<img decoding="async" class="size-full-width wp-image-1581155" src="https://observer.com/wp-content/uploads/sites/2/2025/09/jahmy-hindman-1.png?w=970" alt='Professional portrait of Jahmy Hindman, SVP & CTO of John Deere, smiling at the camera while wearing a light blue dress shirt. He is positioned in front of a modern office background with white paneled walls. The image includes “A.I. Power Index” branding with his name and title “SVP & CTO, John Deere” on the right side.’ width=”970″ height=”647″ data-caption=’Jahmy Hindman, SVP & CTO at John Deere, is leading the agricultural giant’s AI transformation, including the development of See & Spray technology that reduces herbicide use by up to two-thirds and a 2026 initiative to connect 1.5 million machines through satellite connectivity. <span class=”media-credit”>Courtesy of John Deere</span>’>
Jahmy Hindman, featured on this year’s A.I. Power Index, oversees the integration of artificial intelligence into John Deere’s agricultural equipment, transforming the tractors, combines and tillage machinery that generations of farmers have relied upon into precision-guided, autonomous platforms. Under his leadership, John Deere has developed A.I. solutions that address the unique challenges of agriculture, where technology must perform reliably in harsh rural environments and deliver measurable results for farmers who get only one chance per year to maximize their yields. Hindman is spearheading John Deere’s ambitious 2026 initiative to connect 1.5 million agricultural machines through satellite connectivity, enabling real-time operations in regions lacking cellular coverage and accelerating the company’s A.I. model training capabilities. With global food demand expected to rise as the population approaches 10 billion by 2050, and the average farmer now 58 years old working 12-18-hour days, Hindman recognizes the critical role A.I. plays in addressing agriculture’s demographic and productivity challenges. His work extends beyond traditional farming applications to predictive maintenance engines, digital twins and advanced analytics that transform each piece of equipment into what he describes as a self-operating intelligence platform, designed to help farmers “make every seed count, every drop count, and every bushel count” in an industry where precision and reliability are paramount.
How is the application of A.I. in agriculture different from the way tech companies use it? What does this enable for farmers?
Our customers operate in predominantly rural environments, with changing and often harsh weather conditions. This is the place our technology must perform, which is why we deploy A.I. on the edge in agricultural equipment. While models are trained in data centers, they must run efficiently on GPUs operating in the equipment. These models perform tasks beyond human capability, processing data from various sensing modalities, like camera arrays, to make real-time decisions, such as applying herbicide only where needed. They also make decisions about the environment around the equipment to enable autonomous operations.
Improving the precision of crop inputs allows a farmer to turn a highly varied, dynamic environment like farming into a more manageable and predictable one. This is what differentiates A.I. in farming from the digital-first applications more common in tech companies. That said, the equipment operating in agriculture collects a significant amount of operational and agronomic data. This data lays the foundation for digital-first A.I. insight solutions, which is then created to enable farmers to make better management decisions through their crop cycles.
Computer vision and machine learning are two specific types of artificial intelligence that enhance observation and decision-making for farmers. These technologies help farmers “see” beyond human capacity to observe what’s happening at critical junctures and make precise decisions in real-time throughout the growing season. Take autonomous tractors, for example: Camera arrays can be installed on tractors for a 360-degree view of a tractor’s surroundings, enabling high-quality depth perception to eliminate false positives like shadows. This precision allows farmers to turn a highly varied, dynamic environment, like farming, into a more manageable, predictable one. This is what differentiates A.I. in farming from the digital-first applications common in tech companies.
How does Deere build A.I. products that deliver efficient, measurable benefits to improve a farmer’s bottom line?
With global food demand expected to rise as the population nears 10 billion by 2050, the need for efficiency and sustainability in agriculture has never been greater. At John Deere, it’s our goal to provide farmers with the tools and technology they need to produce the food, fuel and fiber we all rely on. Our approach to A.I. starts with solving real problems that impact a farmer’s bottom line and productivity in the field. Our products are designed and tested with farmers to ensure they meet their needs.
One way we’re meeting this challenge is with See & Spray, which uses computer vision and machine learning to detect where every weed is in a field and precisely apply herbicide only where it’s needed. This plant-level management technology gives a machine the gift of vision, allowing it to “see” more closely with 36 cameras attached to the machine’s 120-foot carbon fiber boom. Processors determine if an individual plant is a crop or weed and send commands that deliver a precise dose of herbicide where the weed is. This See & Spray technology can reduce the amount of herbicide needed by up to two-thirds, which allows farmers to grow healthier crops. This also saves farmers money, reducing the amount of fertilizer and herbicide needed.
