Artificial Intelligence as a Driver of Innovation in Rondônia’s Agriculture

Autores/as

DOI:

https://doi.org/10.18227/1982-8470ragro.v20i00.8772

Palabras clave:

Agribusiness. Artificial intelligence. Sustainability. Productivity.

Resumen

Rondônia’s Agriculture faces challenges in adopting precision technologies due to edaphoclimatic heterogeneity, land fragmentation, and limitations in digital infrastructure, as well as a scarcity of studies that quantify the impacts of artificial intelligence (AI) in the Amazonian context. This study presents a literature review, conducted according to the PRISMA protocol, focusing on the applications and impacts of AI mediated by drones, smart sensors, and predictive analysis systems in agriculture in Rondônia. A total of 31 national and international publications (2010–2025) from the Scopus, Web of Science, SciELO, and Google Scholar databases were analyzed using the PICO strategy, covering variables such as productivity, environmental sustainability, and economic feasibility. It was observed that, although few empirical studies have been carried out directly in Rondônia, evidence from other regions and tropical contexts indicates potential gains of up to 10 bags per hectare in grain production and reductions of up to 90% in pesticide use with AI-based solutions. These results, although inferential, suggest high potential for local application, especially in crops such as coffee, cocoa, and soybeans. In addition to promoting production efficiency, AI contributes to lowcarbon agricultural practices and the mitigation of environmental impacts. In economic terms, analyses indicate a return on investment within up to three harvests, depending on production scale, while small and medium-sized producers remain dependent on cooperatives and credit policies to enable access. It is concluded that AI is promising for agriculture in Rondônia, but its full adoption requires public policies, digital inclusion and the strengthening of regional research.

Publicado

10/01/2026

Número

Sección

Thematic Review Article