Artificial Intelligence

The Digital Farmhand: How AI is Solving the Agricultural Labor Crisis

Tue, 12 May 2026 20:01:45 GMT

Agriculture is facing a historic labor shortage at the same time artificial intelligence (AI) is reshaping how the world operates. Some fear AI adoption will result in job loss and businesses being left behind due to rapidly evolving technology. Others say AI is the digital farmhand agriculture needs right now to handle repetitive data tasks while humans focus on high-value animal husbandry or field work.

Either way, one thing is true – AI is not going anywhere.

“Whether AI replaces jobs or not depends on how the industry chooses to use it,” says Angel Andaya, manager of digital solutions for Silver Support, a managed development center supporting operations, finance, digital solutions, information technology and automation services.

If AI is seen purely as a replacement, she says that is likely the direction it will take. But it could also become a powerful tool to help farm operations thrive despite labor challenges.

The “Why Now” of AI: Accessibility and Adoption

While AI has existed for years (think Netflix recommendations and GPS), the launch of ChatGPT marked a paradigm shift that made the technology conversational and accessible to everyone, says Tracy Soper, senior director of data excellence at Keystone Cooperative.

“At 100 million [users] in two months, ChatGPT’s growth is unheard of – nothing has grown that fast,” Soper said at the National Pedigreed Livestock Council’s annual meeting. “Why? Because it was conversational and easy to access. It was something all of us could touch and could relate to, like, ‘Oh, this is a thing. It makes my life easier.’”

In the past, technology adoption took years. Now, it happens in months, creating a sense of “AI hysteria” and a need for clear strategy, he adds.

Problem First, People Always

Rather than viewing AI as a replacement for human expertise, it should be viewed as an amplification tool, he says. The strategy is to avoid expensive shelfware by starting with specific business problems.

“It can do a lot of things, but how are we going to use it?” Soper asks. “For us at Keystone, AI is not about replacing people; it’s making people better.”

Years ago, Soper says his job was to look over all things related to information technology (IT). Today that looks like AI and automation solutions as the cooperative’s scale has grown.

“For us, it’s starting very specifically with what problem we’re trying to solve today and then asking, ‘Why can’t we solve it with what we’ve got?’” he says.

Keystone takes a four-step approach:

1. Start with the problem, not the technology.

“AI only creates value when it’s solving a real business challenge. Companies that buy a tool, hand it to IT and expect magic end up with expensive shelfware,” Soper says.

2. Data readiness before algorithms.

“Any insight is only as good as the data feeding it,” he says. “We invested significant time building a modern data foundation before ever pursuing AI.”

3. Amplify expertise – don’t replace it.

“AI is not replacing agronomists, breed managers or the people closest to the animals. It’s amplifying their experience and sharpening their decision timing,” Soper explains.

4. Your data is the competitive edge.

“The competitive gap will be built on data readiness as much as algorithms,” he says.

In the future, Keystone is working actively in predictive machine learning and generative AI, using them to improve decision timing, streamline operations and better serve the producers who depend on the cooperative.

Shorten Time-Consuming Tasks

AI helps experts ask better questions sooner, Soper says. With data flowing more freely across the value chain, he believes there is great opportunity where AI and animal data converge.

For example, computer vision for body condition scoring, lameness detection and welfare monitoring is moving from research into practice in many barns. He’s also excited about how AI-assisted genomic prediction and health monitoring are advancing across species and can help make progress more quickly.

Andaya encourages farmers to think about the daily realities on the farm. What tasks are essential, but time consuming and repetitive?

“Even small improvements in how they are managed can free up valuable time and improve decision-making on the ground,” Andaya says.

If these processes are supported through AI, she believes it will enable farmers and their employees to focus more on animal welfare, planning and improving overall farm productivity.

“In this sense, AI is less about replacement and more about giving farmers and livestock teams the space to focus on what truly matters,” she says.

4 Tips for Successful AI Implementation

Agriculture and livestock operations are full of valuable data from daily logs to finances, Andaya explains.

“What’s changing is how effectively this information can be used,” she says.

Soper says Keystone has learned four important lessons in their journey to use AI more efficiently.

1. Data quality is everything.

Start with the data you own. Then budget time for discovery and cleanup.

2. Build for the people doing the work.

The tool needs to make someone’s job easier or it won’t get used. AI should amplify good discipline.

3. Scope tight, prove value first.

Prove it works before you scale. The business has to own the problem – IT enables, but stakeholders drive adoption and define success.

4. Governance can’t wait.

Policies around approved tools, data and data protection need to exist before people experiment. Once people start using AI on their own, it’s harder to rein in.

