Deere vs. FMC: The Infrastructure Bet in the AI Agriculture S-Curve

The agricultural sector is on the cusp of a fundamental S-curve transition. For decades, the model was built on chemical inputs-fertilizers, pesticides, and herbicides-sold by companies like FMC. The new paradigm, however, is built on data and automation, where the infrastructure layer is being defined by AI. This isn't incremental improvement; it's a shift from selling products to selling intelligence and capability.

The numbers underscore the exponential growth of this new layer. The global market for AI in agriculture is projected to expand from $2.8 billion in 2025 to $8.5 billion by 2030, growing at a compound annual rate of 25.1%. This isn't just a niche trend. By 2025, over 60% of large farms worldwide are projected to adopt AI-powered precision agriculture technologies. The adoption is driven by clear, tangible benefits: boosting yields, cutting costs, and promoting sustainability through smarter resource use. The industry is moving from a model of chemical application to one of data-driven decision-making and autonomous execution.

This is where the investment thesis crystallizes. FMC represents the legacy chemical business, a model facing structural headwinds as the industry pivots. Its future is tied to the declining efficacy and rising regulatory pressure on traditional inputs. In contrast, Deere is building the fundamental rails for the next paradigm. The company is pioneering the convergence of AI, automation, and precision technology, moving beyond digitization to true autonomy. Its smart sprayers, designed to apply chemicals only where needed, are a direct application of this shift, already demonstrating declines in cost and pollution in testing. Its suite of digital tools and satellite imaging forms the data backbone, while its development of self-driving tractors and robotic harvesters points to the ultimate infrastructure layer.

The bottom line is a classic disruption story. The AI infrastructure layer is growing at an exponential rate, powered by massive global demand for food and efficiency. Companies that are building this layer-like Deere-are positioned to capture the value of the entire S-curve. Those that are merely selling the inputs for the old model are being left behind.

The Financial S-Curve: FMC's Decline vs. Deere's Potential Momentum

The financial trajectories of FMC and Deere tell a stark story of alignment and misalignment with the technological S-curve. FMC's stock has plunged 71.5% in 2025, a collapse that mirrors the erosion of its core business model. Management's own outlook is bleak, citing only limited growth potential over the next three years. This isn't just a cyclical downturn; it's the market pricing in a structural decline. The company is caught in a squeeze: higher-margin products are going off-patent, inviting generic competition that pressures prices, while high interest rates in key markets like South America are straining customer liquidity. The result is a clear path of declining revenue and profits, forcing aggressive cost cuts and a drastic 86% reduction to its dividend. For investors, this sets up a classic value trap scenario-cheap on paper, but with no visible inflection point on the horizon.

Deere, by contrast, is positioned at the leading edge of the adoption curve. Its recent quarter showed the potential for upward momentum, a sign that its investment in the new infrastructure layer is beginning to pay off. The company's smart sprayers, a direct application of AI and automation, are demonstrating the exponential efficiency gains promised by the paradigm shift. In testing, these systems have achieved a 50% reduction in chemical use and an 87% reduction in drift. This isn't incremental improvement; it's a fundamental redefinition of input application, cutting costs and pollution simultaneously. Viewed another way, Deere is building the rails while FMC is selling the last of the old track.

The bottom line is a divergence in momentum. FMC's financials are decelerating, reflecting a business that is being left behind on the S-curve. Deere's financials, while facing headwinds in the near term, are showing signs of accelerating as its AI-powered solutions gain traction. The company is not just selling machines; it is selling the intelligence and autonomy that will define the next generation of farming. For an investor, the choice is clear: bet on the declining slope or the rising inflection.

The Infrastructure Layer: Compute Power and Adoption Rate

The new agricultural paradigm is built on a foundation of real-time compute power and accelerating adoption. This isn't about selling more fertilizer; it's about embedding intelligence directly into the farm's operating system. The infrastructure layer relies on AI systems that process data from sensors, cameras, and satellites to make complex decisions on the fly. On a CNH Industrial combine, for instance, AI algorithms manage everything from steering to optimizing input application, all in real time to boost productivity from steering vehicles to optimizing inputs. This compute layer is what transforms a machine from a tool into a thinking partner.

The most tangible proof of this shift is in the field. Technologies like the SenseApply™ sprayer automation use machine vision to apply treatment only where needed, a direct application of this AI infrastructure. The results are exponential: these systems have demonstrated a 50% reduction in chemical use and an 87% reduction in drift in testing. This isn't just efficiency; it's a fundamental redefinition of resource management, cutting costs and pollution simultaneously. The adoption rate for such precision tools is now accelerating, with over 60% of large farms worldwide projected to adopt AI-powered precision agriculture technologies by 2025.

The next frontier is autonomy. Testing of self-driving tractors is advancing rapidly, representing the ultimate convergence of AI, robotics, and precision technology. This isn't science fiction; it's the next step in farm automation, designed to address labor shortages and optimize resource use across entire fields. The promise is clear: by 2025, AI-powered precision agriculture is expected to increase crop yields by up to 30% globally. This infrastructure layer directly tackles the twin global challenges of feeding a growing population and doing so sustainably.

For Deere, this is the core of its strategic bet. The company is not merely selling tractors; it is building the compute and automation rails for the entire industry. Its investment in AI, autonomy, and digital tools positions it at the center of this exponential adoption curve. The infrastructure is being laid, and the adoption rate is climbing. The question for investors is whether they are backing the company that owns the rails or one that is selling the last of the old freight.

Catalysts, Risks, and What to Watch

The investment thesis hinges on a clear divergence in momentum and strategic positioning. For Deere, the key catalyst is a visible acceleration in the adoption rate of its AI infrastructure. Watch for quarterly reports that show not just growth in digital services revenue, but also a significant uptick in the deployment of its smart sprayers and other autonomous systems. Any expansion of its AI-driven product suite-such as new software integrations or hardware add-ons for its existing machinery-would validate the company's bet on the infrastructure layer. The bottom line is that Deere needs to demonstrate that its technological S-curve is steepening, moving from early adoption to mainstream scaling.

The primary risk for FMC is financial strain locking it out of the new paradigm. The company is already retrenching, with a substantial 86% reduction to its dividend and a turnaround not expected until 2028. This severe cash constraint likely prevents the kind of aggressive investment or acquisition needed to build an AI platform. Without that, FMC is left selling legacy chemicals into a declining market, unable to participate in the exponential growth of the new infrastructure layer. The risk is not just slow growth, but becoming irrelevant.

The most significant catalyst for the thesis would be a major, unexpected acceleration in FMC's turnaround. However, the evidence suggests this is unlikely before 2028. The company is facing headwinds from off-patent products and high customer interest rates, and its own management has declared a "reset year" for 2025 and likely 2026. While the stock's plunge may make it appear cheap, the financials point to a prolonged period of decline and restructuring. For now, the setup favors Deere's infrastructure bet, with the next inflection point being the company's ability to scale its AI solutions across the global farm base.