Integration of KM, CHIS, and AI in Territorial Governance: An Integrative Literature Review Focused on Small and Medium-Sized Municipalities in Brazil
Keywords:
Knowledge Management, Smart Cities, Artificial Intelligence, Territorial Governance, PRISMA 2020Abstract
In Brazil, many small and medium-sized municipalities face significant challenges in public planning due to the lack of proper knowledge management systems and skilled technical teams. Although they represent the majority of Brazilian municipalities, these cities struggle with structural limitations, leading to the fragmentation of information and hindering the creation of useful knowledge for governmental decision-making. This article presents an integrative literature review aimed at exploring how the concepts of Knowledge Management (KM), Human, Smart, and Sustainable Cities (CHIS), and Artificial Intelligence (AI) are integrated in academic research on territorial governance.
The review follows the PRISMA 2020 protocol, with searches conducted across Scopus, Web of Science, SciELO, Redalyc, and other databases, considering publications from 2010 to 2024. The review selected studies focusing on KM, smart cities, public innovation, and technologies in public administration. The goal is to determine whether these topics—KM, CHIS, and AI—are predominantly discussed in the context of large cities, with limited attention to the realities of smaller municipalities. The hypothesis is that the literature tends to overlook the technical and operational limitations of these localities, which represent the majority of Brazil’s municipalities and account for more than a third of its population.
This review emphasizes the urgent need for digital solutions that also cater to smaller municipalities, which have been historically excluded from major technological innovations. The study proposes a conceptual framework that integrates KM, CHIS, and AI, aiming to develop a public tool that enhances community tacit knowledge, strategic local governance, and evidence-based resource mobilization.
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