Technology is reshaping the world, and the agricultural sector is no exception. Artificial intelligence (AI) and predictive analytics are at the forefront of this transformation, providinginsights valuable ones that promote more efficient and sustainable management. E-commerce is becoming an increasingly important component of Brazilian agriculture. It enables an additional sales and relationship channel among the participants in the supply chain. At the same time, e-commerce facilitates data collection and analysis, which can improve demand forecasting accuracy.
Brazil is at the forefront of research and development of technologies. We are transitioning from Agriculture 4.0, which focuses on machines and technological solutions, to Agriculture 5.0. This new phase incorporates robotics,machine learningand AI to agricultural production systems, focusing on productivity and sustainability.
Predictive analysis
AI, with its ability to process and analyze large volumes of data, is being used to identify patterns and relationships that were previously difficult to detect. This is especially useful in agriculture, where factors such as climate, soil, and cultivation practices can have a significant impact on production. As a subfield of AI, predictive analytics uses historical data and machine learning algorithms to forecast future demand and optimize production and distribution.
Agtechs
According to Embrapa (Brazilian Agricultural Research Corporation), more than 2,000 Brazilian agtechs (startups dedicated to agribusiness) are driving the sector with IoT (Internet of Things) and AI tools. Furthermore, the investment value in AI in the global agriculture market, according to Statista, is expected to grow to approximately US$ 4.7 billion by 2028. It is a promising transformation for the sector.
Challenges
The successful implementation of technologies in agribusiness faces some challenges related to data collection and analysis of large volumes of data, as well as the need to develop suitable machine learning algorithms and ensure data security.
Still, they should shape the evolution of agribusiness, helping companies not only with demand forecasting but also with supply chain optimization and operational efficiency improvement. Additionally, they can help promote sustainability by reducing waste and improving food safety and quality.
