AgTech: Are We Still Building for Reaction or Precision?

By: Mikayla Mooney

In life everything you build and every decision you make lives somewhere along a spectrum: proactive or reactive. The same is true for founders.

This isn’t just a technical distinction. It’s a mindset. One that shapes what gets adopted, when it gains traction, and who ultimately wins.

It’s tempting to argue that being proactive is always better. But the truth is more nuanced. Some of the most widely adopted tools in agriculture are reactive and for good reason.

Let’s break this down.

The Proactive vs. Reactive Framework

Proactive solutions aim to prevent a problem before it arises.
They require foresight, education, behavior change, or infrastructure. Often before there’s a crisis.

They're harder to sell, harder to adopt, but often more sustainable in the long run.

Reactive solutions address the symptoms after they appear.
They're easier to grasp, often have a more immediate ROI, and meet people where they already are: in a state of need.

This isn't just theory. It's deeply human. We’re wired to solve the fire that's burning, not the fire that might spark three harvests from now. Most people, and most businesses, default to reactive.

GLP-1 and the Obesity Economy

I’m pretty sure I live in the top 10% of households in the U.S. when it comes to healthy lifestyle. My husband and I train for ultramarathons and half-ironmans. Most of our meals are home-cooked, with zero processed sugar, and locally sourced ingredients. It helps that he owns a salad drive-thru where the greens are grown on site!

That’s why it’s been fascinating to watch the rise of GLP-1 receptor agonists (Ozempic, Wegovy, Zepbound, etc) as miracle drugs for obesity.

Rather than overhauling food choices and reducing ultra-processed food consumption, or building active lifestyles, millions are choosing a drug that suppresses appetite and modulates insulin response.

It works. It’s effective. But it’s reactive.

People rarely invest in prevention because it feels abstract, and let’s be honest, it’s harder. We all have the best intentions at the start of the year with that newly minted gym membership and workout routines, but sticking to it requires dedication and discipline.

Obesity isn’t a meal, it’s a decade. And by the time it demands attention, it’s often too late for light-touch fixes.

Many solutions are designed to act after a problem is visible, because that’s when we as decision-makers feel the urgency.

The same reactive behavior plays out across all sectors of agriculture. Many tools are adopted not when they make sense, but when the pain finally sets in.

In-Field AgTech: Farming the Map, Not Just the Field

Picture a grower preparing to fertilize a thousand-acre field. The quick option? Apply a uniform rate across everything. No testing. No prescription map. Just a flat spread based on last season’s yield.

It feels efficient, but it ignores how wildly variable soil nutrient levels can be. Some areas are nutrient-rich and overloaded, others are deficient. The result? Wasted inputs in one zone, underperformance in another, and potential nutrient runoff downstream.

Now contrast that with a grower who starts with grid soil sampling, builds a variable rate application (VRA) map, and applies precisely what each zone needs. There’s upfront costs like sampling, mapping, and software, but over time, it pays back in lower inputs, better yields, and cleaner environmental outcomes.

Reactive is fast but blunt. Proactive is slower but smart.

The first approach solves today’s task. The second builds next year’s advantage.

Animal Health: What H5N1 is Teaching Us About Reactive Risk

Animal health, at times, works on a reactive model: wait for clinical signs, then intervene. There is seasonality, and there are standard health protocols and standards to improve performance. But the spread of avian influenza has exposed just how fragile that system is.

When High Pathogenic Avian Influenza jumped from birds to cattle, many dairy operations (and veterinarians) were caught off guard. Not just by the biology of the virus, but by the absence of foundational infrastructure to monitor, trace, and respond within dairy systems.

Unlike swine and poultry production, where vertically integrated systems have long required strict biosecurity protocols, such as entry logs, controlled movement, dedicated equipment, and diagnostic surveillance testing, most dairy operations lacked those layers of defense.

By the time anyone noticed cows were off feed, or milk production had dipped, it was already too late. The virus had spread between states, between herds, and even into workers.

In dairy, that muscle wasn’t built. The assumption was that large animals in open barns were lower risk. Until they weren’t.

It wasn’t a failure of knowledge. It was a failure of readiness.

The irony is, proactive animal health works best when it looks unnecessary. Joel Harris perfectly captures this:

“A man in Kansas is sitting, rubbing his hands together, in the middle of a field. The farmer walks up to the sitting man and asks, ‘What are you doing?’ The man replies that he is keeping the elephants away. Puzzled, the farmer says, ‘What are you talking about? There are no elephants in Kansas!’ The sitting man smiles and looks over his rubbing hands into the distance and replies, ‘Must be working!’”

