In accelerated growth, Artificial Intelligence impacts daily agribusiness

The Artificial Intelligence (AI) market is expected to grow 19.6% this year, reaching US$432.8 billion, according to IDC consultancy report. Companies are expected to increase investment in this resource by 28% compared to 2021. Industry, health, human resources and agriculture sectors are pointed out by experts as the most promising in the use of AI.

Interestingly, some time ago, agriculture was one of the areas where the application of this technology was imagined the least. In addition to the rural environment itself, the fact that the activity was based on consolidated traditions and practices brought up this doubt. However, even though AI began to directly impact the field just a few years ago, it has already caused unimaginable advances in efficiency.

Currently, around 10% of artificial intelligence companies focus on agriculture, and the trend, with increasing investments in the area, is for the technology to be implemented on a large scale in the coming years.

The applications cover a range of possibilities in all field processes — from planting planning to transporting the raw material to the industry. In practice, there are two main fronts of action: automation, which assists in the execution of tasks in an agile and precise way, and strategy, which uses data analysis to bring impacts on business intelligence. With its mechanisms, it is possible to test a gigantic number of alternatives until reaching the one with greatest efficiency and lower cost for the agricultural company.

Strategic diagnostics and automation for efficiency

In recent years, sensors have started to record the activities of agricultural equipment from second to second, collecting hundreds of information about the operations performed — from the simplest ones, such as machine speed and fuel level, to the most complex ones, such as hydraulic pressure and actuation of implements. As such, companies in the sector have begun to accumulate a multitude of information collected in different processes.

In this scenario, the use of AI is able to support the elaboration of diagnoses and allow actions based on predictability. Technology handles this data and designs scenarios, anticipating undesirable situations and making recommendations in real time. Some common actions include advising the ideal time to perform a maintenance on the equipment and the choice of routes and more efficient movements to perform the operations. At the same time, the analysis of machine behavior allows identifying more economical and efficient practices, supporting companies in improving their activities and allocating resources on a daily basis.

Another example is diagnostic imaging. Along with the work of drones, it is possible to process immense areas remotely, visualising where there are possible threats, weeds, fungal diseases and nutritional deficiencies. As a result, it can be precisely identified where it is necessary to apply correctives or other products to recover productivity. 

In terms of automation, the market already has vehicles with autopilot and prototypes of "self-driving" machines that need AI so as not to make mistakes or cause accidents. With innovation, in addition to the popularisation of this type of machine, we will soon have tractors and harvesters capable of operating with even more revolutionary resources. 

The idea is that the machine is as self-sufficient as possible, reducing the need for intervention by the operator. For example, they can dispense the optimal amount of pesticide to be applied in an area, identify plants ready for harvest or in need of disposal, and even change course when there is some external interference, such as an unmapped obstacle. All on their own.

Technology as a means, not an end

Despite the major opportunities for AI applications in agriculture, there are some challenges that hinder its wide access. The lack of familiarity with the technology, the high initial cost associated with its implementation and the scarce connectivity in the field are some of the factors that restrict its scope.

Moreover, it is important to remember that while the potential of artificial intelligence for agribusiness is enormous, it is only an instrument — a means, not an end, like any other technology. I tis necessary to have concrete planning and goals laid out to take advantage of your capacity. The right question when studying the possibility of adopting it is: what is the goal? 

According to the Gartner CIO and Technology Executive Survey 2022 by global consultancy Gartner, 48% of executives have already deployed or plan to deploy AI and machine learning mechanisms in the next 12 months. However, only players who have a goal set for their use, investing in qualified suppliers and training their teams, will remain ahead of the market, effectively harnessing the potential of this innovation.