Precision agriculture: Artificial intelligence as a tool helping farmers

April 17, 2026

Dr. Bruno Basso is advancing the responsible use of artificial intelligence (AI) in precision agriculture, demonstrating how this once futuristic technology has become a practical decision support tool that helps farmers manage complex operations by analyzing large datasets and generating insights quickly. This perspective, written by Rich Price of Michigan State University Extension and the Basso Digital Agriculture Lab, highlights how AI is being integrated with research-based agronomy to support real-world farm decisions while maintaining a strong emphasis on scientific rigor and field-level context.

Powered by large language models, AI can efficiently summarize research, synthesize weather and market data, and outline workflows for tasks such as variable rate seeding and nutrient management, but Basso emphasizes that these tools do not replace agronomic expertise or the inherent complexity of agricultural systems, where outcomes depend on the interaction of soil, crops, management decisions, and unpredictable weather. Examples developed within the lab show that AI can support decisions such as identifying management zones, summarizing fertilizer recommendations, and tracking precipitation and input price trends, while also revealing key limitations, including its inability to predict weather or accurately account for field-specific conditions without quality data inputs. For instance, while AI can outline steps for creating a corn seeding prescription using spatial data layers and population ranges, research and Extension guidance reinforce the need to incorporate multi-year yield stability, soil characteristics, and economic considerations, underscoring that strong yields depend not only on inputs but also on environmental conditions like rainfall and temperature.

Under Basso’s leadership, ongoing work with Michigan farmers continues to demonstrate that AI is most effective when paired with Extension-backed science, local knowledge, and human judgment, enabling improved decision-making without oversimplifying the complexity of modern agricultural systems.

Read the full article at MSU Extension Precision Agriculture