Artificial Intelligence for Business Decision-Making in Latin America: A Systematic Review of Evidence, Contributing Countries, and Key Insights

In recent years, Latin America has experienced a growing incorporation of Artificial Intelligence (AI) into business and organizational environments, driven by digital transformation, data availability, and competitive pressures. Across multiple sectors, AI-based tools are increasingly used to support complex decision-making processes, raising both opportunities and challenges related to efficiency, ethics, and organizational readiness. Within this context, this systematic review examines the scientific evidence on the implementation of AI in business decision-making in Latin America. Following PRISMA 2020 guidelines, a systematic search was conducted in the Scopus database for articles published between 2021 and 2025. The search strategy combined Boolean operators related to AI and decision-making. Inclusion criteria comprised original, open-access research articles conducted in Latin American countries and published in Spanish or Portuguese. After screening for temporality, geographic focus, language, document type, accessibility, duplication, and relevance, 27 studies were selected from an initial pool of 276,302 records. The studies originated mainly from Peru, Colombia, Chile, and Ecuador. The findings show that AI is applied across sectors such as industry, agriculture, finance, education, and public services, primarily to enhance predictive capacity, automate processes, and support data-driven decisions. While AI adoption improves efficiency, cost reduction, and strategic innovation, its effectiveness depends on staff training, ethical governance, and strategic alignment. Persistent challenges include resistance to change, data quality limitations, and concerns regarding transparency and algorithmic bias. Overall, AI emerges as a transformative but context-dependent tool for business decision-making in Latin America.