Inteligencia artificial y eficiencia en los costos de producción agrícola: un estudio bibliométrico

Artificial intelligence applied to agricultural production has become an increasingly relevant topic in recent scientific literature, particularly because of its connection with efficiency, resource management, and the reduction of operating costs. Even so, existing studies are still distributed across technical, productive, and economic approaches, which makes it difficult to understand how this research field has actually taken shape. Based on this gap, the objective of this article was to analyze the evolution of scientific production on artificial intelligence and efficiency in agricultural production costs through a bibliometric study of documents indexed in Scopus between 2015 and 2026. To do so, performance indicators and science mapping techniques were used to identify publication trends, influential sources, author productivity, thematic structures, and emerging research lines. The results show a growing field, marked by high levels of collaboration, thematic dispersion, and an increasing orientation toward precision agriculture, data-driven decision making, and cost reduction. The main contribution of the study lies in organizing a fragmented body of literature and identifying the conceptual cores that are currently guiding academic discussion. It is concluded that artificial intelligence does not operate only as a technological support tool, but as an articulating axis between productive management, input optimization, and economic sustainability in agriculture.