:07:32 GMT

John Deere has announced its acquisition of Minnesota-based aerial optics innovator Sentera. Although specific details are few and far between this early in the process, here’s what we know so far:

The two companies have a long history. John Deere was the first enterprise customer Sentera signed onto its system over a decade ago, and the two companies have had an API link in place between Sentera’s drone management software and John Deere’s Operations Center since 2016.
Financial details are not being disclosed. We do know the deal is not subject to any further regulatory or shareholder approvals.
In a similar fashion to the Blue River Technologies and Bear Flag Robotics acquisitions, Sentera will maintain its independence as a free-standing business unit. Once fully integrated into the Deere family, Sentera will operate under the John Deere Intelligent Solutions Group (ISG) framework. Sentera leadership will remain at its St. Paul, Minn., headquarters.
For the time being, no major changes are planned for either company as we head into the heart of the summer crop scouting and spraying season. The two companies anticipate having more details to share about the nuts and bolts of the acquisition this fall.
The two groups are a natural fit. Sentera is aggressively marketing its SmartScripts drone weed mapping program, and the technology is complimentary to John Deere’s Operations Center and its See & Spray and ExactApply application technologies. One driving force behind this deal, Farm Journal is told, is Deere’s motivation to integrate more real-time agronomic data into its Operations Center platform, and Sentera’s aerial data capture capabilities can help make that happen.

(John Deere)

A deal to lift both boats. John Deere has built up a deep bench of artificial intelligence, machine learning and autonomous technology expertise within ISG, and Sentera has a long track record of aerial sensing and camera payload innovation. Considering how many cameras and sensors are included from the factory on new John Deere machines and within its Precision Upgrades retrofit kits, there should be a healthy cross pollination of sensor and camera innovation between Urbandale, Iowa, (where ISG is based) and St. Paul, Minn.
Sentera can help make See & Spray even better. SmartScripts uses drone-based imaging to scan a field and build a weed pressure map which is then loaded onto the sprayer’s in-cab computer. Now the sprayer operator can see exactly where weeds are in the field and focus their spraying efforts there first. There’s also a logistical and planning aspect to SmartScripts: by knowing exactly how many weeds are present in the field, and even what type of weeds are there, an adept operator can have the right active ingredients premixed and the exact amount needed loaded into the tank or staged nearby in a tender truck to keep that sprayer running all day long.

“Farming is becoming a very sensor and data-centric business, and in our opinion, there isn’t anyone doing it at broad scale today better than John Deere,” says Eric Taipale, chief technology officer, Sentera. “The way we can bring these data-driven insights and improve grower outcomes — it’s just what we’ve always been about. It’s what John Deere is all about. There’s such a great mesh between the two cultures, the objectives and the mission of the two organizations.”

Joseph Liefer, global technology marketing lead at John Deere, adds, “We’re excited about how this complements our existing portfolio with See & Spray, and then not just that (product). Now a farmer with an individual nozzle-controlled sprayer from any manufacturer can also leverage this technology. A drone can fly their field, generate a weed map, turn it into a prescription in Operations Center and the machine can go execute the plan. From an ag retailer standpoint, that might have a mixed fleet, and this gives them more tools in the toolbox to do targeted application for growers and help them save on herbicide. We view this deal as complementary to our overall tech strategy.”

Your Next Read: MAHA Report’s Surprising Stance on Glyphosate, Atrazine Explained

Why U.S. Agriculture Needs More AI Investment to Stay Ahead in Global Crop Innovation Race

Tue, 20 May 2025 18:15:48 GMT

Artificial Intelligence (AI) is a key tool in accelerating the discovery, development and manufacturing of new crop protection molecules to fight yield-robbing weeds, pests, and diseases in U.S. farm fields.

The technology helps researchers shorten the discovery window and find new and novel active-ingredient molecules that are much more difficult and expensive to uncover using traditional research methods.

That was among the talking points that emerged from Tuesday’s congressional hearing on AI in farming, held in front of the U.S. House of Representatives Science, Space, and Technology Committee in Washington, D.C.