The global population is projected to reach 10 billion by 2050, while the average farmer is 58 and working 12-18-hour days. How is John Deere using A.I. to address this demographic challenge before it becomes a food crisis?
John Deere delivers highly efficient, automated farm equipment that maximizes productivity throughout the growing cycle to make every seed count, every drop count, and every bushel count. For example, our latest combine harvesters are packed with automated technologies designed to optimize harvesting efficiency. Using stereo cameras and satellite imagery, the machine continuously analyzes field conditions in real time, adjusting the speed of the machine as it moves through uneven terrain. This intelligent automation ensures every bushel is captured from the field and allows farmers to focus on other value-added tasks across the farm.
Barron’s predicted Deere’s stock to grow by 50 percent due to the success of its A.I.-enabled solutions. Deere hit all-time highs in May. Which A.I. capabilities are driving that momentum, and how are they impacting farmers?
The edge A.I. solutions we’ve deployed are aimed at helping farmers do more with less. See & Spray reduces herbicide applications while protecting, and in some cases improving, crop yields. Predictive Ground Speed Automation improves the performance of the harvesting operation while reducing the skill level necessary for the operator. Autonomous tractors allow the farmer to get necessary work done at the time it needs to be done when available labor is being used on more valuable tasks.
Our momentum is driven by A.I. solutions that create tangible value for farmers, saving them time, reducing costs, and improving yields. Today’s farms generate vast amounts of data. John Deere Operations Center, the operating system for the farm, allows farmers to set up their equipment, create work plans for each field, monitor every machine in real-time as it completes work, and analyze the data for smarter and faster decisions on the farm. These capabilities are reshaping how modern farming is done.
John Deere is expanding satellite connectivity to reach farmers worldwide, including regions like Brazil. How are these connectivity solutions helping farmers overcome infrastructure gaps to unlock value in their operations?
Brazil is one of the world’s top exporters of agricultural products; however, roughly 75 percent of the country lacks secure and reliable connections. This makes it challenging for farmers to take advantage of the latest technology, some of which requires reliable internet. Satellite communication services, like Deere’s SATCOM service, fill this connectivity gap and allow farmers to improve productivity, profitability and sustainability. With improved connectivity via satellites, farmers can work more efficiently and productively, reduce downtime, and coordinate among machines for more efficient use of resources.
What’s one assumption about A.I. that you think is dead wrong?
A.I. will replace farmers. This isn’t the case. Rather, A.I. enhances and complements the work of the farmer, automating repetitive tasks, reducing variability in the process and providing tools for smarter, more efficient operations. Deere shares farmers’ commitment to protecting the land for future generations. We see A.I. as a tool that empowers farmers to do more with less, leading them into the digital era while solving decades-long challenges from limited skilled labor to managing weather variability.
Was there one moment in the last few years where you thought, “This changes everything” about A.I.?
A.I. is really about compute, algorithms and data. I’ll highlight two examples. For compute, Deere charted GPU performance over time, looking at CUDA cores and clock speed. When we plotted our own embedded GPU performance alongside current state-of-the-art and projected roadmaps from our compute partners, the curve was clearly exponential—even in embedded GPUs. That’s significant because compute has traditionally been a limiting factor for embedded A.I. applications, and now that constraint is disappearing.
The second example is data. Deere recently began streaming 150 Mbps with 70 ms latency over satellite connections. For our applications, data is generated on the edge, and collecting it in sufficient volume is challenging, often constrained by seasonal growing cycles. With a persistent, high-bandwidth connection, we can move that edge data more quickly, which accelerates the model training flywheel and leads to faster, more robust improvements.
What’s something about A.I. development that keeps you up at night, that most people aren’t talking about?
In farming, the stakes are high. Farmers get one chance a year to do it right, so every decision and every action matters. We’re responsible for developing consistent, always-on A.I.-enabled technology that farmers trust. Farmers need to know that when they invest their hard-earned dollar into precision technology on our machines, it will perform exactly as expected every time. Making trustworthy A.I.-enabled tools for the people who need it most is what drives us to keep developing more innovative, cutting-edge technology.
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