Atribuição de tarefas no serviço público: uma solução a partir da inteligência artificial generativa

Authors

  • João Kaian dos Santos Perlingeiro Universidade Federal de Uberlândia
  • Carla Bonato Marcolin

DOI:

https://doi.org/10.48075/comsus.v12i1.34517

Abstract

This study proposes to optimize the task assignment process in the Municipal Department of Public Works (SMO) of Uberlândia through a human-machine interaction approach. The organization focuses on public works oversight, and the research identifies challenges such as delays, high costs, and workload asymmetries stemming from the lack of a structured system. The methodology involves analyzing the existing process, implementing automation technologies, and leveraging artificial intelligence to achieve fairer and more efficient allocation. The result is a proposed process for SMO and a model adaptable to other organizational contexts. The study enhances resource management efficiency and improves services delivered to the public.

Published

15-07-2025

How to Cite

DOS SANTOS PERLINGEIRO, J. K.; BONATO MARCOLIN, C. Atribuição de tarefas no serviço público: uma solução a partir da inteligência artificial generativa. Revista Competitividade e Sustentabilidade, [S. l.], v. 12, n. 1, p. 102–119, 2025. DOI: 10.48075/comsus.v12i1.34517. Disponível em: https://saber.unioeste.br/index.php/comsus/article/view/34517. Acesso em: 19 jul. 2025.