Tecnologías emergentes y de datos aplicadas al sector público: Una revisión sistemática de la literatura copilotada por IA

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This study aimed to explore the use of emerging and data technologies (Rotolo et al., 2015) in the public sector, investigating their applications, challenges, and benefits through the analytical perspectives proposed by Criado et al. (2024). To amplify the analytical capacity, minimize data process...

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Detalles Bibliográficos
Autores: Vasconcellos Leão Lyrio, Maurício, João Lunkes, Rogério, Vasarhelyi, Miklos
Formato: artículo
Fecha de Publicación:2025
Institución:Pontificia Universidad Católica del Perú
Repositorio:PUCP-Institucional
Lenguaje:portugués
OAI Identifier:oai:repositorio.pucp.edu.pe:20.500.14657/205211
Enlace del recurso:https://revistas.pucp.edu.pe/index.php/contabilidadyNegocios/article/view/32270/28159
http://hdl.handle.net/20.500.14657/205211
https://doi.org/10.18800/contabilidad.202502.003
Nivel de acceso:acceso abierto
Materia:Emerging technologies
Artificial intelligence
Public sector
Systematic literature review
Tecnologías emergentes
Inteligencia artificial
Sector público
Revisión sistemática de la literatura
Tecnologias emergentes
Inteligência artificial
Setor público
Revisão sistemática da literatura
https://purl.org/pe-repo/ocde/ford#5.02.04
Descripción
Sumario:This study aimed to explore the use of emerging and data technologies (Rotolo et al., 2015) in the public sector, investigating their applications, challenges, and benefits through the analytical perspectives proposed by Criado et al. (2024). To amplify the analytical capacity, minimize data processing time and analyze relevant studies on the topic in high-impact journals, the study adopts a systematic literature review process, inspired by H. Gu's et al. (2024) co-piloted artificial intelligence (AI) in audit studies and informed by prior literature review methods (Lyrio et al., 2018; Page et al., 2021; Ruijer et al., 2023; Straub et al., 2023). Based on Criado’s et al. (2024) perspectives, the results showed that, at a macro level, AI and big data stand out in the formulation of public policies. At a meso level, use cases demonstrated the potential of these technologies to optimize processes and improve organizational efficiency. At a micro level, the studies highlighted the personalization of public services and improvements in interaction with citizens, although they also warned of risks such as digital exclusion and loss of trust in governments. The study concludes that research on the topic is still in an evolving phase and has prioritized ethical and regulatory issues to balance efficiency, innovation, and the democratic values of the public sector.
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