Generative AI in Software Development: Impact on Various Industries

• Autores: Lulichac Ramos, Guliana, Pantoja Payajo, Fernando Olivert, Torres Villanueva, Marcelino
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Universidad La Salle
• Repositorio: Revistas - Universidad La Salle
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.ulasalle.edu.pe:article/259
• Enlace del recurso: https://revistas.ulasalle.edu.pe/innosoft/article/view/259; https://doi.org/10.48168/innosoft.s23.a259; https://purl.org/42411/s23/a259; https://n2t.net/ark:/42411/s23/a259
• Nivel de acceso: acceso abierto
• Materia: Generative artificial intelligence; machine learning; generative model; neural network; industry; Inteligencia artificial generativa; aprendizaje automático; modelo generativo; red neuronal; industria

Software development underwent a significant transformation through the integration of generative artificial intelligence (AI) technologies. The research set out to evaluate the influence of these technologies in different industries and their implications on development processes through a systematic analysis of their impact and implementation in various industrial sectors. The PRISMA methodology was implemented for the analysis of publications between 2022 and 2024 in the Scopus and SciELO databases, using specific inclusion criteria and key terms related to AI applications. The study revealed significant adoption in the pharmaceutical, food, dental and maxillofacial health, maritime, mining, telecommunications, mental health and medical education industries, registering a substantial increase in scientific production, which evolved from 40 documents in 2022 to 54 in 2024. The geographical analysis showed a leadership of China in Scopus publications, while Brazil highlighted its research in SciELO. The findings showed that these technologies optimized the efficiency in the generation and debugging of code, democratizing software development and facilitating the creation of effective solutions without requiring advanced technical expertise. It was concluded that, despite the challenges in accuracy and ethical implications, tools based on generative AI were consolidated as fundamental elements for organizational competitiveness in the contemporary technological environment.