That’s the veterinarian’s paradox. When vaccines and protocols work, no one sees the crisis that didn’t happen. But that’s the point.

The dairy sector suddenly had to reckon with:

• Delayed detection and slow diagnostics

• Lack of traceability across infected herds

• Uncoordinated responses that stoked public confusion

• Mounting concern over food safety and human transmission

If dairy had adopted the same biosecurity standards already common in swine and poultry, would outbreaks have been contained sooner? Would fewer cows be infected? Would consumer trust have held?

Maybe eggs wouldn’t have reached $12 a dozen.

Instead, the response became reactive, media-driven, and politically tense—because the infrastructure to respond with science simply wasn’t in place.

Now, dairy sectors are racing to catch up:

• Controlled facility access

• Daily logs of people and vehicle movement

• Routine diagnostic sampling and surveillance

• Farm-to-farm movement tracking

• Risk modeling to inform preemptive containment

These are foundational systems, not crisis add-ons.

H5N1 is showing us the true cost of reactive infrastructure. It exposed the cost of assuming “that won’t happen here.” The cost isn’t just financial, it’s public trust, food system stability, and human health.

Revenue Models, Adoption Curves, and the Farm of the Future

Here’s the hard truth for startups: proactive solutions are harder to sell.

Reactive tools fit the moment. A problem is visible. The value is urgent. The check gets written.

The business model is straightforward:

• One-time treatments

• Per-acre pricing

• Simple transactional revenue

Proactive solutions? They live upstream. They ask a producer to spend money to avoid a problem they can’t yet see.

That’s a harder pitch - especially in an industry with tight margins and seasonal cycles.

These solutions often rely on:

• Subscription models

• Monitoring and analytics fees

• Long sales cycles

• A leap of faith that optimization beats reaction

In many cases, the economics don’t quite pencil out. At least not yet. Not because the ROI isn’t there, but because the mental model hasn’t caught up.

But that’s changing.

As farms scale, input prices swing, and regulatory and labor pressure rises, the cost of waiting is climbing, too. Farmers are beginning to realize: the only way to protect performance is to prevent the problem altogether.

Reactive tools might win the first sale. But proactive platforms will own the long game.

They aren’t just solving pain. They’re redefining how agriculture thinks.

What Needs to Change for Proactive AgTech to Win?

If proactive solutions are more efficient, scalable, and sustainable, why don’t they dominate the market already?

Because adoption isn’t just about ROI on paper. It’s about behavior, infrastructure, and incentives.

• Short-term pressure: Input financing and crop insurance often reward survival, not optimization.

• Gatekeepers matter: Farmers trust agronomists, nutritionists, and veterinarians more than dashboards or AI models.

• Infrastructure gaps: Proactive tools depend on connectivity, sensors, and data standards that are not yet universally in place.

• Mindset shift: Preventative investment requires trust, proof, and longer-term thinking.

And while progress is being made across all of these dimensions, broad scale adoption is still lagging.

What’s at Stake for Incumbents?

The traditional ag value chain is built on volume, uniformity, and scale: sell more seed, more fertilizer, more feed, more treatments. Reactive solutions fuel that model.

Proactive solutions challenge it.

• They optimize instead of maximize

• Reduce treatment frequency

• Shrink product volumes

• Shift value from chemical to information

For incumbents, this is existential. Business models built on over-application now face structural headwinds in a world that rewards efficiency.

Their choice?

1. Defend the status quo—and risk irrelevance

2. Invest early in digital, data, and outcomes—and become strategic partners, not just product pushers

Some are pivoting. Others are standing still. But in a world where proactive wins, those who don’t evolve will find themselves competing not on brand loyalty, but on survival.

Final Thought for Founders

If you’re building in AgTech, don’t just ask: Does my solution work?

Ask:

• Am I solving today’s fire or tomorrow’s system?

• Does my revenue model match the moment or the future?

• What needs to be true for this to scale five years from now, not just five months?

• And who will lose power if I win?

You don’t have to pick sides entirely. Some of the best companies start reactive, earn trust, and evolve into proactive platforms over time.

But clarity matters.

Because when you know where your product lives on the proactive–reactive spectrum, you’ll understand the behavior you’re asking customers to change and how far ahead of the curve you really are.

That’s the difference between a clever solution and a company that lasts.