On a small plot in Kenya, a drone flies over maize crops while a ground sensor measures soil moisture. The data is sent to an app on the farmer's phone, which alerts him: he only needs to water two of his four hectares. Scenes like this, still a minority, are multiplying in 2026 as part of a quiet but profound transformation in food production.
Precision agriculture could reduce water use by 20% to 50% and boost yields by up to 30% in key crops, according to FAO and university studies.
Technology in the service of the field
Precision agriculture combines satellite imagery, drones, soil sensors, weather stations and artificial intelligence algorithms to apply inputs — water, fertilizers, pesticides — only where and when needed. The goal is to optimize resources and minimize environmental impact. In countries like Brazil, Chile and Mexico, large producers of soybeans, corn and berries already use these tools to monitor pests and schedule irrigation.
The recent leap is due to cheaper sensors and expanding rural connectivity. In regions where the internet did not reach before, low-power networks and low-orbit satellites now allow real-time data transmission. Artificial intelligence processes that information and suggests decisions: what to plant, when to harvest, where to apply fungicide.
Small farmers, big challenges
Access remains unequal. While large farms in the US or Europe integrate autonomous tractors and smart irrigation systems, most of the 500 million smallholder farmers worldwide lack the resources to acquire these technologies. However, international cooperation initiatives and local startups are developing low-cost platforms based on smartphones and open data, adapted to realities in sub-Saharan Africa and Southeast Asia.
Precision agriculture
A set of technologies that allow localized crop management, applying inputs in variable doses according to the specific needs of each area of the field. It reduces costs, increases yields and reduces environmental footprint.
Implications for food security
With a world population exceeding 8.5 billion and climate change altering rainy seasons and increasing drought frequency, precision agriculture is not a luxury but a necessity. The FAO estimates food production must increase by 60% by 2050, and arable land is not growing. Technology offers a way to close that gap without expanding the agricultural frontier, protecting forests and ecosystems.
The role of artificial intelligence
Artificial intelligence has become the brain of this revolution. Machine learning algorithms analyze satellite images to detect water stress or diseases before they are visible to the human eye. Predictive models anticipate pests and recommend optimal planting windows. Companies like IBM, Microsoft and local startups compete to offer affordable solutions, while governments and development banks finance pilots in developing countries.
Challenges and criticisms
Not everything is green lights. Dependence on data and algorithms raises privacy and digital sovereignty risks: field data could end up in the hands of large corporations. Additionally, the digital divide can deepen inequality if small farmers are left out. Social organizations and academics call for regulatory frameworks that ensure technology benefits everyone, not just large producers.
What does this mean for the world?
Precision agriculture will not replace the need for public policies, rural infrastructure investment and fair trade, but it offers a powerful tool to produce more with less. In a context of climate crisis and demographic pressure, every drop of water and every gram of fertilizer counts. The question is not whether this technology will be adopted, but whether we know how to distribute its benefits equitably.