Related: The New Space Race: Why America Must Focus On AI

At the hearing, key agricultural stakeholders advocated for increasing government investment in AI technology and infrastructure. The group warned Congress that America’s status as a world leader in AI has been usurped by Japan and China, while other rival countries are also gunning for top positions.

Testifying on behalf of U.S. agriculture was Corteva Vice President of Agricultural Solutions Brian Lutz, University of Florida associate professor Chris Swale and University of Illinois assistant professor Boris Camiletti.

“AI is without a doubt one of the most profound technologies ever to be invented,” Lutz said. “We believe there is tremendous opportunity for our government to support and incentivize advanced innovation — including by leveraging the benefits of AI — to benefit American farmers. If we want to win, we need to move smarter and faster than our competition. Corteva believes with the support of our government, we will do exactly that.”

Lutz said researchers at Corteva recently used AI to model how 10,000 different molecules might be used in crop protection, all within a matter of weeks. The Corteva model was able to identify dozens of new potential crop protection molecules that its overworked chemists could not have found otherwise. He said the company is currently testing a handful of these molecules and AI will also play a role in moving the testing phase along more quickly than traditional lab-based methods.

Lutz also told Congress how Corteva scientists have deployed AI technology in its fermentation processes, which the company uses to create what he called “molecules of interest” for evaluation. Over the past few years, Corteva has used AI modeling to engineer various bacterial strains that drive fermentation reactions and optimize reaction conditions, allowing the company to run a manufacturing operation that is as efficient as possible. This application of AI helps Corteva maintain a strong U.S. manufacturing base in the Midwest, Lutz said.

“This is the new face of ag innovation,” he added. “We can accelerate discovery of new classes of crop protection products, like biologicals — nature-based solutions that help farmers grow more food by working alongside traditional crop protection products. With AI, we can begin to predict the incredible diversity of biomolecules and metabolites that are produced by microbes and other organisms, with the goal of unlocking the secrets within plant biology to develop the next generation of safe, highly targeted, nature-inspired products.”

Swale testified to AI’s role in helping researchers on his team find and develop biological-based treatments to combat Asian citrus psyllid, an invasive pest that has left the Florida citrus industry — valued at almost $10 billion just five years ago — teetering on the brink of collapse. Effective synthetic chemicals to manage the Asian citrus psyllid exist, but the regulatory hurdles to get those products onto the market are too high, he said

“We have turned to using AI to help discover chemicals of the natural world because the registration requirements are significantly lower when compared to synthetic insecticides,” Swale said.

Camiletti leads a team of researchers combining plant pathology, remote sensing and AI to help U.S. soybean farmers overcome red crown rot, a soil-borne disease first detected in Illinois soybean fields in 2018.

Illinois has been hit the hardest by the yield-robbing disease, Camiletti said, and the pathogen is spreading rapidly to Indiana, Kentucky and Missouri. The disease is difficult to detect visually, he added, and once symptoms appear it’s often too late for successful remediation.

“My team uses satellite imagery and machine learning to identify red crown rot hot spots, and we train the models with high resolution multi-spectral data to near-infrared bands and use ground observations to teach the algorithm what diseased plants look like,” Camiletti said. “This technology has real on-farm impact. We are building tools that generate prescription maps so instead of applying fungicides across entire fields farmers can target only the affected areas.”

After key witness testimony concluded, the committee opened the floor to questions from members of Congress. Watch the full hearing via the video embedded below:

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Is ‘farming without farmers’ the future of ag?

Fri, 16 May 2025 03:55:40 GMT

The rapid evolution of technology, robotics and artificial intelligence has brought continuous and dramatic change to every industry — including, and perhaps particularly, agriculture. To discuss the growing role of AI across agriculture and the fresh produce industry, The Packer sat down with Rizwan Butt, vice president of product management for iTradeNetwork, in a fireside chat webinar on May 14.

“Imagine a future where we are literally farming without farmers,” Butt said. “And that may sound scary and anxiety-inducing for a lot of people, but … the question we have to ask ourselves is: Are we of those who are going to embrace these realities and adjust and adapt to them, or are we going to be apprehensive about them and try to avoid them for as long as possible?”

Agriculture is already employing robotics to aid in everything from planting to crop protection to harvesting to selecting for quality and much more, Butt said.

