As AI lowers the cost of starting a business, experienced professionals with industry knowledge and the right technical skills could become the next big competitors to agriculture’s established giants.
We’ve seen it happen in other industries. Social media and YouTube allowed independent creators to challenge traditional media companies. Uber gave drivers a new way to compete in the transport industry, while Airbnb enabled homeowners to enter the hospitality business without owning or operating a hotel.
Agriculture, however, has proved much harder to disrupt. Its physical complexity, high capital requirements and dependence on established relationships have helped protect traditional business models. But with the emergence of artificial intelligence, this could be about to change.
Agriculture’s biggest potential disruptor might already be working from within. An executive at a bank, grain trader or agricultural input company who knows the market inside out may have already tried to fix some of its inefficiencies, only to run into bureaucracy, competing priorities or a lack of resources. Now, with AI, they have the tools to develop and validate their own solutions, and potentially start their own businesses.
But we’ve also seen what happens when technology makes something too easy. AI has flooded the internet with cheaply produced articles, images and videos, much of it dismissed as AI slop. But that flood of content has also made original thinking, personal experience and authentic voices more valuable. Anyone can generate an article. Building an audience that trusts what you have to say is another matter.
The same could be true in agriculture. AI makes technology more accessible, but knowing which problems are worth solving and who will pay for a solution still requires industry experience, good judgment and the right relationships.
For established agribusiness companies, the implications go well beyond adopting another technology. Some of their most valuable employees may also be their most promising future competitors.
The Human Edge
The competitive advantage in AgTech is shifting from knowing how to build technology to knowing where and why to apply it.
Until recently, it was often easier for a talented software developer to learn about an industry than for an industry expert to acquire the technical skills needed to build a technology company. AI is changing that equation. Developing software is becoming easier and cheaper, while understanding agricultural markets, building customer relationships and knowing which problems are worth solving still takes years.
I believe the first major opportunities will emerge where inefficiencies are greatest, particularly in agricultural finance, inputs and logistics. Brazil’s high interest rates, complicated processes and fragmented markets make these sectors especially attractive.
AgroForte is a good example of the value of industry experience. Its founders came from the banking and animal protein sectors, bringing an understanding of the financing challenges facing livestock and dairy producers. They built a fintech that works with agroindustries and cooperatives to provide credit to farmers who are often poorly served by traditional banks.
In logistics, goFlux followed a similar path. Its founders came from the transportation sector and understood the inefficiencies of Brazil’s fragmented trucking market. They built a digital platform that connects shippers and transport companies, improving freight contracting without owning a fleet of trucks.
Both companies were founded before the current AI boom. They had to develop their technology, establish commercial relationships and prove their business models using traditional software tools. It was a longer and more expensive road than the one available to entrepreneurs today.
Now imagine an experienced credit, logistics or input executive starting a similar business with an AI-native technical co-founder. They already know the customers, understand the inefficiencies and have the contacts to test their ideas. With today’s tools, they can develop and validate a product much faster and with less capital.
For investors, I believe this combination offers one of the most attractive risk profiles in AgTech. An experienced industry professional working alongside a technically skilled founder brings commercial knowledge and customer access that a team of talented developers straight out of university would take years to acquire.
They also don’t need to recreate an entire bank, trading company or input distributor. Solving one expensive problem well can be enough to build a valuable business. And the companies employing these professionals may soon find themselves competing with them.
The Giants’ Dilemma
In 1997, Harvard Business School professor Clayton Christensen published The Innovator’s Dilemma, explaining why successful companies often struggle to respond to disruptive technologies.
His central observation was that the practices that make a business successful can also make it difficult to adapt. Companies protect existing margins, serve profitable customers and invest in improving products that already generate revenue.
Imagine a major agricultural input distributor that has spent decades building a network of sales representatives and agronomists. That commercial presence is one of its greatest assets, but also represents a substantial cost.
AI-powered agronomic recommendations could help the distributor serve more farmers with the same team. Yet the same technology might allow a much smaller competitor to offer similar services without building an extensive commercial network.
Should the distributor embrace a technology that could improve productivity while undermining an advantage built over decades?
Similar dilemmas exist across agriculture. Banks can improve credit analysis with AI, while startups may change how farmers access financing. Grain traders can automate commercial operations, while digital platforms make market intelligence more accessible and challenge traditional intermediation margins.
But the bigger threat may come from how these technologies change the relationship with the customer. A distributor might use AI to make its salesforce more productive, while an independent AI advisor begins influencing which products farmers buy. The distributor becomes more efficient but risks losing control over the purchasing decision.
This raises a question for established companies: are they using AI simply to improve their existing operations, or are they also preparing for competitors with entirely different business models?
Large organizations face additional obstacles. Legacy systems, internal approval procedures and conflicting incentives can slow experimentation. An executive responsible for a profitable division may have little reason to prioritize a project that could reduce its own revenue.
Many corporations already invest heavily in innovation. The harder question is whether they are willing to support ideas that might compete with their existing businesses.
The risk is that companies become more efficient at doing what they have always done, while new entrants capture the customers, decisions and margins that made those businesses attractive in the first place.
The First Move
The companies that understand how AI could disrupt their businesses will also be the ones best positioned to take advantage of it. For established agribusiness companies, the opportunity is to get involved early, before new competitors establish themselves.
That starts with understanding where their existing business models are most vulnerable. Which activities could a small company perform at a fraction of the cost? Where might AI change how customers choose suppliers, access financing or make commercial decisions? And which parts of the business could benefit from entirely new approaches?
The answers could reveal opportunities as well as threats. Established companies have customer relationships, valuable data, technical knowledge and distribution networks that startups would take years to build. Combining those strengths with entrepreneurial talent could help them develop new services, reach underserved customers and create additional sources of revenue.
They don’t have to develop everything internally. Working with startups provides a way to test new ideas, understand emerging technologies and learn from entrepreneurs who approach familiar problems differently. Commercial partnerships can lead to minority investments and, in some cases, acquisitions.
There is also an opportunity within their own organizations. Supporting experienced employees who want to start independent ventures could allow companies to participate in new businesses that might struggle to emerge through traditional corporate structures.
The objective isn’t to identify every future winner. It’s to understand what’s changing, build relationships with promising entrepreneurs and be ready to invest when opportunities emerge. Companies that begin this process early will have more options than those that wait until disruption starts affecting their margins.
The next agricultural giant might be starting today with a small team and an idea that established companies have overlooked. Its founder might even be sitting in one of their offices.
The question for industry leaders is whether they will recognize the opportunity early enough to help shape it, or wait until someone else does.
Thanks for reading.
KFG
Kieran Finbar Gartlan is an Irish native with more than 30 years’ experience living and working in Brazil. He is Managing Partner at The Yield Lab Latam, a leading venture capital firm investing in AgriFood and Climate Tech startups in Latin America.