Farm Business In 2026: Relationship First, Digital Convenience Second

Tue, 28 Apr 2026 17:48:24 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.

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

Fri, 17 Apr 2026 15:10:25 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)

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

Mon, 13 Apr 2026 21:22:17 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 .

Inside The Tax Return of Your Farm's Future

Thu, 09 Apr 2026 14:31:53 GMT

The traditional process of preparing agricultural tax returns has long been defined by manual data entry and the complex reconciliation of income. However, the integration of artificial intelligence into financial systems is ushering in a more sophisticated era of tax management. For the modern farm, the future of filing lies in a seamless pipeline where software handles the heavy lifting of data organization, leaving the high-level strategy to human experts.

Comprehensive Data Integration

The foundation of a modern tax return is the accounting system. Platforms like QuickBooks, Xero or specialized farm management software are becoming increasingly autonomous. In the near future, these AI agents will do more than simply record expenses; they will analyze them in real-time.

With direct links to bank feeds and digital invoices, AI can categorize expenditures with precision. It can distinguish between capital investments, such as machinery or land improvements, and standard operating costs like seed and fuel. This continuous synchronization means by the end of the fiscal year, the financial records are already in a format that mirrors the requirements of a tax return.

Automated Document Reconciliation

A significant portion of tax preparation involves matching — ensuring the farm’s internal records align with the documents issued by third parties. A preparer of a farm tax return may spend more time making sure all of the income is in the right box then planning to optimize the income tax level.

AI is uniquely suited to handle this high-volume verification. The system can automatically ingest Form 1099-PATR (cooperative distributions), 1099-G (government subsidies) and other Form 1099s and W-2s and verify them against recorded deposits.

If a document is missing or a figure does not match the ledger, AI identifies the specific discrepancy immediately, allowing for a targeted correction rather than a manual search through months of records.

The Role of Human Oversight

While AI provides the technical framework for the return, the final stage remains firmly in human hands. Once the software has mapped the data to the appropriate tax schedules, it produces a comprehensive draft for professional review.

This allows the farmer or a tax consultant to transition from a data entry role to a strategic advisory role. Instead of spending hours verifying line items, the human reviewer can focus on critical tax planning decisions including accelerated depreciation choices or income averaging that require professional judgment and an understanding of the farm’s long-term goals.

The result is a more accurate, defensible and efficient tax filing process. By automating the clerical aspects of the return, AI allows agricultural producers to maintain focus on their operations while ensuring full compliance with the evolving tax laws.

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

Wed, 08 Apr 2026 15:15:55 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 .

Smarter Pigs, Smarter Farms: How AI and ChatGPT are Re-Wiring Swine Production

Tue, 02 Dec 2025 18:46:20 GMT

Artificial intelligence is no longer a distant idea reserved for Silicon Valley—it’s a new nervous system for agriculture. For U.S. hog producers, it represents something bigger than technology; it’s a way to manage your pigs, feed and people with new precision. The future of pork is not about who has the most sows or barns. It’s about who learns and adapts the fastest.

From Gut Instinct to Prediction

For generations, the best farmers were those with a feel for their pigs, the ones who could walk through a barn and see which sow was off her feed or ready to farrow or pig behavior. Today, AI can help make those instincts measurable and remove the risks of human errors.

Every feeder sensor, camera or ventilation fan can feed data into models that “learn” from each litter and each season. Tools like ChatGPT make that data useful, turning barn notes, vet reports and spreadsheets into quick-answer insights.

Want to know which group of gilts gained fastest under a new ration? Or whether feed conversion is improving after a ventilation tweak? Ask ChatGPT, connect it to your farm data, and get a summary in seconds.

Pork weighing scales, microphones and cameras can turn weight, sounds and behavior into early warnings. AI models can now detect coughing patterns before clinical signs appear, or spot sows in heat based on posture and motion. For the producer, that means fewer missed breedings, earlier interventions and better pig comfort.

What AI Can Do on the Pig Farm—Right Now

AI is not science fiction; it’s already working in barns, feed mills and logistics. The most practical use cases today include:
• Feed optimization: Machine-learning programs analyze growth, weather, and ingredient prices to recommend the least-cost ration that still meets performance goals. Instead of fixed formulas, AI continually adjusts, saving dollars per ton.
• Health monitoring: Vision systems detect lameness, coughing, and even tail biting. One U.S. integrator has reported that an early-warning algorithm reduced mortality by 9 %. Another is using an ear sensor with a warning light to allow producers to identify problem pigs, immediately.
• Breeding management: Predictive tools combine parity, backfat, and temperature data to forecast farrowing success and optimize breeding windows.
• Barn automation: AI-enabled controllers adjust temperature, humidity, and ventilation in real time, responding to pig behavior rather than fixed setpoints.
• Business insights: ChatGPT-style assistants can summarize market reports, predict feed cost trends, and even draft Standard Operating Procedures or employee checklists—freeing managers from paperwork to focus on people and pigs.