“This is not some scientific sci-fi future. This is a reality today that’s being done either in labs or in experiments or actually being deployed in the real world,” he said. “So, there is going to be a point in time where we have to accept the fact that there are going to be machines and AI tools that are going to augment what we do as human beings and make that job much more productive, much safer and much more optimized.”

As demands on the global food supply are expected to increase by 40% to 70%, while at the same time the labor pool continues to shrink, the need for AI in agriculture is real and the time is now.

For more on how AI is helping agricultural supply chains evolve from reactive to predictive as well as how retailers and growers can now anticipate disruptions — whether from weather, demand shifts or logistics breakdowns — and adapt proactively, watch the webinar now.

Watch on demand: Register here to download and watch the webinar

John Deere Challenge: Watch a New York Tech Journalist Farm 20 Acres of Corn for $20 Profit

Fri, 18 Apr 2025 13:52:49 GMT

You might recall this viral stunt from when it was announced last spring: John Deere and tech influencer David Cogen (@TheUnlockr) joined forces to set the New York-based journalist up as a row crop farmer for an entire growing season. Using 20 acres of prime Iowa farmland, Cogen’s mission was to find out if he could accomplish what farmers must achieve to put food on America’s dinner tables: turn planted crops into cold, hard cash.

Unlike most farmers, though, Cogen was basically given every cheat code in the game: He had guidance from John Deere experts throughout the crop journey, all of the latest John Deere equipment with all the tech bells-and-whistles any farmer could dream for —not to mention a blank check for seed, crop inputs, fuel and labor.

Cogen began by ordering up soil tests and custom fertilizer applications. Then he flew back to Iowa to complete the spring tillage pass and seed the field. Next came another trip to spray weeds post-emergence with Deere’s See & Spray smart application system before returning in the fall to harvest the finished grain and haul it down to the local ethanol processing plant.

Along the way Cogen learned a handful of lessons any seasoned farmer already knows all too well:

The weather never seems to do what you want it to do, when you want it to do it. That’s farming.
You have to eradicate weeds or they will rob your yields and destroy your profits.
Variation is the enemy, it’s all about consistent production and harvesting at the precise moisture level and timing.
A dry late-summer and early-fall is a factor you can’t control but it can cost you real dollars on your final yield. The corn will dry down too fast in the field if you don’t get it off on time, so in this case, water is truly money when it comes to corn and soybean farming.

In the end, Cogen’s field averaged 209 bushels per acre and produced just over 3,000 total bushels of corn, which equates to over 200,000 lb.

His total expenses for the year (land costs, seed, fertilizer and “other”) totaled $16,456, while his total revenues for the 19.24 total acres of corn harvested was $16,478.

Don’t adjust your monitor. Yes, you read that right.

The New York tech editor farmed all year long and only brought home $22 in total profit. It just goes to show, turning a profit on only 20 acres is incredibly hard to do. Small acre farmers deserve just as much respect as the big boys.

“Honestly, I hope that like myself, that this has opened your eyes into what it actually takes to farm,” Cogen says at the end of the video. “Just all of the work that goes into it and you can have a new appreciation for farming and for farmers.

Your Next Read: Farmer Finds A Silver Bullet For High Corn Yields

Carbon Robotics adds autonomous tractor solution

Mon, 31 Mar 2025 20:29:21 GMT

In a move to help growers maximize equipment and address labor shortages, Carbon Robotics launched its Carbon AutoTractor, an autonomous solution installed on existing tractors.

Carbon Robotics’ founder and CEO Paul Mikesell says its Carbon AI will power remotely monitored tractors to help specialty crop growers deploy laser weeders for almost around-the-clock production.

“With LaserWeeder, farmers want to run them as much as they possibly can, but it’s hard to find labor,” he told The Packer. “It’s really hard to find labor to do the tractor driving. It’s hard to find labor to do these late midnight shifts. It’s hard to find people to do all the different tasks you want to do with the tractors.”

The Carbon AutoTractor features two core components: the Carbon Autonomy Kit and the Remote Operations Control Center. Mikesell said operators in ROCC handle any obstructions through monitored autonomy and take over the autonomy system, so production continues. He said growers, then, don’t have to worry whether an autonomous task gets completed.

