How the modern farmer is embracing AI and automation technology in their everyday operations to set a new standard for innovation across other industries.
The agriculture industry has always been a driving force for innovation. Farmers were arguably among the original data scientists, keeping meticulous records on everything from weather patterns and soil conditions to seed germination rates and yields, drawing conclusions to make decisions for future crop years . Even though agriculture has been at the forefront of technological and industrial advancements, it has not been viewed as a leader in digital technology.
However, digital technologies used on farms have become a source from which other industries can learn and optimize operations. The same solutions implemented into farming operations have the potential to advance and automate processes, limit resources and human oversight, and enhance productivity across various industries—specifically regarding AI and automation.
Farmers’ work is a challenging calculus of monotony and precision. The days are long, but the years are short, and the labor is taxing. The average American farm is 464 acres—more than 350 football fields—with larger farms running thousands of acres, mile upon mile of land needing to be tended to: with razor-thin margins, every square inch is significant. The weather is increasingly unpredictable, resources are stretched thin, and the demand to feed a growing global population is looming.
To rise above these challenges, technology that enables everything from self-driving tractors to AI-powered devices is being leveraged on farming equipment to perform critical, highly repetitive tasks more precisely, more sustainably, and with less training/skilled operators needed. With proper implementation, other industries can also benefit from similar solutions leveraged by farmers, ultimately streamlining operations, cutting costs, and conserving resources.
Automating a farmer’s crop production
Time is always at a premium on farms. Automation and autonomous applications are revolutionizing agricultural labor, creating a new way to optimize operations with less human oversight. Autonomous solutions increase efficiency and alleviate stress on farmers, lowering the demand for highly skilled labor and thus widening the available talent pool. For instance, tillage—the preparation of land for growing crops—is an arduous, lengthy task that farmers must complete during a tightly constrained period of time before they plant.
But now, with the advancement of AI and sensors, combined with deep neural networks, farmers can complete this task via autonomous tractors. No driver is required—without a driver operating the tractor, these sensors and neural networks tell the machine exactly how to create optimal planting conditions. By stirring up the earth with centimeter-level precision of depth and positioning, the soil is prepared for highly consistent seed placement despite often drastic soil and residue changes across even one field. Harnessing the power of stereo cameras, lidar and radar, tractors autonomously navigate fields, freeing up the farmer to monitor operations remotely on a device while seeing a stream of real-time data on their tablets to fine-tune performance in real-time.
This meticulous approach conserves fuel and maximizes efficiency while minimizing soil disturbance and environmental impact. Farmers are thus freed to focus on strategic decisions, data analysis, and operational fine-tuning for optimal results.
Once the crop is planted, computer vision cameras and massive data sets are able to distinguish crops from weeds. These sensors, integrated with sprayers and spreaders, can identify plant growth stages and recognize the crop’s health across the fields. This helps determine the exact amount of nutrients, insecticides and herbicides needed to optimize a crop’s yield. Data-informed spraying and spreading machines take this analysis and automatically apply the precise amount of nutrients or pest control each individual plant needs.
When it’s time to harvest, farmers use combine harvesters to cut and gather crops, remove grain from plants, and separate chaff from seed. Camera sensors capture and process detailed images of harvested crops to determine the quality of each grain. Analyzing moisture levels, grain quality, and debris content at the edge is crucial in optimizing this process by using deep learning models trained to recognize patterns in grain samples.
The combine adjusts automatically to stay on task, changing speed or threshing settings to optimize the predetermined goals and quality indicators set by the farmer in the system. Millions of decisions are made autonomously every few seconds, and these real-time updates and adjustments reduce waste by minimizing crop damage, collecting every possible grain, and ensuring the highest quality grain sample cleanliness free of foreign debris. It also improves efficiency by enabling machines to make data-driven decisions on the go, maximizing farmers’ crop yield while reducing operational stress and costs.
Automating the path to autonomy elsewhere
AI and automation are transforming the very essence of farming, but the capabilities of this technology are not limited to farms. Tedious, mundane tasks are a part of operations in every industry. There is an opportunity for AI and automation to make significant impacts in workplaces beyond the agriculture space. As AI grows more and more capable of minimizing human intervention, the capacity and potential for increased efficiency and productivity—no matter the industry—becomes even greater.
AI and autonomous applications optimize tedious tasks that traditionally take up enormous amounts of time, money, and resources. This is precisely why agentic AI, the type of AI that allows machines to make autonomous decisions and take action without human oversight, is gaining so much traction. As the technology on farms demonstrates, there are elements of repetitive, everyday operations that can now be completed without human oversight or intervention, allowing companies to transform operations. Not only can agentic AI act as a digital teammate allowing organizations to streamline processes and reduce error, it will also free up peoples’ time, labor, and effort to strengthen operations within the organization where more human brain power and empathy are needed – something a machine cannot replace. With AI and autonomous applications taking the world (and the agriculture industry) by storm, industries all across the globe can no longer ignore these technologies. It’s not a matter of when they will be used, but how they can be used to optimize operations.