Why does AgTech Matter?
My work in AgTech investing started with a broader climate-tech lens, but agriculture kept showing up as the sector where small changes could create very large climate wins. One of the crops causing the largest amount of greenhouse gas emissions is corn – a lot of these emissions are due to inefficiencies in the production chain. Innovating at the friction points in this chain is key to reducing emissions and delivering more value for producers and consumers.
For me, soil and water are the keystones in the maize emissions puzzle. In my early childhood living in India, I saw firsthand how a dry season or a bad harvest could ripple through entire communities. Healthy soils and water security are not abstract. Practically, these issues are measurable. We can now track soil carbon and water use with precision, which means we can prove impact, unlock carbon credits, and finance change at scale.
If we can master soil regeneration and water optimization with AI, everything else in the value chain, from reducing fertilizer waste to cutting post-harvest losses, becomes easier, cheaper, and more sustainable
Why focus on maize crops for this case study?
Maize is more than a staple crop. It is the backbone of food, feed, and biofuel systems worldwide. But maize production also accounts for significant greenhouse gas emissions, largely driven by how we treat our soil and water.
Globally, agriculture uses 70% of freshwater withdrawals and is responsible for a quarter of greenhouse gas emissions. In maize specifically, degraded soils require more fertilizers which emit nitrous oxide, a potent greenhouse gas, and inefficient irrigation strains already scarce water resources. This is not just an environmental issue. It is an economic and food security crisis in the making.
If we can solve the twin problems of soil degradation and water usage inefficiency, we do more than decarbonize maize production. We create ripple effects that improve yields, reduce input costs, and protect the livelihoods of farmers.
What makes the maize value chain inefficient?
Looking across the maize value chain from baseline measurement to deployment of solutions, two bottlenecks stand out. First, soil degradation caused by monocropping, over-tillage, and chemical dependency has eroded soil organic matter. Poor soil health reduces productivity, forcing farmers to increase fertilizer use, which raises both costs and emissions. Without accurate, scalable monitoring, it is nearly impossible to track soil recovery or carbon sequestration progress. Additionally, outdated irrigation systems waste water and energy, often delivering more water than plants can use. Climate volatility means farmers face both drought and flooding in the same season, which disrupts production. A lack of real-time monitoring and predictive tools makes it hard to match irrigation with actual crop needs.
These are not isolated issues. Degraded soils hold less water, and poor irrigation accelerates erosion. Left unaddressed, they cascade into secondary problems such as fertilizer inefficiency, harvesting losses, pesticide overuse, waste mismanagement, and emissions-intensive processing.
How can AI solve the three most critical issues?
One of the biggest issues we face starts with the soil – more specifically, preserving its health. Healthy soils store carbon, retain water, and reduce the need for synthetic fertilizers. AI-driven platforms like Elaniti, CinSOIL, and Xsupraare emerging to baseline soil health using microbial analysis, satellite imagery, and spectroscopy. They then guide regenerative practices that restore organic matter and boost resilience.
Second, we also need to focus on optimizing water usage. Precision irrigation is key to both climate adaptation and emissions reduction. Startups such as Verdi, EarthMetric, and Telaquaare using sensors, IoT, and AI to schedule irrigation exactly when and where it is needed. These systems often cut water use by 50 to 70 percent while improving yields.
Lastly, solutions in this space must be continually integrated. One-off interventions do not last. We need a baseline, roadmap, deploy, and track cycles. Companies like Farmevo AI provide AI monitoring services to improve such productivity. AI models can continuously analyze satellite data, in-field sensors, and weather patterns to track progress, flag risks, and adjust strategies in real time. This creates a feedback loop for sustained improvement. These three are the highest priority because they directly control the primary emission sources in maize production while enabling efficiency gains in every other part of the value chain.
To conclude, the global AgTech market size was approximately USD 15.49 billion in 2024 and is projected to grow at a compound annual growth rate of 15% between 2025 and 2034, reaching USD 62.67 billion by 2034.
Applying AgTechnologies to the $50 billion corn production market represents a significant opportunity. Integrating AI solutions in the input supply stage could deliver up to $1.5 billion dollars in value in the short term, making this space extremely impactful and lucrative.
We would ensure food security to the world while decarbonizing maize production, regenerating soil beneath our feet and the water that feeds it. Farmers would benefit from saved costs, higher yields and better profits. Startups have a strong chance at success, and investors can see a high return through guiding founders in growing their companies.