“They’re trained in using Carbon Auto Tractor,” he said. “They know how to do the functions that the farmer wants to do in the field. And then, whenever there’s something that comes up, they can literally change drive the tractor remotely, and get through whatever obstacle it is, and then keep moving.”

Mikesell said the Carbon Auto Tractor will currently work for LaserWeeder tasks, ground prep such as mulching, mowing, discing and more, but there are plans to expand its capabilities in the future.

The Carbon Autonomy Kit is initially compatible with John Deere 6R and 8R Series tractors, requiring no permanent modifications and installation completed in less than 24 hours. Once installed, tractors can toggle between autonomous and manual operation as needed.

“It bolts on and then that you plug into the harness in the inside on the inside cab, and there’s a box that mounts on the window that you can turn it on and off,” Mikesell said.

The Carbon AutoTractor system includes RTK-accurate GPS, 360-degree cameras and radar-based safety sensors, as well asphysical, remote and mobile e-stops connected via a high-speed, low-latency satellite link.

“We have better visibility from the cameras on the roof than you do from the inside the cabin,” Mikesell said.

And for those growers who might be reluctant to go to an autonomous tractor, Mikesell said the Carbon AutoTractor is designed to help growers better deploy farm labor where it’s needed most.

“You want somebody there to inspect or notice problems with your irrigation or things of that nature. You’ll still want to have those people around, but the point is that they don’t have to spend all that time driving up and down the rows to do the simple task,” he said. “They can then spend their time focusing on figuring out where or if there’s issues and how to address other problems and it relieves the constant need to be driving the tractor all the time.”

Mikesell said this solution also offers growers the option to deploy tractors at night for weeding or when the nighttime temperatures are cooler. This also helps growers maximize return on investment by being able to run the autonomous solution all the time, he said.

“We found that lot of people want to run their LaserWeeder 24/7 because they get a really good ROI or more crops they can put it under, but they just can’t find the operators to run it 24/7,” he told The Packer. “If you can run it, 24/7, you can double the hours in a typical season and you can get that tool doing everything you need it to.”

Carbon Robotics said the autonomous solution works seamlessly with its LaserWeeder, automatically adjusting speed to optimize weeding performance based on weed type, size and density, which can boost coverage by up to 20% compared to manually operated systems.

Brandon Munn, farm manager with Columbia Basin Onion, has worked with the Carbon Robotics team on this autonomous solution.

“With many of our tractors and LaserWeeders running autonomously with Carbon AutoTractor, we’re able to operate more hours, address labor challenges and make night shifts safer and more reliable,” Munn said in a news release. “This isn’t just automation; it’s a practical solution that’s fundamentally changing how we farm.”

Additional Details Come In On AutoTractor
Farm Journal talked with CEO Paul Mikesell to see what else we could learn about the system and what makes it different from other tractor autonomy kits on the market. Here’s a handful of bullet points breaking down what we uncovered:

Don’t Call It A Retrofit - Because the AutoTractor kit doesn’t effectively alter or change anything mechanically on the tractor itself, Mikesell says he prefers to refer to it as a “augmentation kit.”
Satellite Connectivity Changed The Game - When Mikesell and his team started this project back in 2023, connectivity was a limiting factor in enabling a tractor to safely operate with complete autonomy. That is no longer a limiting factor as developments in the stratosphere like SpaceX’s StarLink and Intellsat’s low earth orbit constellations have provided the necessary latency and bandwidth to make driver-less operation safe and viable.
Pricing Is Still TBD - Pressed on how much the system will cost from an up-front investment standpoint, Mikesell told us that “we’re still fine tuning that price.”
Expect An Hourly Fee - Mikesell did confirm that the technology will carry a per-hour fee. He says that fee will track closely with what the user would pay a local machine operator to run the tractor. That could mean a per-hour fee anywhere from $15 in the Midwest to upwards of $25 per hour in high-wage markets like California and Washington. “We’re trying to save you money by not having to worry about travel time out to the fields. There’s no lunch break. You don’t have to worry about paying overtime. This machine will do as many double shifts as you want, and we’re still employing people to do all the monitoring. So we have a very skilled and qualified group of people that are doing all the monitoring. So that’s kind of the model: we charge you per hour to run this machine for you and we’ll work with you on what jobs you want done and how you want it done and make sure that everything is handled appropriately.”
Remote Operators With Tractor Experience - Mikesell says his remote operators that task and oversee the driverless tractors for farmers get a crash course in how tractors are used on your typical farm. “Just being out there in the field long enough to understand the size of things that are around you and just kind of what a field looks like and how things are laid out, makes a huge difference when you’re trying to drive remotely,” says Mikesell. “Even though you have a better view driving remotely, because you have a nice 360 degree view off the roof, having some concept and understanding about the size of things and kind of what everything looks like helps quite a bit.”

