Artificial intelligence is gaining ground in agricultural

Artificial intelligence is changing a little-known stage of agriculture: the development of the machines that reach the fields. Used by engineering teams to analyze data, run simulations, and evaluate different design alternatives, the technology is helping manufacturers accelerate the creation of tractors, sprayers, harvesters, and planters. 

At AGCO, which owns brands such as Massey Ferguson, Valtra, and Fendt, artificial intelligence has become part of the new product development process, alongside digital tools already used by engineering. The goal is to make the evaluation of solutions more agile and expand the ability to test scenarios even before the construction of the first prototypes. 

According to Paulo Vilela, Engineering Director at AGCO, recent studies conducted in engineering and software development environments indicate productivity gains of between 20% and 40% in analysis, simulation, and development activities assisted by artificial intelligence. In agricultural machinery engineering, the technology allows for the evaluation of more design alternatives, accelerates simulations, and anticipates the identification of potential problems even in the virtual phases of development, reducing the time needed to transform concepts into solutions for the field.

Although technology is gaining ground, developing a new agricultural machine remains a complex task. A project can take three to four years to reach the market and involve more than 300 engineers, as well as specialists in areas such as manufacturing, quality, validation, purchasing, marketing, and customer service.

"The development of a machine begins long before the production phase. We listen to producers, study the needs of different agricultural operations, and evaluate various technical possibilities until we arrive at the final solution," says Paulo Vilela. 

Much of this work currently takes place in virtual environments. Before any component is manufactured, engineers use digital models to evaluate the behavior of structures, systems, and components under different operating conditions. Artificial intelligence complements this process by enabling faster analysis of large volumes of information, supporting decisions throughout development. 

The participation of rural producers is also crucial. The teams collect information directly in the field to understand the challenges faced by operators and identify opportunities for improvement. These contributions help transform practical needs into features that will be incorporated into the new equipment. 

After the virtual stages, the physical tests begin. The prototypes undergo evaluations in the laboratory and under real working conditions to verify performance, durability, and reliability. The tests reproduce situations found in different agricultural regions of Brazil, considering factors such as climate, terrain, soil types, dust, humidity, and intensity of use. 

In some projects, validation accumulates thousands of hours of operation. During testing, sensors installed on the equipment continuously record information about the machines' operation. The collected data is returned to the engineering teams, who use this information to improve components, electronic systems, and embedded software. 

It is worth highlighting that artificial intelligence is also present in the machines themselves. Connectivity features, sensors, image processing, and automation allow equipment to interpret information in real time and perform operations with greater precision. The development of these technologies is part of a series of research projects aimed at increasing the efficiency of agricultural activities. 

Brazil occupies a strategic position in this process. AGCO maintains research and development centers in Mogi das Cruzes (SP), Canoas (RS), and Ibirubá (RS), responsible for creating and validating technologies for tractors, sprayers, harvesters, planters, and engines. Some projects conceived by Brazilian teams are produced and marketed globally. 

“The adoption of artificial intelligence in the development of agricultural machinery follows a trend observed in various sectors of industry. In agribusiness, the technology has been contributing to accelerating analyses, expanding testing capacity, and supporting the creation of equipment prepared for the challenges of an agriculture that demands productivity, precision, and operational efficiency,” concludes Vilela.