Artificial intelligence and machine learning implementation status on Latam: a systematic literature review

• Autores: Palomino Vidal, Carlos, Condori Obregon, Patricia, Stolar Sirlupu, Enrique
• Formato: revisión
• Fecha de Publicación: 2024
• Institución: Universidad Tecnológica del Perú
• Repositorio: UTP-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.utp.edu.pe:20.500.12867/14501
• Enlace del recurso: https://hdl.handle.net/20.500.12867/14501; https://doi.org/10.11591/ijeecs.v36.i3.pp1911-1918
• Nivel de acceso: acceso abierto
• Materia: Artificial intelligence; Big data; Data analysis; Machine learning; https://purl.org/pe-repo/ocde/ford#2.02.04

Artificial intelligence (AI) and machine learning (ML) are disruptive technologies nowadays. It is well known that many important organizations use them to improve their productivity and processes, and many new applications are being developed as well. In Latin America, the adoption of new technologies is slower than in other parts of the world, limited by budget and trained personnel. The present research is a systematic literature review (SLR) conducted to analyze the implementation status of AI and ML technologies in Latin America, analyzing the improvements that these technologies bring to organizations. The methodology used in this literature review was PRISMA, a popular method widely used in this type of research. The findings were that the most relevant areas using these types of technologies are education and health, identifying also that their implementation improves operative efficiency, technology innovation, and competitiveness. These findings also demonstrate the lack of efforts in implementation in other business sectors like administration, agriculture, and production, which provides a great opportunity to improve in these areas in the future.