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AI-powered FarmWise prepares for next chapter in ag robotics

Tue, 18 Mar 2025 13:08:24 GMT

FarmWise, an artificial intelligence and computer vision weeding technology company in the robotic precision weeding technology space is restructuring its business, CEO Tjarko Leifer told The Packer on March 14. The Salinas, Calif.-based company, which employs a staff of 50, is best known for its Vulcan next-generation, intra-row weeder and precision cultivator that launched in 2023.

“The need for solutions like Vulcan has grown as growers face mounting pressure from labor shortages, rising input costs and operational complexities, said Leifer. “The technology has proven its ability to deliver meaningful efficiency gains and cost savings in the field. But even with growing demand and a product that works, achieving sustainable, profitable growth remains a significant challenge in today’s market.”

Vulcan is really a three-in-one implement that does precision weeding, cultivation and thinning, says Leifer.

On the specialty crop side, the company’s Vulcan technology is employed primarily by growers of lettuce and brassicas in the coastal California and Arizona vegetable crop markets. More recently, FarmWise entered the processing tomato market in California’s Central Valley, a new segment that Leifer says is nearly as big as the leafy green and brassicas market on an acreage basis.

Leifer points to one customer — a 10,000-acre vegetable grower with farms in Yuma, Ariz. and Salinas — who saw significant savings and a reduction in labor costs.

“Implementing the FarmWise Vulcan has transformed how we approach weeding on our operation,” the vegetable grower said. “Over just one season, we reduced weeding costs by nearly $550,000 and eliminated the need for cultivator passes on 64% of the acres covered. The AI-powered technology has allowed us to scale operations more efficiently, reduce labor costs, and improve precision in ways that traditional methods couldn’t match. This technology has set the foundation for even greater growth and profitability in the future.”

The grower also reported its per-acre weeding costs dropped 38% in romaine and 15% in broccoli. Additionally, 64% of its acreage no longer needed cultivator passes, cutting fuel use and field wear. And machines achieved up to 100 acres weeded per week, with 1-3 acres per hour efficiency and no compromise on weed removal quality.
With such notable results, why was FarmWise unable to scale?

“The short version is that we haven’t — with the resources that we’ve been able to raise — been able to reach profitability,” said Leifer. “And that’s such a critical threshold to get to for any business.

FarmWise CEO Tjarko Leifer is hopeful about the next chapter for the agtech company.

(Photo courtesy of FarmWise)

“We’ve had some great milestones we’ve achieved in terms of a product that really works for farmers, that drives a return on investment, that has a payback period of less than two years, and that’s deployed commercially and reliable day-in and day-out,” he continued.

But the company has also faced challenges.

FarmWise says the time horizons have been challenging for the company, because while it sees demand for the technology, it needs a longer runway to prove itself and drive adoption.

Leifer says broader macroeconomic headwinds have also impacted ag equipment investment overall — from rising interest rates and policy uncertainty to challenges around labor and immigration.

“Agriculture is a business that rightfully values caution and real-world proof,” Leifer said. “Growers want to see new technology work on the ground before fully adopting it — and we respect that approach.” Next-gen tech isn’t alone in feeling these headwinds.

The CEO also said these headwinds aren’t unique to startups. Large equipment manufacturers have seen sales drop 30% to 50%, making it a particularly tough moment for capital-intensive innovations, he said.