Each of these tools starts small — one barn, one dataset — but they build fast. As my AI-in-agriculture survey of 40 experts demonstrated, “AI doesn’t substitute, it amplifies.” It scales farmer judgment across millions of data points.

People Plus Machines: A New Kind of Teamwork

Many farmers worry that AI means fewer jobs. The truth is subtler. Routine data entry and paperwork will shrink, but new roles are emerging, digital barn managers, AI-savvy nutritionists and veterinarians, and on-farm data stewards.

The best advisors, nutritionists, veterinarians, production supervisors, won’t be replaced; they’ll be augmented. Imagine your vet arriving on-farm already briefed by an AI which has summarized every case history of pigs on the farm and flagged unusual patterns in the last 30 days.

As one expert noted in our survey, “The best people will become better, but teams must upskill now to stay relevant.” The future belongs to “farmers who can code”—or at least, who can ask good questions of their digital co-pilot.

ChatGPT makes that accessible. You don’t need programing skills; you just need curiosity. The hog producer who experiments, asking ChatGPT to draft a pig-flow plan, prepare a proposal to file an environmental plan, or explain a spreadsheet formula, is already ahead of the game.

Five Steps to Get Started with AI on Your Farm

When I conducted a survey of 40 experts in AI and Food resulted in the ‘DRIVE’ acronym for what you need to do to move from theory to action:

Data: Clean up your data. AI runs on clean, structured information. Start digitizing feed deliveries, weights, and mortality logs. Even a basic spreadsheet is a start.

Run Pilots: Pick one problem. Choose a specific, high-value use case—detecting sick pigs sooner, forecasting feed needs, or improving gilt selection. Measure results.

Insiders: Or Insider experts, not just outsider consultants. Those surveyed didn’t say not to use consultants in the initial stages but suggested that building internal competency and experts in your pork production team is essential

VIPs: must participate. There is a tendency for the CEO, Boss or even senior management team to delegate responsibility for tech projects. AI is so essential everyone must understand what is happening and help implementation. As one person in my survey said “Don’t treat AI as an IT project. It’s a strategy shift.”

Execute Now. As Nike said in their adverts, “Just do it.” Don’t wait.

Will AI Change the Job of the Pig Producer?

Absolutely—for the better. Automation may take over repetitive chores, but judgment, empathy and local knowledge remain irreplaceable. AI can count pigs; it can’t feel if a pen “just doesn’t look right.”

A Leadership Moment

AI adoption isn’t a technician’s job, it’s a leadership responsibility. Whether you’re running 200 sows or 20,000, the question is no longer if AI will affect you, but how fast you’ll adapt.

Start small. Learn daily. Share results with your neighbors. Pig farmers are practical people; they won’t believe the hype until they see it work. But once they do, adoption will spread quickly—because efficiency, health and welfare all improve together.

One participant in our AI-in-Agrifood study said, “AI will not replace humans. But humans using AI will replace those who don’t.”

Bottom Line: It’s like Electricity
Treat AI like electricity—foundational, ubiquitous and non-optional. ChatGPT and similar tools are already becoming digital assistants for feed, health and finance decisions.

The next revolution in pork production won’t come from a new antibiotic or crate design—it will come from information. Every squeal, step and sip of water is data. When analyzed well, that data can tell you what your pigs need before they do.

The race is on. Don’t over-plan. Start acting and learning. Your pigs, your people and your profits will thank you.

A Farmer Can Dream, Right? Tesla Robots As the Farm Labor Force of the Future?

Thu, 24 Oct 2024 18:24:44 GMT

With a visual form ripped straight from a skin-crawl inducing robot thriller, Tesla’s new AI-bot, Optimus, is eliciting strong reactions from tech advocates and flip-phone touting technophobes.

Let’s indulge our imaginations for just a second and imagine how a farmer could put one of Musk’s $20,000 helper robots to work around the family farm in, say, the year 2040. I use 2040 because, even though the prototypes in the video below look awesome, it turns out the AI behind it needs more work before any farmer would feel safe setting a squad of them loose on the farm.

Our own Clinton Griffiths was also inspired by Optimus’ unveiling. In his upcoming column in the November issue of Farm Journal, Clinton gets right to the heart of the issue, and that’s whether the bots will pan out on the farm?

The real test, he writes, “will be whether it can keep its glossy finish motoring along regardless of whether or not the field is mud-free.”