“If you’re a 120-year-old company, it’s a cyclical downturn,” he said. “If you’re a startup, it’s a much steeper hill to climb with limited resources.”

Agtech is in need of fellow visionaries to succeed, and Leifer sees this as a moment for the industry to rally around innovation, while recognizing the path from early adoption to scale is never linear.

“Building a great product is only half the challenge,” he said. “The next chapter is building the distribution and support infrastructure to bring it to scale. That’s where partnerships become critical.”

FarmWise’s core product is the AI-powered Vulcan, which weeds, cultivates and thins vegetable crops like lettuces and brassicas.

(Photo courtesy of FarmWise)

Labor considerations

While agriculture, like many industries, is in a labor crisis, in some cases it’s been slow to adopt technology that would alleviate that challenge.

“Labor cost inflation, especially coming out of COVID, and also changes in laws around how ag overtime is treated in California, are pressing issues, but with the new administration’s approach to labor and immigration, people really don’t know if labor will become plentiful or if it’s going to be much harder to hire people,” said Leifer. “So, there’s a lot of things changing right now, and a bit of a wait-and-see attitude.

“It’s an existential question for many segments of farming, in particular vegetable farming segments where there’s a lot of labor costs per acre,” Leifer continued. “Those costs are going up. It’s getting harder to find people, and farmers are very interested in technology and solutions that help them address that.”

Leifer says even if growers aren’t looking to reduce labor, they’re still looking for solutions that allow them to farm on a larger scale with the skilled labor they already have.

“How can you upskill the needs you have so you can do more with the good people you have? It’s how do we keep agriculture profitable and healthy in the United States and competitive? We need to find ways to be more productive,” said Leifer.

With AI and computer vision robotics, there are efficiencies that can be delivered today that couldn’t before, he said.

Robotics addresses inputs

In addition to the labor side of the story, there’s also the chemical side.

“There’s a lot of talk about some of the herbicides that are used in broccoli being removed from the market,” said Leifer. “And as you broaden out to row crops, there’s the whole herbicide-resistance story in a lot of those cropping systems, which ultimately mean farmers are going to need new technologies. We’ve always thought that AI and robotics can play a really important role there.”

Robotic machinery allows growers to see and understand the crop in the field, differentiate between the crop and weeds, and then control in real time how the machine is behaving as it goes through the field. As such, robotics also offers the potential to reduce the use of chemistry, drive crop fertility and automate tasks that are still done manually, says Leifer.

“There’s natural herbicide resistance that’s gaining and farmers are going to need new solutions in a broad range of cropping systems,” he said. “The market is working on providing innovations for them and we believe one of those — a big one — has to do with robotics and agriculture.”

The road to adoption

FarmWise says its flagship three-bed, 80-inch unit had an MSRP of $645,000. The annual service and support package is an additional $45,000. Leifer says the savings driven by the unit pays for itself in under two years.

“It’s a very attractive proposition,” said Leifer. “If the machine works and it saves people money, people should be ripping this out of your hands and off the lot to put into their fields.”

But employing AI-driven tech is not as simple as flipping a switch or screwing in a light bulb.

“It takes someone who believes in it and sees their success in the organization tied to the success of making the program work,” he said. “It takes an ownership group that wants to empower somebody like that. So, there ends up being a lot of nuances to how an organization can successfully adopt technology.”

What’s next for FarmWise?

While the current FarmWise team is preparing to wind down operations by April 1, the company says it is actively pursuing strategic opportunities — including acquisition, partnership and technology transfer — to ensure the Vulcan platform continues to thrive.

“We’re proud to have proven that advanced robotics can deliver real value in one of the most complex environments — agriculture,” Leifer said. “This is just the start of what’s possible with this kind of technology.

“We’re in active discussions with potential partners and investors,” he added. “There’s a path forward here, and I’m hopeful the technology we’ve built will continue to scale and serve more growers in the future.”

FarmWise says it remains committed to supporting its current customers and ensuring continuity during the transition period — including access to service and spare parts.

“We know growers depend on this technology, and we’re doing everything we can to provide stability and a strong handoff,” Leifer said.