I couldn’t agree more, Clinton. Serving up fancy drinks during an unveiling party on a glitzy Hollywood film studio lot is one thing. Standing up to all the dust and heat and tough conditions of your average farm or ranch is a different beast altogether.

In that vein, we offer up the following farm chore list Optimus can take over from here on out.

No, seriously Opti, you don’t need our permission. Just go ahead and take care of these few little things every single day for the rest of time, and we’ll be off, I don’t know, fishing at the lake with the kids, rocking on the front porch, or something.

Farm equipment maintenance tech
Director of crop protection jug disposal
Backpack spraying around-the-clock weed warrior
Chief grain bin inspector
Head ladder climber
Irrigation pivot inspector general
Head high in July crop scout
Pig loader and unloader extraordinaire
Master bottle mixer and calf feeder

Now that you’ve read my list, I’m curious how you would use a robot that walks, talks and moves like a real human (and never gets tired, bored or spends 20 minutes staring at its phone) on your farm? or click

Share your robot wish list by clicking the green “Respond Here” button or click here .

Your Next Read: As the Wizard of Yield, Ken Ferrie Reveals His Secrets on Unscripted

“Technical Debt” Continues To Grow Rapidly In The Agriculture Industry

Fri, 27 Sep 2024 02:17:54 GMT

Last December Southwest Airlines was forced to cancel more than 15,000 flights during the peak holiday season. It wasn’t weather, mechanical issues, or even striking airline workers that caused the chaos. Instead, the real reason for the grounding was the weight of the company’s overall “technical debt” had become too much too bear. In short, the company’s antiquated systems and technology broke down at the worst possible time.

Could the same thing happen in agriculture? Absolutely. In fact, the agricultural industry as a whole, at both the macro and micro levels are ripe for such technical tsunamis. That’s not just Chicken Little talking, such warnings are echoed by a recent McKinsey Global Institute study that placed agriculture dead last in terms of the industry’s state of digitization.

Is too much “technical debt” putting your farm’s future at risk? To answer that question you must first understand what technical debt means and how it affects your overall business.

Technical debt — or tech debt — is the implied cost incurred when businesses do not fix problems that will affect them in the future. Accruing technical debt causes existing problems to get worse over time. The longer the debt builds up, the more costly it becomes to rectify.

Learn more about the risk of technical debt at the 2024 Top Producer Summit. Register online today!

Farmers have been on the agricultural treadmill for the better part of two centuries now. It was JFK’s Chief Agricultural Economist Willard Cochrane that coined the phrase “technology tread-mill” to describe the race to adopt new technologies in order to remain cost competitive. From the Industrial Revolution to the Green Revolution, to the Biotech Revolution, to now the Information Age, it feels like Cochrane’s treadmill has accelerated to warp speed.

Assessing your farm’s technical debt is not as simple as evaluating risks from financial debt. There is not a clear formula, like a debt ratio, that measures total debt to total assets. Addressing technical debt involves taking inventory of the technology on the farm today and evaluating the short-term and long-term risks to your overall operation if one or more of those technologies fail.

That’s just the first layer of the onion when it comes to knowing your true technical debt. The exercise should also involve answering various questions about your farm’s overall technical health. Questions like — What technology is missing that I need today, or even tomorrow? What equip-ment should immediately be put out to pasture or parked in the digital fencerow? Are my technology pieces compatible? In other other words, do they play nice together and talk to each other? And finally — are you really using the technology you already have and the data that comes with it?

In the real world those questions might sound something like this — Do I need to digitize and record more of my field activities, like anhydrous or crop protection product application, in order to increase my farm’s future carbon market value? Is my yield monitor so old that they don’t even make memory card readers to download the data? Will my John Deere tractor display talk to my new Kinze planter? Do I religiously use technology to implement actionable agronomy practices like variable-rate seeding and crop removal recommendations?

Just like financial debt, not all technical debt is bad. Just like regular debt, it must be managed and serviced on a regular basis. The most important way to turn technical debt into a positive is to simply have a technology plan. What do you want your technology to do for you and does it align with the other overall future goals for your farming operation?

Tech debt cannot be eliminated by geeking out and going on a technology buying spree. Investment in tech should not be considered just a fair weather proposition, nor should it be considered when you’re behind the eight-ball like in the case of Southwest. Since the dawn of precision farm-ing, the industry’s pervasive mentality has been that technology falls into more of a luxury category than treating it as the capital expense it should be.

The agricultural treadmill has always been unforgiving. The recent rise of technical debt has only ratcheted up the intensity. If you are not proactive, you will likely spend all your time putting out fires. That leaves little time or energy left for planning. And as Winston Churchill once said: “He who fails to plan is planning to fail.”